Copyright TechTarget - All rights reserved Customer experience management (CEM) requires technology and strategy to enable excellent customer experience (CX). On this site, CX leaders can read about tech innovations, news and the latest best practices successful brands employ to create cutting edge digital experiences. https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Sat, 06 Jun 2026 04:11:21 GMT https://www.techtarget.com/searchcustomerexperience editor@techtarget.com <p>CX used to be easier to describe as a set of systems.</p> <p>There was CRM. There was the contact center. There were marketing tools, customer data platforms, analytics systems, feedback tools and digital engagement channels. Each had a defined role and its own team. Each could be improved, replaced or optimized -- more or less -- on its own.</p> <p>That version of CX is getting harder to defend.</p> <p>Customer experience now depends less on any one tool and more on whether the larger environment holds together. The question is not only whether a company has CRM data, contact center AI, personalization tools, journey analytics or marketing automation. The harder question is whether those systems can coordinate the work that sits between them.</p> <p>That is why CX orchestration is becoming the hard part. It is the layer of work that determines whether customer context follows the customer, whether a handoff works, whether AI acts on the right information, whether service learns from what marketing promised and whether someone owns the next step when the customer problem crosses systems.</p> <p>Customers do not experience the CX stack. They experience the handoffs.</p> <section class="section main-article-chapter" data-menu-title="CX is no longer a collection of separate tools"> <h2 class="section-title"><i class="icon" data-icon="1"></i>CX is no longer a collection of separate tools</h2> <p>The front office is becoming more connected.</p> <p>CRM, contact center platforms, digital engagement tools, analytics systems, customer data platforms and AI features are increasingly treated as part of a single operating environment. That makes sense. Customers do not move through a company by software category. They research, buy, onboard, use, ask, complain, renew and sometimes leave.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Customers do not experience the CX stack. They experience the handoffs. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>The work behind those moments usually cuts across systems.</p> <p>A customer might land in service because a product page was unclear, a bill was confusing or a self-service path did not actually solve the problem. A marketing offer might create an expectation that support cannot meet. A sales handoff might leave onboarding to figure out the customer context after the fact.</p> <p>From inside the company, those might look like separate issues. To the customer, they feel like one experience. None of that is new. What is changing is how much companies now expect software and AI to smooth out those edges.</p> <p>That expectation raises the bar. It is no longer enough for each CX tool to perform its own function well. The tools must support a larger flow of customer work. They have to carry context across touchpoints, route the right work to the right place and make it clear who owns the next step.</p> <p>That is orchestration, not just integration. Integration means systems can connect. Orchestration means the work, context, rules and ownership move correctly across those systems.</p> <p>That is also where <a href="https://www.techtarget.com/whatis/definition/customer-journey-orchestration">customer journey orchestration</a> fits the broader CX problem. It can help coordinate customer experiences across channels, but the enterprise must still ensure the work, data and ownership behind those experiences do not break down.</p> <p>That is where <a href="https://www.techtarget.com/searchcustomerexperience/tip/Omnichannel-orchestration-engages-customers-drives-revenue">omnichannel orchestration</a> becomes more than a channel strategy. The real work is making sure customer context, next steps and business rules do not reset every time the customer moves from one touchpoint to another.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/how_a_total_experience_strategy_enables_transformation-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/how_a_total_experience_strategy_enables_transformation-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/how_a_total_experience_strategy_enables_transformation-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/how_a_total_experience_strategy_enables_transformation-f.png 1280w" alt="Diagram showing how a total experience strategy connects customer experience, employee experience, user experience and multiexperience." height="426" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>CX orchestration depends on more than improving one customer-facing tool. It requires coordination across customer experience, employee experience, user experience and multiexperience workflows. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Service shows where orchestration breaks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Service shows where orchestration breaks</h2> <p>The contact center is often where CX orchestration issues first surface.</p> <p>Customers usually contact service after something else has already gone wrong. The product was confusing. The policy was unclear. The bill did not make sense. The website did not solve the problem. The customer had to repeat information. The handoff from one team to another failed.</p> <p>From the company's point of view, that might look like contact volume. From the customer's point of view, it feels like effort. That is why improving the <a href="https://www.techtarget.com/searchcustomerexperience/tip/How-to-improve-the-contact-center-experience-for-customers">contact center experience</a> often depends on fixing work that starts outside the contact center.</p> <p>That is where contact center metrics can be misleading.</p> <p>A company can improve its handle time, deflect more contacts, or route calls more efficiently while still leaving the customer's problem mostly untouched. The contact center experience might improve at the edges, but the reason customers needed help in the first place might still lie elsewhere -- on the website, the bill, the policy, the product or the handoff between teams.</p> <p>Service can absorb that work for a while, but it cannot fix the entire operating model on its own.</p> <p>That is where orchestration becomes organizational, not just technical. Product, billing, operations, digital, marketing and service may all touch the same customer problem. If those teams do not share the signal, the same issue keeps landing in the contact center.</p> <p>The contact center ends up processing the symptoms. The business fails to fix the cause.</p> </section> <section class="section main-article-chapter" data-menu-title="AI can make weak orchestration more visible"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI can make weak orchestration more visible</h2> <p>AI makes this problem more urgent because it can move work faster through a weak process.</p> <p>That can be useful when the work is narrow and well-defined. AI can summarize calls, route requests, support agents, retrieve knowledge, detect intent, translate conversations and reduce after-call work.</p> <p>Those <a href="https://www.techtarget.com/searchcustomerexperience/feature/Important-contact-center-AI-features-and-their-benefits">contact center AI features</a> can create real gains. But they are not the same as fixing the customer journey.</p> <p>If the knowledge base is incorrect, AI can surface the wrong answer more quickly. If the handoff is broken, AI can move the customer through a weak workflow more efficiently. If the business has not identified what keeps creating avoidable contact volume, AI might help the service team process the consequences more quickly.</p> <p>That is not transformation. It is acceleration.</p> <p>CX orchestration must answer a more basic question before the AI layer does too much: What work is the company actually trying to improve?</p> <p>If the answer is unclear, the company risks optimizing the wrong part of the problem.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/ai_sharpens_contact_center_features_and_actions-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/ai_sharpens_contact_center_features_and_actions-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/ai_sharpens_contact_center_features_and_actions-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/ai_sharpens_contact_center_features_and_actions-f.png 1280w" alt="Table showing contact center AI features, including IVR systems, self-service chatbots, agent performance, predictive customer analytics and post-call summaries." height="355" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Contact center AI can help route requests, support agents, analyze interactions and summarize conversations, but those features work best when they support a coordinated CX workflow. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Customer data must move with the work"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Customer data must move with the work</h2> <p>Most CX orchestration problems eventually become data problems.</p> <p>That is unavoidable. Customer context is scattered across the enterprise. CRM contains the account information. Marketing systems track the campaign history. Service platforms capture complaints. E-commerce systems record transactions. Product data reveals usage patterns. Billing systems track disputes. Analytics platforms identify trends.</p> <p>That is why <a href="https://www.techtarget.com/searchcustomerexperience/tip/How-to-choose-a-customer-data-platform">customer data platforms</a> sit close to the orchestration problem. A unified customer view can help, but only if the data is current, governed and available inside the workflow where the customer issue is being handled.</p> <p>A customer does not care which system owns which fact. They care whether the company seems to understand the situation.</p> <p>That does not mean every team needs every piece of data at all times. It means the right context must move with the work.</p> <p>An agent should not have to ask a customer to repeat information the company already has. A marketing team should not keep targeting a customer who is in the middle of an unresolved service problem. A service team should not discover halfway through a call that a policy, promise or product change elsewhere in the business created the issue.</p> <p>That is why CX orchestration depends on more than a unified profile. It also depends on rules, permissions, workflow design and ownership.</p> <p>Data must be usable. But it also has to be governed, current and tied to the process where it is being used.</p> </section> <section class="section main-article-chapter" data-menu-title="Orchestration is not the same as automation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Orchestration is not the same as automation</h2> <p>Automation completes a task. Orchestration coordinates the work around the task.</p> <p>That difference matters in CX because many customer problems are not single-step problems. They involve context, timing, judgment, escalation and handoffs. They often move across systems and teams before the customer sees the result.</p> <p>That is why automating one step can help without solving the larger experience.</p> <p>A refund is not just a refund if it depends on policy rules, finance approval and customer communication. A retention issue is not just a CRM note if it also depends on product usage, support history, pricing and the account team's judgment. A delivery problem might show up in service, but the real work could sit in fulfillment, logistics or e-commerce.</p> <p>Orchestration asks where the customer issue started, which systems hold the relevant context, who owns the next step, and what should happen when the workflow encounters an exception. It also asks where AI should support the work and where a person still needs to stay close to the decision.</p> <p>Those questions are not glamorous. But they are often where the customer experience succeeds or fails.</p> </section> <section class="section main-article-chapter" data-menu-title="CX orchestration needs feedback loops"> <h2 class="section-title"><i class="icon" data-icon="1"></i>CX orchestration needs feedback loops</h2> <p>A better CX system should not only resolve customer issues. It should help the business learn from them.</p> <p>That is where feedback loops matter.</p> <p>If customers keep contacting service about the same billing confusion, that should not stay a service problem. If customers struggle with onboarding, that signal should reach the teams responsible for product, documentation, digital experience and customer success. If self-service fails, the business should know whether the problem is the content, the interface, the policy or the underlying process.</p> <p>This is where <a href="https://www.techtarget.com/searchcustomerexperience/definition/voice-of-the-customer-VOC">voice-of-the-customer programs</a>, <a href="https://www.techtarget.com/searchcustomerexperience/feature/Context-is-key-The-limits-of-experience-analytics-software">experience analytics</a> and contact center insights can become more useful. Not because they produce another dashboard, but because they help the organization see where the experience is actually breaking.</p> <p>The point is not to collect more feedback; it is to make the feedback useful to the teams that can fix the cause. That is hard because the owner of the customer interaction is not always the owner of the customer problem.</p> <p>CX orchestration must close that gap.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading"></h3> <h3 class="splash-heading">What CX orchestration needs to coordinate</h3> <p>CX orchestration is not just system connectivity. It is the operating work behind the customer experience.</p> <p>At minimum, it should make clear:</p> <ul class="default-list"> <li>Which customer context needs to move across systems.</li> <li>Who owns the next step when a customer issue crosses teams.</li> <li>Where handoffs happen among service, sales, marketing, digital and operations.</li> <li>How AI-generated summaries, routing or recommendations fit into the workflow.</li> <li>When an issue should be escalated instead of automated.</li> <li>Which data source is trusted for the decision.</li> <li>What service interactions are telling the rest of the business.</li> <li>Whether metrics show a better experience, not just a faster process.</li> </ul> <p>The goal is not to make every interaction more complicated. It is to make the work behind the interaction visible enough to manage.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="The business case must be bigger than efficiency"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The business case must be bigger than efficiency</h2> <p>A lot of CX technology is still sold around efficiency.</p> <p>That is understandable. Faster service, lower cost to serve, more automation and less manual work are easy to measure. But the stronger case for CX orchestration goes beyond labor savings.</p> <p>Done well, it can reduce repeat contacts, improve customer trust, make personalization more useful, help frontline employees do better work and give leaders a clearer view of where customer problems are forming. It can also help companies connect CX investments to revenue, retention, loyalty and risk reduction.</p> <p>That is a more demanding case to make. It requires companies to measure more than speed. They need to understand whether customers are getting better answers, whether problems are being prevented, whether handoffs are improving and whether teams are acting on what the customer experience is revealing.</p> <p>Efficiency matters. But if CX orchestration only makes a broken journey move faster, it has not solved enough.</p> </section> <section class="section main-article-chapter" data-menu-title="The hard part is ownership"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The hard part is ownership</h2> <p>The biggest challenge in CX orchestration may not be the technology. It may be ownership.</p> <p>Someone must decide which systems matter, which data is trusted, which workflows should change, which AI use cases are worth scaling and which team owns the customer problem when it crosses departmental lines.</p> <p>That is where CX orchestration becomes a management issue.</p> <p>Vendors can provide platforms, integrations, AI agents, analytics and workflow tools. Those can all help. But the business still must decide how customer work should move across the organization.</p> <p>That means CX leaders, CIOs, marketing leaders, service leaders, sales leaders, operations teams and data teams cannot treat orchestration as someone else's problem.</p> <p>The customer journey already crosses their boundaries. The operating model must catch up.</p> <p>CX orchestration is the new hard part because the easy story -- add better tools, automate more work, personalize more interactions -- is no longer enough. Enterprises already have plenty of tools. What they need now is a better way to make the tools, teams, data and decisions work together around the customer.</p> <p>That is where the next phase of CX work begins.</p> <p><em>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</em></p> </section> Enterprises have plenty of CX tools, channels and AI features. The harder problem is coordinating the work, data, handoffs and ownership behind them. https://cdn.ttgtmedia.com/rms/onlineimages/customer_service03.jpg https://www.techtarget.com/searchcustomerexperience/feature/CX-orchestration-is-the-new-hard-part Fri, 05 Jun 2026 12:28:00 GMT <p>Average handle time is not obsolete and probably won't become obsolete, but it must be used properly to achieve appropriate outcomes.</p> <p>Historically, average handle time, or <a href="https://www.techtarget.com/whatis/definition/Average-handle-time-AHT-What-is-it-and-how-to-improve-it">AHT</a>, has been one of the most controversial metrics when measuring contact center agent productivity because it creates behaviors that are not aligned with customer needs.</p> <p>The problem with average handle time is it could force agents to complete phone calls in a specific amount of time and not fully resolve a customer's issue. As a result, call centers should not use average handle time as a standalone performance metric for agents.</p> <section class="section main-article-chapter" data-menu-title="A critical use of average handle time"> <h2 class="section-title"><i class="icon" data-icon="1"></i>A critical use of average handle time</h2> <p>Average handle time is important because it's a key input for calculating the workload and required staffing levels in a call center. The total workload of a call center is calculated by multiplying the projected volume of phone calls by the average handle time. The workload is one of the inputs that is then used to calculate the number of staff required on a monthly, daily and hourly basis.</p> <p>Additionally, measuring the three individual components of average handle time can provide insight into how to improve call center operations. The three components of AHT are:</p> <ol class="default-list"> <li><b>Average talk time.</b> The amount of time an agent spends speaking with the caller during a phone call.</li> <li><b>Average hold time.</b> The amount of time an agent places a customer on hold during a phone call.</li> <li><b>After-call work time.</b> The amount of time an agent performs follow-up work on a call once the caller is off the phone line. This metric is sometimes called wrap time.</li> </ol> </section> <section class="section main-article-chapter" data-menu-title="Controlling the flow of a phone call"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Controlling the flow of a phone call</h2> <p>Agents who have higher average talk times and/or average hold times may be struggling with controlling the flow of telephone calls. To address this issue, contact centers can take the following steps:&nbsp;</p> <ul class="default-list"> <li><b>Improve coaching.</b> Agents should be coached on <a href="https://www.techtarget.com/searchcustomerexperience/tip/AI-improves-customer-experience-call-center-efficiency">how to make customer interactions efficient</a>, while still showing appropriate amounts of empathy and caring. It's fine for an agent to ask callers if they had a good weekend, for example, but the agent should not get into detailed discussions of the callers' activities.</li> <li><b>Improve agent training.</b> <a href="https://www.techtarget.com/searchcustomerexperience/tip/Best-practices-for-call-center-agent-training-programs">Agents should have continuous training</a> so they become more proficient in handling customer interactions, including the ability to find information in a knowledge base.</li> <li><b>Improve automated systems.</b> Systems should be streamlined and have a logical flow so agents don't have to put customers on hold while they search for information.</li> <li><b>Implement agent assist.</b> <a href="https://www.techtarget.com/searchcustomerexperience/tip/How-agent-assist-technology-works-in-the-contact-center">Agent-assist technology</a> monitors phone interactions between a customer and agent and provides real-time guidance, information and scripting to the agent to help streamline the conversation with the customer.</li> </ul> <ul class="default-list"></ul> </section> <section class="section main-article-chapter" data-menu-title="Reduce after-call work"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Reduce after-call work</h2> <p>In many cases, a large amount of after-call work represents the amount of time agents are documenting conversations with the customer for case notes.</p> <p>A solution to this challenge is to use speech transcription technology that transcribes a conversation between a caller and an agent. This provides a <a target="_blank" href="https://sinch.com/blog/what-is-call-transcription-call-centers/" rel="noopener">written script</a> of the call that can be automatically loaded into case notes rather than having the customer service agent type out notes after a call.</p> </section> <section class="section main-article-chapter" data-menu-title="Business process changes affect AHT"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Business process changes affect AHT</h2> <p>Finally, average handle time and its three components are metrics that can measure the effectiveness of change. Average handle time -- or its specific components -- can be measured before and after a change is made to a business process to determine the effect of the change.</p> <p>In most cases, an improved business process will help reduce AHT. However, <a href="https://www.techtarget.com/searchcustomerexperience/tip/Businesses-can-benefit-from-customer-self-service-channels">increases in self-service support</a> may increase AHT because customers are completing the simpler transactions by themselves and talking with agents when they have more complex customer service issues.</p> <p>Going forward, average handle time is a critical metric that should never become obsolete. Average handle time should be used to identify improvement opportunities that drive operational efficiency along with higher levels of customer satisfaction and not a goal forced upon agents as a number they must achieve.</p> <p><em>Scott Sachs is president and founder of SJS Solutions, a consultancy that specializes in contact center strategy assessments and technology selection.</em></p> </section> No, average handle time is not obsolete. This key metric, when analyzed with other metrics, can help determine contact center staffing levels and improve agent efficiency. https://cdn.ttgtmedia.com/rms/onlineimages/customer_service02.jpg https://www.techtarget.com/searchcustomerexperience/answer/Is-average-handle-time-obsolete Fri, 05 Jun 2026 09:46:00 GMT <p>Sitecore on Wednesday acquired Scrunch, an answer engine optimization platform designed to help its customers be better recognized in AI search and summaries.</p> <p>Sitecore did not divulge the financial terms of the acquisition, but Bloomberg reported it was for about $225 million. Using algorithms different from the tried-and-true marketing practice of <a href="https://www.techtarget.com/searchcontentmanagement/answer/SEO-vs-SEM-Whats-the-difference">search engine optimization (SEO),</a> AI search agents <a href="https://www.techtarget.com/searchcontentmanagement/feature/Is-SEO-dead-How-GenAI-changed-search">operate on different principles</a> to rank -- and cite -- <a href="https://www.techtarget.com/searchcustomerexperience/feature/Answer-engines-put-marketing-tools-on-notice">the most authoritative</a> web sources for their summaries.</p> <p>Sitecore isn't the only company retooling its platform to accommodate AI search in the last year. Adobe added <a href="https://www.techtarget.com/searchcustomerexperience/news/366626187/Adobe-takes-on-AI-search-optimization-with-LLM-Optimizer">LLM Optimizer</a> and then <a href="https://www.techtarget.com/searchcustomerexperience/news/366634642/Adobe-bolsters-AI-SEO-with-planned-19B-Semrush-acquisition">bought SEMrush</a> to acquire more. <a href="https://www.techtarget.com/searchcustomerexperience/news/366641773/HubSpot-builds-answer-engine-optimization-into-its-platform">HubSpot,</a> among many others, added its own.</p> <p>Martech is at a crossroads, where users will have to decide whether to use a standalone AEO tool or go with embedded tools in platforms such as Sitecore. Sitecore chief marketing officer Michelle Boockoff-Bajdek said that existing Scrunch customers will be able to use it as a standalone, and also that Scrunch-driven features will eventually be integrated into Sitecore.</p> <p>Marketers will have to grapple with the question of AEO versus SEO: How to allocate finite marketing budgets to one or the other, as both will likely remain relevant for the foreseeable future. AEO -- because it puts value on earned recognition at sites like Reddit or review sites -- brings the notion of "earned media" back into marketing conversations after a decade or more of focus on the other two kinds of media, <a target="_blank" href="https://online.hbs.edu/blog/post/earned-vs-paid-media" rel="noopener">paid and owned</a>, said Liz Miller of Constellation Research.</p> <p>Marketers have preferred paid and owned media in recent years because marketing automation and analytics technologies readily measure and determine return on investment for those content categories -- and not so much for earned. But those technologies have also fragmented the work that public relations communications and marketing teams do, and they used separate tools to gauge their individual successes.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/LKmGM8zxKTY?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <p>Earned media is coming back into the picture because of how AI search values authority -- and authority is earned. PR and marketing teams will have to work together on unified technology platforms, Miller predicts, and Sitecore's Scrunch acquisition may help enable that kind of collaboration needed to fuel AI search success.</p> <p>"Earned becomes the wild card," Miller said. "It is a wild card that is really, really hard to control, to master and to monitor -- but it's going to be a requirement as we're looking at AEO and [<a href="https://www.techtarget.com/searchcontentmanagement/tip/How-to-integrate-GEO-with-an-SEO-strategy">generative AI optimization</a>]."</p> <section class="section main-article-chapter" data-menu-title="Human in the loop"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Human in the loop</h2> <p>Scrunch was cofounded in 2023 by Chris Andrew, who had spent 11 years at Hearsay, a social sales and marketing platform that was <a href="https://www.techtarget.com/searchcontentmanagement/tip/Software-tools-for-knowledge-sharing-and-collaboration">acquired by Yext.</a> Scrunch took on AI search optimization -- and monitoring -- on leading AI search platforms, including ChatGPT, Perplexity, Meta AI and others.</p> <p>Its flagship product is AXP (Agent Experience Platform), which tailors a website's experience for AI agents, and a host of other marketing analytics tools to monitor site traffic, map sites for AI agents, and compare a company's AI search performance with competitors.</p> <p>Boockoff-Bajdek, while not discussing Sitecore's specific product roadmap, imagines a future in which marketers log in to Sitecore each morning and see recommendations for new and recast content. The marketer, always remaining the human in the loop, approves the recommendations with the click of a button or addresses them in other ways.</p> <p>Scrunch, she continued, analyzes all of a user's content and can find authority-building documents in places humans might not have thought of, such as in sales enablement content, analyst materials, product documentation and other files that might not yet be customer-facing on the web. Building authority in AI search may not require new content in some cases but may involve merely exposing authoritative content you already possess to the AI search agents.</p> <p>Human marketers, however, will steer the changes and updates.</p> <p>"It shows you how the world, through AI, sees you; it shows you how the world really interprets you," Boockoff-Bajdek said. "We are outsourcing our browsing and research to these agents, but it's still a human who is looking for an answer. It is still a human who is deciding what to do with that information. So, as marketers, we have a responsibility to maintain the human element that is still critically important."</p> <p><i>Don Fluckinger is a seasoned B2B technology journalist with more than 30 years of experience, specializing in enterprise IT, digital experience and content management. As a senior news writer at Informa TechTarget he delivers award-winning analysis that helps IT and business leaders navigate complex technologies to enhance customer and employee experiences. Got a tip? </i><a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article"><i>Email him</i></a><i>.</i></p> </section> Sitecore becomes the latest customer experience/digital experience vendor to add more AEO to its platform. https://cdn.ttgtmedia.com/rms/onlineimages/ai_a373894778.jpg https://www.techtarget.com/searchcustomerexperience/news/366643973/Sitecore-acquires-Scrunch-for-answer-engine-optimization Thu, 04 Jun 2026 10:17:00 GMT <p>Autonomous service is not a new idea. Companies have long tried to automate customer-centric tasks to answer routine questions, route customers faster, provide 24/7 support, reduce repetitive work and lower service costs. Done well, that can make customer service more efficient. Done poorly, it can make customers feel trapped in a system that is fast, cheap and unhelpful.</p> <p>That tension is not new either. What is different now is the level of autonomy that AI agents and other automation tools are starting to promise.</p> <p>AI agents can answer more questions, automate more tasks and take more action without human involvement than earlier generations of customer service technology. In one example, Zendesk has previewed AI agents, copilots, no-code agent design tools, workflow builders, context tools and quality scoring for both AI and human agents as part of a <a href="https://www.techtarget.com/searchcustomerexperience/news/366643472/Zendesk-adds-AI-tools-in-pursuit-of-autonomous-service">broader push toward autonomous service</a>. The company's roadmap points toward a service model where AI does not just answer questions, but also supports account lookup, action-taking and workflow execution.</p> <p>That is where the human handoff becomes more important.</p> <p>The more AI moves from answering questions to taking action, the more important the human handoff becomes.</p> <section class="section main-article-chapter" data-menu-title="Autonomous service needs a stopping point"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Autonomous service needs a stopping point</h2> <p>The concept of autonomous service is useful up to a point.</p> <p>Many customer interactions are routine enough to automate. A customer wants to check an order, change an appointment, update a listing, get a basic answer, reset a password or find information that already exists in a knowledge base. These are the kinds of tasks where AI agents, chatbots, self-service tools and automated workflows can help.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The more AI moves from answering questions to taking action, the more important the human handoff becomes. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>But customer service rarely remains simple for long.</p> <p>A case can become emotional, account-specific, operationally messy, policy-heavy, relationship-sensitive or tied to a broader workflow. That is where automation needs to know when to stop.</p> <p>Furnished Finder's example shows how quickly this gets more complicated. Its AI assistant can start with basic Q&amp;A. From there, the company is looking at account lookup and then account action, such as updating a calendar for a specific rental listing. That is a real jump. Answering a question is one thing. Looking inside an account is another. Changing something for the customer is another thing entirely. Each step adds value. Each step also adds risk.</p> <p>The issue is not only that AI might get something wrong. Human agents get things wrong, too. The bigger issue is that AI needs to know when human judgment is required. That must be built into the workflows, use cases and escalation paths that shape how the AI behaves.</p> <p>Yes, AI should have some agency. But that agency should include knowing when, how and to whom to pass the torch.</p> <p>The handoff cannot be a dead end, either. The system should provide the human agent with enough context to identify the issue without requiring the customer to start over. That means the transcript, account history, actions already taken, reason for escalation, suggested next steps and any relevant risk or policy flags should move with the case.</p> <p>Otherwise, autonomous service becomes another version of a familiar customer service problem: The customer gets transferred, repeats everything and realizes no one actually owns the issue.</p> </section> <section class="section main-article-chapter" data-menu-title="Customer service is not only digital anymore"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Customer service is not only digital anymore</h2> <p>Just as customer service itself is messy, so is the way it is delivered.</p> <p>The handoff from AI to a human will not always be a clean one-to-one transfer. It also will not always be a simple move from chatbot to contact center agent. Service environments vary, and so does the level of expertise required to resolve an issue in a way that actually satisfies the customer.</p> <p>Sometimes, those interactions happen in physical spaces.</p> <p>In one example, <a target="_new" href="https://www.techtarget.com/searchcustomerexperience/feature/Avaya-CX-service-blends-AI-robots-and-human-interactions">Avaya and avatarin are using Avaya Infinity</a> to extend human expertise into physical service environments. In a Tokyo municipal office, a resident who speaks a language the onsite staff cannot speak can interact with a human-sized robot displaying the live face of a remote municipal worker. Avaya's CX platform is designed to orchestrate interactions among AI systems, remote human agents and physical robots in places such as airports, government offices and retail locations.</p> <p>That moves service beyond the contact center and beyond traditional voice and digital channels. It brings customer service into physical environments where staffing shortages, language barriers and limited onsite expertise can create real service gaps.</p> <p>The point is that autonomous service is not only about AI answering more questions. It is about connecting the customer to the right form of help. That requires customer context to move across systems in real time, so the customer does not have to repeat the same story during a handoff between AI, a remote human agent or someone working in a physical location.</p> <p>There is some irony in the human touch arriving through a robot's screen. But the important point is that the human handoff occurs when it needs to.</p> <p>Human involvement is not being treated as a failure of automation. It is part of the service model itself. AI can handle routine questions, translation and data gathering. Robots or digital interfaces can make remote help feel more present. But when the issue requires empathy, judgment or specialized knowledge, the service model still needs a person.</p> <p>That makes the handoff the connective tissue between AI, people, physical spaces and the systems behind the service interaction. It helps prevent a customer from repeating a story, restarting a process or figuring out which part of the organization owns the problem.</p> <p>The experience should feel seamless to the customer, whether the interaction moves from AI to a remote human, a robot, a physical world process or some combination of all three.</p> <p>Here, autonomous service starts to look less like fully independent service and more like coordinated service. The handoff is not where automation fails. It is where the rest of the service experience must begin.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/crm-contact_centers.jpg "> <img data-src="https://www.techtarget.com/rms/onlineImages/crm-contact_centers_mobile.jpg " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/crm-contact_centers_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/crm-contact_centers.jpg 1280w" alt="Graphic showing multidimensional contact centers with social media, mobile apps, video telephony, advanced analytics and generative AI." height="288" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>Autonomous service depends on more than AI agents. Customer service now spans multiple channels, data sources and support models, making clean human handoffs even more important. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Human roles must change, too"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Human roles must change, too</h2> <p>Autonomous service really means a need for more coordinated service. That includes handoffs among automated entities, such as AI agents and bots and humans across contact centers, digital channels, physical locations, remote service settings and other customer environments.</p> <p>That is already a major change from older customer service models. Traditional service relied more heavily on human agents, interactive voice response, self-service, knowledge bases and narrower chatbot assistance. The emerging model is different. Autonomous service is not just about AI answering more questions or replacing agents. It is about building a coordinated service model where AI, automation, humans, workflows and sometimes physical spaces all know when to act, when to stop and how to pass context along.</p> <p>But that does not mean the roles of real people stay the same. They can't.</p> <p>There are too many things AI can now do autonomously -- including processing data, recognizing patterns, routing work, summarizing interactions, retrieving knowledge, detecting intent, translating language and gathering account information -- for humans to keep playing the same role they always have.</p> <p>That does not make people less important. In some ways, it makes human work more important.</p> <p>As <a target="_new" href="https://www.techtarget.com/searchcustomerexperience/tip/AI-creating-new-contact-center-jobs-for-agents">AI creates new contact center roles</a>, the remaining human work is more likely to involve judgment, empathy, orchestration, training, specialization or behind-the-scenes support for AI-driven service. Humans may need to interpret AI output, manage several AI inputs, handle a high-emotion customer, apply policy judgment, correct the service path or feed what they learn back into the system.</p> <p>That is where autonomous service and human service must work together. AI can take on more of the scalable work. It can process data, spot patterns, route work, summarize interactions and pull answers from knowledge systems. But people still must handle the moments where ambiguity, relationship risk, empathy, reasoning or accountability matter.</p> <p>Businesses worried about falling behind in AI should also worry about falling behind in the human role in customer service. If companies want more autonomous service, they need to be just as deliberate about the people around it.</p> <p>Human involvement is not a failure of automation. In an AI-heavy contact center, people might become orchestrators, specialists, trainers, designers, analysts or some mix of those roles. Some of that work is customer-facing. Some of it happens behind the scenes. But both sides matter because autonomous service still needs people who can handle ambiguity, improve the system and own the outcome.</p> <p>The human role, in the simplest terms, is becoming the relationship and judgment layer inside automated service systems. That can include the traditional agent role, but it can also include orchestrator, specialist, owner, trainer, designer, analyst or some mix of all of those.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading"></h3> <h3 class="splash-heading">Human roles in autonomous service</h3> <p>Autonomous service does not eliminate human work. It changes where human judgment, empathy and expertise show up.</p> <p>Some of the emerging roles include:</p> <p><b>CX orchestrator.</b> Coordinates AI inputs, customer data and workflow steps so the customer is guided through the right service path.</p> <p><b>Customer success facilitator.</b> Uses customer data, sentiment signals and service history to resolve issues while protecting the broader customer relationship.</p> <p><b>CX specialist.</b> Handles complex, ambiguous or domain-specific cases that require expertise beyond what an AI agent can provide.</p> <p><b>Conversational AI designer.</b> Shapes bot conversations, call flows and language so automated service sounds natural, useful and consistent with the brand.</p> <p><b>AI agent trainer.</b>&nbsp;Reviews accuracy, tone, bias, empathy and escalation behavior so AI agents improve over time.</p> <p><b>CX data analyst.</b>&nbsp;Interprets AI-generated customer data, finds patterns in service issues and helps the business act on what the contact center learns.</p> <p>The common thread is ownership. As AI takes on more routine work, human roles shift toward the parts of service that require judgment, context and accountability.</p> </div> </div> <p>Automation may take on more of the grunt work. But that raises the level at which many customer service specialists need to perform. A weak handoff does not become strong just because a human is technically available. The human needs the right context, authority, training and role definition to take over.</p> <p>The human handoff only works if there is a human role ready to receive it.</p> </section> <section class="section main-article-chapter" data-menu-title="The handoff must move the context"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The handoff must move the context</h2> <p>A human handoff is not just a transfer.</p> <p>If the customer moves but the context does not, the handoff has already failed. The person receiving the case needs to know what the customer asked, what the AI answered, what actions were taken, what data was used, what the customer is trying to accomplish and why the case escalated.</p> <p>That matters because the remaining human work is often the hardest work.</p> <p>The easy interaction might never reach a person. The customer who reaches a human agent may be angry, confused, anxious, stuck in a policy exception or dealing with a problem that spans billing, operations, fulfillment, product, account management or another part of the business.</p> <p>That agent should not have to reconstruct the case from scratch. The customer should not have to serve as the integration layer between the AI tool and the company.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading"></h3> <h3 class="splash-heading">What should move with the human handoff</h3> <p>A customer handoff should move more than the customer. It should move enough context for the next person or team to own the issue.</p> <p>That can include:</p> <ul class="default-list"> <li>Transcript or interaction summary.</li> <li>Customer and account history.</li> <li>Actions the AI already took.</li> <li>Reason for escalation.</li> <li>Customer intent, urgency and sentiment.</li> <li>Relevant policy, risk or compliance flags.</li> <li>Data or systems the AI used.</li> <li>Suggested next step.</li> <li>Clear owner for the next action.</li> </ul> <p>Without that context, a handoff can make the customer start over. With it, the human handoff becomes part of the service experience instead of a sign that automation failed.</p> </div> </div> <p>A good handoff should move the case with enough information for the person to own the next step. It should also make clear whether the person is taking over the customer interaction, reviewing an AI-suggested action, correcting a workflow, applying judgment or sending feedback back into the service system.</p> <p>That is where autonomous service can become more than deflection. It can become a better service model, but only if autonomy and human ownership are designed together.</p> </section> <section class="section main-article-chapter" data-menu-title="Coordinated service is the real goal"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Coordinated service is the real goal</h2> <p>Autonomous service sounds like the customer never has to leave the machine. That is not the best goal.</p> <p>The better goal is coordinated service. AI should handle what it can handle well. Automation should move routine work faster. Robots or remote interfaces can extend human help into places where expertise is not physically present. Humans should step in when the issue requires judgment, empathy, specialized knowledge, accountability or relationship care.</p> <p>That is a more realistic promise than full autonomy. It also makes the human handoff central to the system rather than an exception.</p> <p>Autonomous service will not be judged only by how many cases AI resolves. It will also be judged by what happens when AI reaches the limits of its capabilities.</p> <p>The best systems will not just automate the front door. They will know where the customer goes next.</p> <p><i>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</i></p> </section> AI agents, robots and automation can handle more service work, but customer service still needs human judgment, clean handoffs and coordinated ownership. https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Artificial_intelligence_AI.jpg https://www.techtarget.com/searchcustomerexperience/feature/Autonomous-service-still-needs-a-human-handoff Wed, 03 Jun 2026 14:00:00 GMT <p>E-commerce now drives more B2B revenue than the in-person channels that defined the category for decades. According to industry reports, e-commerce is a top revenue channel for organizations that offer it, and more than half of large B2B transactions, $1 million or greater, are processed through digital self-serve channels.</p> <p>That shift puts platform selection at the forefront of organizational priorities. The timing is also urgent, as SAP <a target="_blank" href="https://help.sap.com/docs/SAP_COMMERCE/980b87d07d0d40fcb0493dfb3384f854/aa4d455501b04818ae7efcff861b5a76.html" rel="noopener">ends mainstream maintenance</a> for on-premises SAP Commerce next month, forcing one of the largest enterprise re-platforming events in years. Choosing the right B2B e-commerce platform now sets the trajectory for revenue, integration debt and customer experience.</p> <section class="section main-article-chapter" data-menu-title="What is a B2B e-commerce platform?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is a B2B e-commerce platform?</h2> <p>A B2B e-commerce platform is the software stack that powers digital sales between businesses, handling product catalogs, account-specific pricing, order entry, payment terms, fulfillment hooks and the buyer self-service portal. Unlike consumer commerce, B2B platforms must accommodate multi-tier account hierarchies, customer-specific contract pricing, request-for-quote (RFQ) flows, credit limits, purchase approvals and procurement system integrations.</p> <p>The B2B e-commerce platform market features several vendors:</p> <ul class="default-list"> <li><b>Adobe Commerce</b> -- a longstanding enterprise option with deep B2B feature parity.</li> <li><b>BigCommerce B2B Edition</b> -- a Gartner Magic Quadrant Challenger six years running, with strong mid-market adoption.</li> <li><b>commercetools</b> -- API-first and <a target="_blank" href="https://www.youtube.com/watch?v=2aqbslr3PtQ" rel="noopener">composable</a>, named a Gartner Leader for six straight years.</li> <li><b>OroCommerce</b> -- purpose-built for B2B workflows, five years in the Gartner Magic Quadrant.</li> <li><b>Salesforce Agentforce Commerce</b> -- consistently deemed a leader in industry reports.</li> <li><b>SAP Commerce Cloud</b> -- recognized in Gartner's Magic Quadrant for 11 consecutive years.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Scalability matters more than feature count"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Scalability matters more than feature count</h2> <p>Scalability is the architectural decision that compounds over time. Monolithic platforms accumulate integration debt as catalog, customer base and channel count expand.<a href="https://www.techtarget.com/searchcustomerexperience/definition/headless-commerce-headless-e-commerce"> </a><a href="https://www.techtarget.com/searchcustomerexperience/definition/headless-commerce-headless-e-commerce">Headless commerce</a> and composable commerce architectures decouple the storefront from back-end commerce logic, letting each component scale and evolve independently.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The question for enterprise buyers is whether the platform supports composability today. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>The performance data backs the shift. Companies excelling at omnichannel sales, typically supported by composable digital ecosystems, capture up to 70% higher market share growth than their peers, according to McKinsey <a target="_blank" href="https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/five-fundamental-truths-how-b2b-winners-keep-growing" rel="noopener">research</a>.</p> <p>The practical question for enterprise buyers is whether the platform supports composability today, through documented APIs and modular extensibility, or whether scaling will require a significant upgrade in three to five years.</p> </section> <section class="section main-article-chapter" data-menu-title="Essential features to evaluate"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Essential features to evaluate</h2> <p>A serviceable B2B platform handles how businesses actually buy. The non-negotiable platform features include the following:</p> <ul class="default-list"> <li><b>Account hierarchies and role-based access</b> -- parent-child account structures with permissions that mirror the buyer's organization.</li> <li><b>Contract and tier pricing</b> -- account-specific price lists, volume discounts and customer-segment pricing rules.</li> <li><b>Quote-to-cash workflows</b> -- RFQ handling that converts to a purchase order without manual re-keying.</li> <li><b>Credit limits and payment terms</b> -- net-30/60/90 terms, pay-on-account and credit ceiling enforcement.</li> <li><b>Punchout catalogs</b> -- direct integration with buyer procurement systems such as Coupa, SAP Ariba and Jaggaer.</li> <li><b>Approval workflows</b> -- configurable rules that route orders for sign-off based on deal size, product mix or buyer role.</li> <li><b>Bulk and reorder tools</b> -- CSV upload, saved order templates and one-click reorder from order history.</li> </ul> <p>Newer checklist additions include AI-assisted reorder recommendations and agent-commerce APIs that expose pricing and inventory to autonomous purchasing agents. The native feature catalog matters less than whether the platform can support these patterns without heavy customization.</p> </section> <section class="section main-article-chapter" data-menu-title="ERP and CRM integration"> <h2 class="section-title"><i class="icon" data-icon="1"></i>ERP and CRM integration</h2> <p>B2B sellers consistently rank <a href="https://www.techtarget.com/searcherp/tip/Learn-benefits-and-challenges-of-CRM-and-ERP-integration">ERP and CRM integration</a> as their top operational challenge. The reason is structural: Master data, product information, customer accounts, inventory levels and pricing rules live in the ERP, while customer history and service interactions live in the CRM. A platform that cannot synchronize bidirectionally with both creates duplicate data, inconsistent pricing and stockouts.</p> <p>The integration payoff is significant. Companies running integrated commerce-ERP stacks see meaningful sales lifts and overall reductions in order error rates. The right question is not whether a platform offers ERP connectors but how those connectors handle real-time sync, exception handling and the schema drift that follows any ERP upgrade.</p> </section> <section class="section main-article-chapter" data-menu-title="Cost considerations"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Cost considerations</h2> <p>License fees are the smallest part of the total cost of ownership. Industry implementation data puts a light SaaS portal at $20,000 to $80,000 in year one, a mid-market deployment at $80,000 to $300,000, and an enterprise build at $300,000 to $1 million-plus. A fully composable custom build can run between $500,000 and $2 million-plus.</p> <p>The spread of costs is driven by integration complexity, catalog data quality, customization depth and operational support. Commerce migrations typically run in multiple phases and require process redesign to control cost, meaning the platform decision is also a business-process decision.</p> </section> <section class="section main-article-chapter" data-menu-title="User experience and customer engagement"> <h2 class="section-title"><i class="icon" data-icon="1"></i>User experience and customer engagement</h2> <p>The buy-side has voted on what good looks like. A recent Gartner <a target="_blank" href="https://www.gartner.com/en/newsroom/press-releases/2026-03-09-gartner-sales-survey-finds-67-percent-of-b2b-buyers-prefer-a-rep-free-experience" rel="noopener">sales survey</a> found that 67% of B2B buyers prefer a rep-free buying experience. McKinsey reports that 54% of decision-makers will abandon or switch suppliers after a poor omnichannel customer experience.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> 67% of B2B buyers prefer a rep-free buying experience. </figure> <figcaption> <strong>Gartner sales survey</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>That makes self-service depth and interface quality direct revenue inputs, not soft factors. Buyers expect product configurators, real-time inventory, transparent pricing, order tracking and persistent saved carts, features that many B2B platforms still bolt on rather than build in.</p> <p>A caveat on personalization, though, as Digital Commerce 360 <a target="_blank" href="https://www.digitalcommerce360.com/2025/06/05/personalization-can-damage-b2b-customer-loyalty-sales/" rel="noopener">reported</a> that 53% of B2B buyers felt personalization hurt their most recent purchase journey, with irrelevant suggestions correlating with purchase regret. Personalization belongs on the roadmap, but only behind clean fundamentals.</p> </section> <section class="section main-article-chapter" data-menu-title="A checklist for choosing a B2B e-commerce platform"> <h2 class="section-title"><i class="icon" data-icon="1"></i>A checklist for choosing a B2B e-commerce platform</h2> <p>When evaluating B2B e-commerce platforms, decision-makers should work through six tests:</p> <ol type="1" start="1" class="default-list"> <li><b>Map the architecture.</b> Does the platform support composable extension, or will scale force a re-platform?</li> <li><b>Test the integration story.</b> Request real ERP and CRM connector demos using the buyer's actual data, not vendor sample sets.</li> <li><b>Audit B2B feature depth.</b> Confirm account hierarchies, contract pricing, RFQ, punchout and approvals are native, not customized add-ons.</li> <li><b>Model three-year TCO.</b> Include license, implementation, integration, customization and operational support -- not just the subscription line.</li> <li><b>Validate buyer-experience flows.</b> Run live tests with actual customers, not feature checklists.</li> <li><b>Confirm analyst position and roadmap.</b> Cross-reference current Gartner and Forrester assessments and ask vendors to defend their position.</li> </ol> <p>The platforms that win scale with the business, integrate cleanly with what is already running and let buyers transact without picking up the phone. Selection is no longer a procurement exercise -- it's a growth decision.</p> <p><i>Griffin LaFleur is a RevOps and GTM Engineering leader at Granite GTM, where he works with B2B technology companies on go-to-market strategy, systems architecture and revenue operations.</i></p> </section> When choosing a B2B e-commerce platform, businesses should prioritize scalability and composability, evaluate native features and consider cost and integration challenges. https://cdn.ttgtmedia.com/rms/onlineimages/maze_g1194975109.jpg https://www.techtarget.com/searchcustomerexperience/tip/How-to-choose-a-B2B-e-commerce-platform Wed, 03 Jun 2026 11:07:00 GMT <p>In 2024, the size of the <a href="https://www.marketresearchfuture.com/reports/customer-experience-analytics-market-3119" target="_blank" rel="noopener">market for experience analytics software</a> was estimated at $12.6 billion. The market grew to $14.43 billion in 2025. It is projected to grow even further to $55.99 billion, at a compound annual growth rate (CAGR) of 14.52%, between 2025 and 2035.</p> <p>Experience analytics platforms are rich with customer data, so it's not surprising that enterprises are investing heavily in them. These systems capture information about customer behaviors and sentiments to help cross-functional teams like sales, marketing and customer support to better understand customers' needs and pain points. These customer-facing teams can then proactively implement data-driven changes to enhance customer experience (<a href="https://www.techtarget.com/searchcustomerexperience/definition/customer-experience-CX">CX</a>). In doing so, they can enhance <a href="https://www.techtarget.com/searchcustomerexperience/answer/Why-are-loyalty-programs-important">customer loyalty</a> and <a href="https://www.techtarget.com/searchcustomerexperience/tip/10-customer-success-KPIs-and-metrics-to-track">customer lifetime value</a> (CLV), reduce <a href="https://www.techtarget.com/searchcustomerexperience/definition/churn-rate">customer churn</a> and boost profitability.</p> <p>That said, experience data alone is insufficient for companies to understand what's actually wrong CX-wise or what they need to fix first. Considering these insights in isolation rather than within the context of service, support, logistics and onboarding workflows can cause tunnel vision, resulting in firms misdiagnosing the root causes of customer behavior and optimizing the wrong aspects of CX.</p> <section class="section main-article-chapter" data-menu-title="The missing context -- and why it can be problematic"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The missing context -- and why it can be problematic</h2> <p>CX analytics unpacks the story behind every customer's experience. However, this story is often incomplete because traditional experience analytics platforms fail to consider three crucial types of business context:</p> <ul class="default-list"> <li><b>Operational. </b>This includes aspects like service delivery times, logistics performance, product quality, checkout times and product messaging.</li> <li><b>Cultural.</b> This refers to regional or demographic differences in customer expectations, values, beliefs, behaviors and preferred communication styles.</li> <li><b>Workflow.</b> This encompasses internal processes like customer onboarding, account management, issue resolution and returns handling.</li> </ul> <p>Ignoring contextual cues can be problematic. The following examples illustrate why.</p> <h3>Example 1: Retail</h3> <p>A retail company analyzes customer journey data to optimize website navigation, eliminate checkout friction and deliver hyper-personalized shopping experiences. These aspects <i>can</i> help to enhance CX. However, CX does not depend on these aspects alone. Many other factors can also drive CX quality, including shipping timelines, product quality, pricing, return policies and support resolution timelines.</p> <p>When pursuing CX optimization, the firm must consider <i>all</i> these factors, rather than depending on insights derived from experience analytics alone. If teams ignore these factors and rely solely on customer journey data, they might, for example, waste limited enterprise resources on website navigation improvements instead of addressing shipping delays. Instead of making <i>meaningful</i> CX improvements, these actions might fail to address the main source of customer frustration, invite negative publicity and weaken the company's competitive posture.</p> <h3>Example 2: SaaS provider</h3> <p>A SaaS provider performs sentiment analysis with an experience analytics platform. The goal: improve customer onboarding and help customers achieve their business goals with the SaaS product. While its teams invest resources in the improvement of onboarding emails, they ignore workflow bottlenecks that typically hinder product setup and cause frequent downtime. By misplacing its resources, the SaaS provider might make little to no progress in restoring customer trust or decreasing customer churn -- and potentially erode its customer base as negative reviews mount.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/customer_experience_maps_vs_customer_journey_maps-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/customer_experience_maps_vs_customer_journey_maps-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/customer_experience_maps_vs_customer_journey_maps-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/customer_experience_maps_vs_customer_journey_maps-f.png 1280w" alt="Diagram comparing customer experience and customer journey maps" height="400" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>Customer journey maps capture more than just sentiment, but they can still lack important operational, cultural and workflow context that explain customer behavior. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Benefits of integrating experience analytics with enterprise systems"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of integrating experience analytics with enterprise systems</h2> <p>Companies <i>can</i> close the gap between experience analytics and contextual factors to meet customer expectations and improve CX. The key is to integrate experience analytics with operational systems, including ERP, <a href="https://www.techtarget.com/whatis/video/An-explanation-of-customer-relationship-management-CRM">CRM</a>, <a href="https://www.techtarget.com/searchitoperations/definition/ITSM">IT service management</a>, workflow automation and data warehouses.</p> <p>Integrating experience analytics with other platforms can help provide a holistic view of customer journeys and spotlight the operational, cultural or workflow-related issues that might be negatively affecting those journeys. It ensures that all customer-facing teams view a single, all-encompassing analysis. This could minimize costly errors and redundancies; enhance the speed, accuracy and consistency of business planning and decision-making; and enable proactive issue resolution. Ultimately, well-planned, thoughtfully designed integrations help transform businesses into successful, customer-centric organizations.</p> <p>Needless to say, cross-functional collaboration between CX leaders, software teams and operational managers is critical to ensure seamless integration between CX platforms and other business systems. Close coordination between these stakeholders ensures alignment between technical rollouts and actual business needs. It also helps to streamline workflows, foster buy-in and adoption, and accelerate time to value for the integrated ecosystem.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/cust_ex-customer_journey_map-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/cust_ex-customer_journey_map-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/cust_ex-customer_journey_map-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/cust_ex-customer_journey_map-f.png 1280w" alt="Table illustrating stages of the customer journey map" height="516" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>To create an all-encompassing analysis of customer behavior, data from customer journey maps, like the example presented here, should be integrated with other business systems, including ERP and workflow automation platforms. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Real lessons from the field"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Real lessons from the field</h2> <p>Several real companies have successfully aligned experience analytics with operational context to enhance CX and customer satisfaction.</p> <h3>Delta Air Lines</h3> <p>One example is Delta Air Lines' award-winning Connected Onboard Platform (<a href="https://news.delta.com/deltas-connected-onboard-platform-recognized-best-industry" target="_blank" rel="noopener">CoP</a>). By connecting operational, connectivity and CX data, this multinational airline managed to deliver seamless, connected onboard experiences to flyers. Glenn Latta, Delta's managing director of in-flight entertainment and connectivity, believes that combining experience analytics with other kinds of business data is critical to breaking down silos across CX teams and enabling smarter service delivery across the organization. "This achievement is a testament to the engineers, operators and partners who made CoP possible, breaking down silos across the customer and employee experience to design something truly one-of-a-kind that fits the needs of our business."</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Combining experience analytics with other kinds of business data is critical to breaking down silos across CX teams and enabling smarter service delivery across the organization. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <h3>University of Chicago Medicine</h3> <p>Like Delta, University of Chicago Medicine also uses contextual analytics to minimize workflow inefficiencies. This healthcare provider has <a href="https://www.salesforce.com/customer-stories/uchicago-medicine-andrew-chang-byline/" target="_blank" rel="noopener">deployed</a> Salesforce's customer analytics platform to automate and streamline multiple patient-facing processes, including appointment scheduling and FAQ assistance.</p> <p>Andrew Chang, the organization's chief marketing officer, believes it's not lack of information but rather lack of <i>integration</i> that is responsible for antiquated customer experiences in the healthcare sector. Chang also believes that collecting "every touchpoint and behavioral signal, and then making them actionable," is the key to personalizing customer journeys and enhancing patient experiences.</p> <h3>UPS</h3> <p>Multinational shipping company UPS uses journey and delivery data, such as missed delivery patterns and support interactions, alongside operational metrics like route efficiency and on-time delivery rates. This enables the company to reroute deliveries as needed and improve delivery transparency, which then reduces failed deliveries and helps optimize delivery experiences for customers.</p> <h3>Takeaways</h3> <p>These real-world examples present several useful lessons for companies that have not yet integrated experience analytics with operational context:</p> <ul class="default-list"> <li>Use analytics to identify root causes of issues, not just surface-level trends.</li> <li>Use <i>real-time</i> insights to proactively resolve issues before they escalate.</li> <li>Focus on journey-level analytics instead of isolated touchpoints to identify and address cumulative friction throughout the customer journey.</li> <li>Invest in data integration and interoperability between CX platforms and enterprise systems to unify customer and operational data into a single view.</li> <li>Create a unified data environment to facilitate cross-functional collaboration and decision-making between all customer-facing teams.</li> <li>Tie customer interactions to operational events to facilitate faster root-cause analyses and more accurate decision-making.</li> <li>Use AI to analyze data faster and augment human decision-making -- while maintaining human oversight to eliminate bias, discrimination and <a href="https://www.techtarget.com/searchenterpriseai/tip/Why-does-AI-hallucinate-and-can-we-prevent-it">hallucinations</a>.</li> <li>Tie CX metrics directly to measurable operational and financial <a href="https://www.techtarget.com/searchbusinessanalytics/definition/key-performance-indicators-KPIs">KPIs</a>, such as customer retention and CLV, to justify investments in experience analytics and drive meaningful business improvements.</li> <li>Foster a culture of collaboration between CX, IT and operations teams to ensure shared visibility into customer journeys and to prevent fragmented decision-making.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/follow_these_best_practices_for_customer_journey_mapping-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/follow_these_best_practices_for_customer_journey_mapping-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/follow_these_best_practices_for_customer_journey_mapping-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/follow_these_best_practices_for_customer_journey_mapping-f.png 1280w" alt="List of customer journey mapping best practices" height="262" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Cross-team collaboration and periodic review and updating of customer journey data can help companies unlock new insights for improving customer engagement. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="The evolving landscape of experience analytics"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The evolving landscape of experience analytics</h2> <p>Many leading CX platforms are evolving beyond traditional customer feedback and journey analytics to incorporate operational and workflow data.</p> <p>One example is Salesforce's Agentforce Contact Center, an AI-first customer service <a href="https://www.salesforce.com/news/stories/agentforce-contact-center-announcement/" target="_blank" rel="noopener">platform</a> for tracking and streamlining customer interactions. Rooted in organizational data, this unified system combines CRM, digital channels, voice and AI to help firms deliver intelligent, integrated services and meet customer demands across every business touchpoint.</p> <p>Like Salesforce, several other experience analytics systems now integrate with operational systems, workflow orchestration and other platforms. These include the following:</p> <ul class="default-list"> <li>Adobe CX Enterprise.</li> <li>Contentsquare Experience Analytics.</li> <li>Crescendo.ai.</li> <li>Qualtrics Digital Experience Analytics (DXA).</li> <li>Qualtrics XM.</li> <li>Quantum Metric.</li> </ul> <p>Integrated platforms enable organizations to act on both customer and operational signals in real time, and tie CX improvements to measurable business impact.</p> <p>Some experience platforms are also adding AI capabilities. <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-agents">Agentic AI</a> technology connects data about customer behaviors with the operational, cultural and workflow context in which those experiences occur. It also generates contextual insights that help customer-facing teams to proactively interpret customer sentiment, analyze customer journeys and predict potential customer friction. Teams can also access real-time recommendations within agentic AI experience analytics systems to prioritize and remediate incidents, as well as deliver personalized experiences at scale.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/lqaO53DJsYk?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Context is key to successful enterprise CX"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Context is key to successful enterprise CX</h2> <p>Experience analytics is a powerful way to analyze customer behaviors and optimize customer journeys. But as we have seen, analytics without detailed and up-to-date operational, cultural and workflow context can lead organizations astray. To anticipate, understand and meet evolving customer needs, companies need to treat experience analytics as a holistic matter that requires seamless integration with business platforms as well as cross-functional collaboration across teams.</p> <p><i>Rahul Awati is a PMP-certified project manager with IT infrastructure experience spanning storage, compute and enterprise networking.</i></p> </section> Experience analytics can show behavior, journeys and sentiment, but without operational, cultural, service and workflow context, organizations risk optimizing the wrong things. https://cdn.ttgtmedia.com/rms/onlineimages/maze_g1333061126.jpg https://www.techtarget.com/searchcustomerexperience/feature/Context-is-key-The-limits-of-experience-analytics-software Thu, 28 May 2026 11:30:00 GMT <p>The SAP Sapphire conference was held in Orlando, Fla., on May 11-13.</p> <p>The event centered on topics including Joule, SAP's generative AI copilot, and other AI subjects, including SAP products like Business Data Cloud and Business Technology Platform. Developments such as multi-agent orchestration and agentic AI remain the dominant topics in the tech world.</p> <p>As in past years, the longstanding effort to move customers from SAP ECC to S/4HANA and the 2027 end of support for ECC remained major topics. The conference also included discussion about SAP’s engagement offerings as the company has worked to integrate its engagement technology with other enterprise tools.</p> <p>IT decision-makers can check back here for the latest on SAP announcements and other developments since the conference concluded.</p> Here are the newest developments from SAP Sapphire in Orlando, Fla., with the enterprise software vendor's 2026 announcements and our writers' takes on the news. https://www.techtarget.com/searchsap/conference/SAP-Sapphire-Now-news-trends-and-analysis Thu, 28 May 2026 09:00:00 GMT <p>Every day, businesses leave critical customer insights buried inside support tickets, live chats and phone transcripts. This sinkhole exists because organizations have long relied on post-interaction surveys to capture customer sentiment. These surveys have a key flaw: They lack adequate responses from all customers except from the most delighted or deeply frustrated outliers. Despite this deficiency, the post-interaction survey remains the go-to mechanism for gathering customer sentiment for most companies, according to Metrigy research.</p> <p>However, forward-thinking contact center operations are tapping into the power of AI inferred sentiment analysis to get themselves out of the mire. Today, inferred sentiment analysis uses <a href="https://www.techtarget.com/whatis/definition/large-language-model-LLM">large language models</a> and context-aware processing to discern emotional tone of customer interactions. Essentially, inferred sentiment delivers a customer sentiment score for every touchpoint without requiring the customer to fill out a single survey.</p> <p>Since Metrigy began tracking inferred sentiment in early 2023, we've seen a big bump in use, from 15% to 45% in early 2025. But the real story is in the reported improvements in core operational metrics from its use.</p> <section class="section main-article-chapter" data-menu-title="The benefits of inferred sentiment analysis"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The benefits of inferred sentiment analysis</h2> <p>Metrigy's "AI for Business Success: 2025-26" global research study of 1,104 companies underscores how inferred sentiment acts as a force multiplier for CX success, delivering substantial improvements in employee efficiency, costs and revenue.</p> <ul class="default-list"> <li>Inferred sentiment ranks as the single-most-effective CX tool for driving down expenses, generating an average 22% decrease in operational costs.</li> <li>Automating customer sentiment analysis offloads manual categorization and highlights crucial issues, resulting in a 31.7% surge in employee efficiency.</li> <li>By capturing friction points and uncovering clear buying signals in real time, businesses experience a 26.7% boost in revenue.&nbsp;</li> </ul> <p>Increasingly, inferred sentiment analysis doesn't stand alone. Rather, it's seen as one piece of the intelligence layer for CX, intertwined with <a href="https://www.techtarget.com/searchcustomerexperience/tip/Employee-conversational-analytics-unlocks-business-insights">conversational intelligence</a> and <a href="https://www.techtarget.com/searchcustomerexperience/tip/Customer-interaction-analytics-spurs-better-business-results">interaction analytics</a>.</p> <p>Conversational intelligence drills down into the behavioral nuances of distinct voice or video calls, such as evaluating talk-to-listen ratios. Interaction analytics aggregates macro-level data across text and speech channels to pinpoint broad operational trends. Inferred sentiment bridges these two tools, running in the background and translating qualitative conversations into hard, quantifiable data points.</p> </section> <section class="section main-article-chapter" data-menu-title="How does inferred sentiment analysis work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does inferred sentiment analysis work?</h2> <p>In action, the tech looks like this: Inferred sentiment analysis turns human chatter into sentiment scores, fed into an interaction analytics dashboard. Interaction analytics constantly monitors those scores. Upon spotting a spike in negative sentiment scores linked to, say, a specific billing phrase, like "unauthorized charge," it coordinates with <a href="https://www.techtarget.com/searcherp/tip/Learn-benefits-and-challenges-of-CRM-and-ERP-integration">CRM and ERP systems</a> to flag customer accounts, update billing routing rules or dynamically inject contextual warning questions into post-interaction surveys. For example, the question might be: "Based on the billing issue you discussed with our team today, how likely are you to explore alternative providers if this charge is not fully reversed?"</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> AI-enabled inferred sentiment analysis can unearth valuable insights that propel business improvements. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Additionally, contact center operations that shift to AI-enabled, automated sentiment evaluation can free up time that was lost to manual quality assurance. Successful contact center operations prioritize this extra time strategically. <a target="_blank" href="https://www.customerexperiencedive.com/news/despite-the-hype-ai-is-not-replacing-the-customer-service-workforce/818327/" rel="noopener">Rather than scaling down head count</a>, successful companies put these saved hours back into the business, Metrigy has found. Some examples include:</p> <ul class="default-list"> <li>Customer service teams use their freed capacity to query conversational data using natural language, drilling down into the precise root causes of client friction.</li> <li>Supervisors use automatically generated empathy and tone metrics to provide rapid, data-backed guidance to contact center agents.</li> <li>Organizations trigger immediate, <a href="https://www.techtarget.com/searchcustomerexperience/tip/Proactive-customer-service-drives-satisfaction-and-revenue">proactive outreach</a> to resolve emerging billing or technical failures before a customer chooses to churn.</li> </ul> <p>Post-interaction and other customer survey types remain important tools, but in this age of AI, they're not the end of the road -- nor should they be. Relying exclusively on active feedback leaves companies with too muddied a view of their customers' sentiment. By deploying AI-enabled inferred sentiment analysis as part of the CX intelligence layer, they can unearth the valuable insights that propel business improvements.<i>&nbsp;</i></p> <p><i>Beth Schultz is vice president of research and principal analyst at Metrigy. She focuses her research on unified communications, collaboration and digital customer experience.</i></p> </section> Automated customer sentiment evaluations can help organizations understand their customers better, replace manual tasks and boost revenue by uncovering buying signals. https://cdn.ttgtmedia.com/rms/onlineimages/customer_service14.jpg https://www.techtarget.com/searchcustomerexperience/tip/How-AI-inferred-sentiment-analysis-unlocks-customer-insights Wed, 27 May 2026 14:24:00 GMT <p>In 2026, Dell continues to position itself as the backbone infrastructure provider for enterprise AI and hybrid cloud.</p> <p>The central theme at Dell Technologies World 2026 was clear: enterprise AI is moving from <a href="https://www.techtarget.com/searchcio/feature/The-AI-plateau-What-smart-CIOs-will-do-when-the-hype-cools">experimentation to production</a>, with organizations increasingly seeking to run AI closer to where enterprise data already lives through hybrid, governed infrastructure.</p> <p>"CIOs are aggressively pivoting to hybrid AI," said Dell founder Michael Dell during Monday's keynote. "The risk is not the cloud -- the risk is losing control of your data, your cost, your security, your intellectual property and your speed."</p> <p>Dell also announced an <a href="https://www.techtarget.com/searchstorage/opinion/Turning-Data-into-Intelligence-for-the-AI-Native-Era">expansion of its AI Factory strategy</a>, positioning it as a framework for helping enterprises deploy and run frontier models in on-premises and hybrid environments. The company emphasized this approach as a way to improve control over data governance, model choice and long-term <a href="https://www.techtarget.com/searchcio/feature/Tokenmaxxing-How-CIOs-extract-maximum-value-AI-tokens">cost management tied to large-scale AI deployments</a>.</p> <p>Across sessions, speakers framed those infrastructure investments as foundational to delivering more proactive, contextual and <a href="https://www.techtarget.com/searchcustomerexperience/news/366629754/AI-agents-evolve-how-automated-customer-service-works">automated customer experiences</a>. However, as discussions shifted from infrastructure to customer-facing outcomes, such as personalization and service automation, a recurring theme emerged across multiple sessions and interviews: data readiness remains a bigger barrier to AI personalization than the technology itself.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Everything you need to make a good decision is scattered across different systems in completely different formats. </figure> <figcaption> <strong>Faizel Khan</strong>Lead AI engineer, Landing Point </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>"The biggest challenge is the data underneath it," said Faizel Khan, lead AI engineer at Landing Point recruiting firm, in an interview with TechTarget. "And it's not even a quality problem. It's that everything you need to make a good decision is scattered across different systems in completely different formats."</p> <section class="section main-article-chapter" data-menu-title="Why AI personalization breaks down in practice"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why AI personalization breaks down in practice</h2> <p>In a session titled "AI-powered personalization: The customization of the customer experience," panelists brought the infrastructure conversation down to the practical reality of how enterprises are trying to operationalize personalization at scale.</p> <p>Across the discussion, speakers described a clear shift in customer expectations: users increasingly expect brands to recognize them as individuals, with context carried across every interaction, rather than treating each engagement as a standalone request. That expectation is colliding with how most enterprises are still structured -- in fragmented systems, siloed teams and sequential workflows that slow down decision-making.</p> <p>"We're still structured very much in silos, and if individual business units are solving just a portion of the customer journey, you end up with a fragmented experience," said Marybeth Pearce, vice president of global enterprise sales at Comcast Business, in the session.</p> <p>Panelists gave several examples of how personalization breaks down in practice. For instance, companies may have the data to understand customer behavior, but that information is often distributed across CRM systems, ticketing tools and internal knowledge bases that don't easily connect in real time. The result is delayed or inconsistent experiences that undermine the very <a href="https://www.techtarget.com/searchcio/feature/Safe-by-design-AI-personalization-in-fintech">personalization efforts</a> enterprises are trying to offer.</p> <p>The panel also repeatedly returned to a key tension: personalization is no longer just about content or targeting, but about operational speed and coordination across the organization. When insights take weeks to move from data to execution, the opportunity for real-time personalization disappears.</p> <p>"The organizations achieving the strongest outcomes are treating AI personalization as an operational transformation challenge involving governance, workflows, customer strategy, organizational alignment and human oversight," said Matt Hasan, PhD and CEO of aiResults technology consulting firm, in an interview with TechTarget.</p> </section> <section class="section main-article-chapter" data-menu-title="4 best practices for AI personalization"> <h2 class="section-title"><i class="icon" data-icon="1"></i>4 best practices for AI personalization</h2> <p>Speakers on the CX panel shared various tips for AI personalization, many of which aligned with insights from other enterprise leaders TechTarget interviewed.</p> <h3>1. Build a unified data foundation</h3> <p>Enterprises often push toward real-time personalization before the <a href="https://www.techtarget.com/searchenterpriseai/opinion/The-critical-role-of-data-in-building-an-AI-agent">underlying data foundation</a> is ready -- and that's where execution starts to break down. Most organizations already have plenty of customer data, but it sits fragmented across tools and platforms.</p> <p>When systems aren't aligned, AI can surface insights but can't reliably act on them across the customer journey. The prerequisite for real-time personalization is not more data, but more usable data -- connected, normalized and accessible in a way that supports decisions.</p> <p>"The moment you try to scale before the foundation is ready, it falls apart," Khan said.</p> <h3>2. Start with one use case at a time</h3> <p>Successful AI personalization isn't about scaling everything at once. It's about narrowing scope, aligning around a specific outcome and sequencing execution in a disciplined way.</p> <p>Rather than broad transformation programs, organizations can start with well-defined use cases where the data and systems can actually support delivery, then expand through structured iteration.</p> <p>"Companies actually succeeding at real-time personalization aren't doing it everywhere -- they're doing it really well in one place," Khan said.</p> <h3>3. Make data usable, not locked away</h3> <p>Organizations that succeed with AI personalization stop treating data as something fragile or siloed. Instead, they connect it across teams, systems and workflows so it can flow into decisions and customer experiences.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Stop treating your data like this precious thing in a box -- use it. </figure> <figcaption> <strong>Jocelyn Chen</strong>AI and data leader, EY </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>The shift is from ownership to enablement. Data moves from a protected asset controlled by one function to something shared, operationalized and used in real time across the business.</p> <p>"Stop treating your data like this precious thing in a box -- use it. Harness it. Just start connecting, share it, democratize it," said Jocelyn Chen, AI and data leader at EY, in the session.</p> <h3>4. Build accountability and transparency into AI from day one</h3> <p>Trust in AI systems depends on whether organizations can explain how decisions are made -- and whether accountability is built in from the start. Transparency is not an afterthought. It is a design principle.</p> <p>"If you can show people why an agent made a decision and how it got there, trust follows naturally. Transparency isn't a feature you add later. It's the foundation. Build it in from the start or you're just hoping nothing goes wrong," Khan said.</p> <p>In production, that principle also shows up in how organizations handle failure. The emphasis shifts from avoiding mistakes entirely to owning them clearly when they happen.</p> <p>"If there's a bump, own it. Tell the customer, 'That algorithm wasn't right. We apologize for the mistake,'" Pearce said.</p> <p>Trust and transparency remain critical, but they do not require perfection. As organizations move AI systems into production, the expectation is not error-free performance, but <a href="https://www.techtarget.com/searchenterpriseai/tip/Agentic-AI-governance-strategies-A-complete-guide">visible accountability when issues arise</a>. The emphasis is shifting toward building systems that can be explained, corrected and improved in real time -- without slowing adoption. Organizations must move forward with intent, stay transparent with customers and acknowledge and fix mistakes when they happen.</p> <p><em>Tim Murphy is a site editor and writer for the IT Strategy team at TechTarget.</em></p> </section> Dell doubles down on hybrid AI infrastructure as enterprises shift from experimentation to production. However, data fragmentation continues to slow CX personalization efforts. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1270372095.jpg https://www.techtarget.com/searchcustomerexperience/news/366643343/dell-pushes-ai-personalization-but-data-hurdles-remain Thu, 21 May 2026 09:16:00 GMT <p>A resident goes into a Tokyo municipal office seeking help. He speaks a language the onsite staff can't speak. Traditionally, that interaction might end with the resident shuffled among departments, leading him to repeat the same information or leave without resolution altogether.</p> <p>Instead, the resident approaches a human-sized robot displaying the live face of a remote municipal worker, who assists him in real time. That scenario is part of a broader effort by Avaya and avatarin to rethink customer experience (CX) when expertise is not physically available where it's needed.</p> <p>avatarin, a Tokyo-based robotics and AI company, is using <a target="_blank" href="https://url.us.m.mimecastprotect.com/s/lkwACo2vOqf8ojQQqFzhJUpj_GK?domain=techtarget.com" rel="noopener">Avaya Infinity</a>, Avaya’s CX platform, to orchestrate interactions between AI systems, remote human agents and physical robots across environments, including airports, government offices and retail locations.</p> <section class="section main-article-chapter" data-menu-title="Contact center in a physical world"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Contact center in a physical world</h2> <p>The fresh deployment reflects Avaya's effort to extend the contact center beyond traditional voice and digital channels into physical service environments where organizations face staffing shortages, multilingual demands and fragmented service experiences.</p> <p>It also comes as enterprises face pressure to deliver more <a href="https://www.techtarget.com/searchcustomerexperience/tip/Why-customer-journey-touchpoints-matter">continuous service across disconnected digital and physical touchpoints</a>.</p> <p>At the center of the initiative is what avatarin CEO Akira Fukabori calls "unmet presence." These are situations where expertise is required in a physical location, but is not available on-site.</p> <p>"The trigger is often a situation where the right support or expertise is not available where it is needed," Fukabori told TechTarget.</p> <p>While enterprises have invested heavily in <a href="https://www.techtarget.com/searchcustomerexperience/tip/Omnichannel-orchestration-engages-customers-drives-revenue">omnichannel CX systems</a>, physical environments remain a weak point. Customers starting with in-person interactions often face staffing gaps or language barriers, leading to repeated explanations or abandoned interactions.</p> </section> <section class="section main-article-chapter" data-menu-title="Closing service gaps in physical environments"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Closing service gaps in physical environments</h2> <p>avatarin combines AI agents, remote specialists and physical robots designed as conversational interfaces. When combined with Avaya Infinity, customer context follows users across systems in real time, reducing repetition during handoffs between AI and human agents.</p> <p>"The biggest friction arises from data silos and handoffs between staff who lack specialized knowledge," Fukabori said.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The deployment is designed to preserve continuity as customers move between AI systems, remote workers and physical environments. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Unlike traditional kiosks or standalone video support tools, Fukabori said, the deployment is designed to preserve continuity as customers move between AI systems, remote workers and physical environments.</p> <p>The system uses interoperability standards to share customer context across enterprise workflows. Avaya describes its model as "tandem care," where <a href="https://www.techtarget.com/searchenterpriseai/tip/The-ethics-that-make-human-AI-agent-collaboration-work">AI systems and human agents collaborate</a> rather than operate independently.</p> <p>AI handles routine inquiries, translation and data&nbsp;gathering, while complex issues&nbsp;escalate&nbsp;to human specialists.</p> <p>Tony Lama, senior vice president and general manager of Avaya Software, and David Funck, Avaya CTO, said the platform is designed to unify AI, data and communications across hybrid environments with governance and deployment flexibility.</p> <p>This hybrid model is necessary, Fukabori said, because AI still lacks human judgment in complex or empathetic situations.</p> <p>"Agentic AI excels in scalability, responsiveness and task execution," he said. "However, empathy and complex decision-making remain the domain of humans."</p> <p>In Tokyo municipal pilots, avatarin's "newme" social robot enables remote specialists to assist residents directly. The robot's <a target="_blank" href="https://www.linkedin.com/products/avatarin-newme/" rel="noopener">face-forward display</a> and physical movement are designed to make interactions feel more natural and conversational.</p> <p>"When the face on the screen responds naturally&nbsp;and&nbsp;the robot moves deliberately, users quickly adapt to it as a normal interaction," Fukabori said.</p> </section> <section class="section main-article-chapter" data-menu-title="Blending AI and human expertise"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Blending AI and human expertise</h2> <p>Analysts note that physical AI deployments will depend less on hardware than on back-end integration and continuity of experience. Enterprises still struggle to connect digital CX systems with real-world service environments, said Jon Arnold, principal of&nbsp;J Arnold &amp; Associates.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Enterprises have spent years unifying digital interactions, but the physical world remains disconnected. </figure> <figcaption> <strong>Jon Arnold</strong>Principal, J Arnold &amp; Associates </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>"Enterprises have spent years unifying digital interactions, but the physical world remains disconnected," Arnold said. "The challenge is maintaining continuity as customers move between AI systems, human agents and physical spaces."</p> <p>That challenge is intensifying as organizations face labor shortages, rising multilingual demand and expectations for faster resolution.</p> <p>For avatarin, the goal extends beyond automation. "This model combines AI scalability with human expertise and judgment, and, together, they redefine how customer experience is delivered," Fukabori said.</p> <p>Avaya and avatarin emphasize that the aim is not to replace human interaction, but to extend expertise into environments where it's not physically present.</p> <p>As CX platforms evolve, the Avaya-avatarin deployment reflects a broader shift toward orchestration models extending beyond the contact center into physical environments where AI systems, human agents and frontline staff operate as a unified workflow.</p> <p><i>Moshe Beauford is a writer with nearly a decade of experience covering enterprise technology, including AI, unified communications and customer experience.</i></p> </section> Avaya has partnered with avatarin to unify customer interactions among AI, remote human agents and physical spaces. The goal is to improve contextual customer service. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1273438441.jpg https://www.techtarget.com/searchcustomerexperience/feature/Avaya-CX-service-blends-AI-robots-and-human-interactions Wed, 20 May 2026 08:51:00 GMT <p>Zendesk previewed a handful of <span data-teams="true">AI agents, copilots and admin tools</span> today that will roll out later this year. More importantly, the company gave a sneak peek at the bigger roadmap picture: autonomous service workforce management tools to supplement human employees and customer experience workers.</p> <p>Copilots include tools for analyzing content, service trends and the root causes of ticket generation. Agents to deliver employee service -- built out of technology from Zendesk's <a target="_blank" href="https://www.zendesk.com/newsroom/articles/zendesk-acquires-unleash/" rel="noopener">Unleash acquisition</a> last December -- operate in apps such as Slack and Microsoft Teams.</p> <p>Also in early preview are Agent Builder, a no-code designer; Action Flows for AI agents, a workflow builder; Context Graph, the foundation for agent analytics reporting; and MCP Client, a <a href="https://www.techtarget.com/searchsecurity/tip/Secure-MCP-servers-to-safeguard-AI-and-corporate-data">model context protocol</a> connector for Zendesk agents to tap outside data sources. MCP Server will come later, as will Quality Score, which measures the service quality of both human and AI agents.</p> <p>Zendesk hopes the mix of tools will help get customer service teams from where they are now with their current IT stacks and support technologies to an autonomous service enterprise, said Colin Murphy, chief customer officer at Zendesk. But because users' boards and C-suites are also pushing for accelerated AI adoption to keep up with their competitors, they have to show quick wins with prebuilt, out-of-the-box agents that automate simple tasks, too.</p> <section class="section main-article-chapter" data-menu-title="An early adopter's service AI roadmap"> <h2 class="section-title"><i class="icon" data-icon="1"></i>An early adopter's service AI roadmap</h2> <p>Technology vendors want to make AI adoption as frictionless as possible -- in the shortest time possible -- but many customers still grasp for that "autonomous AI" goal, realizing it takes not only technology but also people and process management that are simpatico.</p> <p>The business of booking monthly rentals -- a market that sits in a sweet spot between the short- and long-term stay -- has boomed since 2020, said Zendesk customer Cami Nariño, COO at Furnished Finder. The company launched in 2014, specializing in rentals for traveling nurses, who are typically looking to spend housing stipends.</p> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/gen_ai_costs_beyond_development-h.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/gen_ai_costs_beyond_development-h_half_column_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/gen_ai_costs_beyond_development-h_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/gen_ai_costs_beyond_development-h.png 1280w" alt="graphic that lists costs of GenAI beyond development" height="312" width="279"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Since the start of the pandemic, Furnished Finder has expanded from 20,000 to 300,000 properties. It has found a much wider audience among consumers -- such as digital nomads -- and workers across numerous industries and the military. Another growth area is insurance housing for individuals and families displaced from their homes.</p> <p>In the middle of its rapid expansion, Nariño said, the company moved off of a homegrown reservation system to Zendesk for its case management and help center.</p> <p>As it scales up, Furnished Finder is looking to automate more of its service interactions, with an emphasis on helping property owners prep, list, describe and price their rental spaces, among other things. That takes a lot of content -- with AI overlaid to surface the right answers and suggestions at the right times.</p> <p>Human customer service will always be the bedrock of Furnished Finder, she said, because the company's reputation is built on high-touch service, especially for the property owners and travelers using it for the first time.</p> <p>"So far, we have enabled Q&amp;A through Zendesk," Nariño said. "As users come to Fern -- our AI assistant -- the chatbot is going to help answer all of the transactional questions they have. The next phase that we're exploring is allowing for account lookups, and then account action -- taking that a step further and actually being able to say, 'Hey, it's [a particular customer] that I'm chatting with, and they need support with the calendar, so I am going to update their calendar for this specific listing.'"</p> </section> <section class="section main-article-chapter" data-menu-title="Both tactical and strategic AI"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Both tactical and strategic AI</h2> <p>That brings up the distinction between tactical, task-based AI tools and broader, long-term strategic AI initiatives. Customers like Furnished Finder want it both ways from their technology vendors.</p> <p>"There is a world in which you can try to automate everything," Nariño said. "But if you move too fast, you could lose some of the key components of actually providing service -- the human touch and the relationship building -- that I think are extremely important for our business."</p> <p>This AI implementation story is being repeated at many Zendesk shops -- and across the board -- in customer service, Murphy said. Contact centers need some fast, tactical improvements that quickly expand and automate customer service availability to 24/7 -- and hand over the simplest customer queries to AI agents, while saving the thornier issues for human agents.</p> <p>But as they build their hybrid human and AI workforces, they will also need broader, strategic AI to enable humans to manage and route work, as well as AI to spot content gaps in knowledge bases and report on trends driving customer tickets that can be solved with automation, when the agents are given the right content.</p> <p>That represents complex change management algebra. AI is evolving so fast that, in some cases, contact center leaders need a hand just figuring out where to start.</p> <p>"Some customers are maybe a little bit less ready for AI than others," Murphy said. "They need to rethink their customer service workflows, and they expect us to help them. We take that redefined process, we build it into our AI agent flows, and we build it into procedures that are generated and followed in our copilot technology."</p> <p><i>Don Fluckinger is a seasoned B2B technology journalist with over 30 years of experience, specializing in enterprise IT, digital experience and content management. As a senior news writer at Informa TechTarget, he delivers award-winning analysis that helps IT and business leaders navigate complex technologies to enhance customer and employee experiences. Got a tip? </i><a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article" target="_blank" rel="noopener"><i>Email him</i></a><i>.</i></p> </section> Zendesk makes the case for an autonomous service workforce for customer and employee experience. https://cdn.ttgtmedia.com/rms/onlineimages/ai_a238006601.jpg https://www.techtarget.com/searchcustomerexperience/news/366643472/Zendesk-adds-AI-tools-in-pursuit-of-autonomous-service Tue, 19 May 2026 11:00:00 GMT <p><i>Customer experience leaders have no shortage of customer data. The harder problem is knowing which groups of customers behave differently, why those patterns matter, and how marketing, product and customer data teams should act on them.</i></p> <p><i>Cohort analysis can help by grouping customers based on shared traits or behaviors, such as when they became customers, how often they use a product, what channels brought them in or how much revenue they generate. For CX and marketing decision-makers, the value is not just more segmentation; it is a clearer view of retention, personalization, churn risk and customer lifetime value.</i></p> <section class="section main-article-chapter" data-menu-title="Customer data is big business"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Customer data is big business</h2> <p><i>By 2027, global annual data creation is <a href="https://www.statspanda.com/live-counters/terabytes-of-data-created-globally" target="_blank" rel="noopener">predicted</a> to reach 284 billion TB. Companies, however, can't do much with that data unless they can analyze and apply it to their business needs. </i></p> <p><i>That's where cohort analysis comes in. </i></p> <p><i>Cohort analysis is a method of <a href="https://www.techtarget.com/searchcustomerexperience/definition/customer-segmentation">organizing customer data into segments</a>, or cohorts, based on factors such as age, geographic location, and frequency of use, and analyzes that data to reveal behavior patterns for each cohort. The result is richer, more detailed information companies can use to <a href="https://www.techtarget.com/searchcustomerexperience/answer/What-are-the-different-types-of-marketing-personalization">personalize and even hyper-personalize marketing efforts</a>.</i></p> <p><i>Arun Prem Sanker is a data scientist at Stripe and has more than 10 years of experience driving product growth and solving complex business challenges across diverse industries. His expertise includes experimentation, predictive modeling, machine learning (ML) and analytics. Prem Sanker has a proven track record of optimizing marketing strategies, improving conversion rates, and enhancing customer perception models. In this Q&amp;A, he offers best practices for using cohort analysis to better understand consumer behavior and enhance product marketing success. </i></p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/cust_ex-customer_segmentation.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/cust_ex-customer_segmentation_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/cust_ex-customer_segmentation_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/cust_ex-customer_segmentation.png 1280w" alt="Chart comparing persona-based, behavior-based and predictive customer segmentation methods" height="398" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Cohort analysis is one method marketers and customer data teams can use to segment customers and identify behavior patterns. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p><i>That decision-making value is especially important as marketing, product and CX teams try to make customer data more useful. Cohort analysis can help them move beyond broad averages and identify which customer groups need different messages, offers, product experiences or retention strategies.</i></p> <p><b>Editor's note:</b> <i>This Q&amp;A, originally published on ITPro Today in April 2025, has been reviewed, updated and republished for SearchCustomerExperience's audience.</i></p> <p><b>What are the main benefits of cohort analysis?</b></p> <p>Arun Prem Sanker: The biggest benefit is that it identifies behaviors within specific user groups. A Gen Z customer might behave differently than a Boomer. A power user who visits a site daily will display different behavior than an infrequent user. Behavior can also vary by geographic location. Cohort analysis enables companies to track the behaviors of specific groups, compare them with other groups and tailor marketing efforts to each group accordingly. Understanding this behavior helps marketers improve <a href="https://www.techtarget.com/searchcustomerexperience/tip/7-key-customer-experience-metrics-to-measure">retention rates and customer lifetime value</a>.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/xiPs4uXyI-w?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <p><b>How does cohort analysis provide deeper insights than traditional analytics?</b></p> <p>Prem Sanker: First, it enables companies to control for external factors, such as the seasons, the weather or a pandemic. Let's say customer activity in a specific area of the country declines for a few days. An aggregate analysis might not reveal that the decline was due to a widespread internet outage, but cohort analysis by geographic areas would.</p> <p>Second, cohort analysis helps distinguish between long- and short-term engagement patterns. For instance, a product like workflow software might experience a spike in sales at the beginning of a new year. Cohort analysis would reveal it as short-term behavior by a cohort of business owners starting the year by tapping their budgets for new technology.</p> <p>Here are two real-life examples. Netflix uses cohorts to understand who watches a particular type of content, such as comedy. If a cohort watches comedy, the platform recommends other comedy-related content to that cohort. Another example is Airbnb, which targets information based on a cohort's travel preferences. A beach-loving cohort will get travel content centered on beach locations.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> For CX and marketing decision-makers, the value is not just more segmentation; it is a clearer view of retention, personalization, churn risk and customer lifetime value. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p><b>What are the essential cohorts for companies to track?</b></p> <p><b></b>Prem Sanker: First is the acquisition cohort, which groups customers according to the channel that brings them to the business. That could be a Google search, an email or a website. The acquisition cohort also includes information on when they became customers. The second is the behavior and engagement cohort, which groups customers by usage. For example, how frequently do they visit a site or buy a specific product? The third is the revenue cohort, which categorizes users based on the revenue they generate.</p> <p><b>What advanced segmentation techniques can enhance cohort tracking?</b></p> <p>Prem Sanker: One technique is survival analysis, which <a href="https://www.techtarget.com/searchcio/tip/Risk-prediction-models-How-they-work-and-their-benefits">predicts when users will <i>churn</i></a> , or stop buying or using a product. Cohort-based retention rates make predictions based on customers who have already churned. Because it predicts the likelihood of churn over time, survival analysis enables companies to intervene and retain customers before they leave.</p> <p>Behavioral clustering, another advanced technique, uses <a href="https://www.techtarget.com/searchbusinessanalytics/feature/15-common-data-science-techniques-to-know-and-use">unsupervised ML techniques</a>, such as hierarchical clustering, to segment users based on their behavior. For instance, a streaming platform could use behavioral clustering to identify users who stream content only on weekends or only watch on Friday afternoons. This approach gives companies more detailed information on users, and the more detail available, the better the data analysis.</p> <p>A third approach involves recency, frequency and monetary (RFM) analysis. RFM sorts customers by how recently they've visited a site, how frequently they visit it and how much they spend during visits. Companies use this information to market to customers with similar RFM behaviors.</p> <div class="extra-info"> <div class="extra-info-inner"> <p></p> <h3 class="splash-heading">3 customer cohorts marketers commonly track</h3> <p>Companies commonly start with three types of cohorts: acquisition cohorts, which group customers by the channel or time period that brought them in; behavior and engagement cohorts, which group customers by usage patterns; and revenue cohorts, which group customers by the value they generate. Together, these cohorts can help marketing and product teams understand how different customers behave, where retention risks appear and which groups might respond to more personalized outreach.</p> </div> </div> <p><b>How can companies set up a cohort analysis framework that meets their business needs?</b></p> <p>Prem Sanker: First, identify the objectives and key results (<a href="https://www.techtarget.com/searchhrsoftware/definition/OKRs-Objectives-and-Key-Results">OKRs</a>). Does a business want cohorts based on usage, age or geographic location? Then, choose the relevant metrics, including conversion rate, retention rate and customer lifetime value. The conversion rate is the percentage of customers completing a transaction. The retention rate measures customer activity over a certain period. Customer lifetime value is the predicted revenue for a customer from the time they engage with the product to the time they churn. Product <a href="https://www.techtarget.com/searchcustomerexperience/tip/6-ways-to-use-analytics-to-improve-customer-engagement">analytics data, marketing attribution data and transactional data</a> provide fodder for these metrics.</p> <p>It's also important to hire and train employees with the skills needed to perform cohort analysis. <a href="https://www.techtarget.com/searchenterpriseai/definition/data-scientist">Data scientists</a> and product managers are essential, but marketing and engineering teams should also be integral to cohort analysis functions. Marketing teams can help guide OKRs because they know how to use the data to target customers better. Everyone needs the <a href="https://www.techtarget.com/searchcustomerexperience/tip/How-to-choose-a-customer-data-platform">right tools, such as data visualization</a>. Upskilling and training employees to use these tools correctly, along with competitive pay, will ensure the right talent is in place.</p> <p>Finally, it's essential for businesses to be aware of and plan for a few data-related curveballs, including artificial intelligence. AI is necessary for cohort analysis because data scientists use ML models to create cohorts. That said, the use of AI and AI agents to collect data raises privacy issues. Customers might love the idea of personalized marketing efforts yet harbor concerns about how much of their personal data is available for businesses to capture and use.</p> </section> <section class="section main-article-chapter" data-menu-title="The solution for better decisions"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The solution for better decisions</h2> <p>Concerns aside, cohort analysis far exceeds traditional data analysis in assisting companies in making the best decisions on how to reach a variety of customers. It's imperative for organizations to establish the right cohorts, train data scientists and product marketing employees to analyze the cohorts using the best tools possible and use the data to personalize and hyper-personalize marketing messages. It's the most effective way to use data in an increasingly data-driven world.</p> <p><i>Lisa Bertagnoli is a writer and editor based in Wisconsin. She has written for a variety of trade and consumer publications, including Builtin.com, AARP Bulletin and Crain's Chicago Business. Connect with Lisa on </i><a href="https://www.linkedin.com/in/lisa-bertagnoli/" target="_blank" rel="noopener"><i>LinkedIn</i></a><i>.</i></p> </section> Data scientist Arun Prem Sanker explains how cohort analysis can improve segmentation, retention, personalization and customer lifetime value. https://cdn.ttgtmedia.com/rms/onlineimages/check_g496816315.jpg https://www.techtarget.com/searchcustomerexperience/feature/How-cohort-analysis-improves-marketing-decisions Fri, 15 May 2026 10:30:00 GMT <p>In the agentic AI era, SAP wants to differentiate itself by simplifying integrations with ERP data and giving front-office workers access to it.</p> <p>Rolling out starting today -- with more planned throughout the rest of the year -- are SAP customer experience (CX) AI agents and assistants that aim to enable customer service workers to perform more detailed case management. The AI tools will also enable marketers to activate campaigns based on operational data, e-commerce teams to understand inventory flows, and sales teams to analyze more deals and identify the elements needed to complete them.</p> <p>Also coming soon: Agents that turn on "buy-for-me" capabilities for a user's customers.</p> <p>SAP earlier this month said it plans to <a href="https://www.techtarget.com/searchdatamanagement/news/366642794/SAP-acquisitions-of-Dremio-Prior-Labs-target-AI-development">acquire two startups</a>, Dremio -- a <a href="https://www.techtarget.com/searchdatamanagement/definition/data-lakehouse">data lakehouse</a> -- and Prior Labs, a frontier AI model foundry, both of which will figure into future SAP functionality if the deals go through. Another acquisition from last March, <a href="https://www.techtarget.com/searchdatamanagement/news/366619541/Reltio-adds-real-time-data-delivery-to-fuel-fast-decisions">Reltio</a>, adds new master data management capabilities to SAP's platform.</p> <section class="section main-article-chapter" data-menu-title="AI agents vs. assistants"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI agents vs. assistants</h2> <p>Agents do work, while assistants help frontline employees in various CX roles -- customer service and marketing, for example -- shape their ideas and manage their agents as they solve customer issues or determine market segments for their next campaign, said Balaji Balasubramanian, president and chief product officer of SAP Customer Experience and Consumer Industries.</p> <p>"The difference between the two is that agents are the real, autonomic thing that actually wakes up, runs, understands [work] and produces results," Balasubramanian said. "Assistants, the way we think about it, are targeted to a persona, to a department, to a team."</p> <p>SAP, Balasubramanian said, is moving from a "human <i>in</i> the loop" metaphor -- where AI needs approvals to advance work on a task -- to "human <i>on</i> the loop," where people monitor the AI as it works autonomously. But humans are the key to keeping those workflows working properly.</p> <p>"Humans matter, and they will get involved, like a customer service, a marketing or a sales persona, and then there are places where it's better digitally…" he said. "The human on the loop becomes so much more powerful to drive profitable growth."</p> </section> <section class="section main-article-chapter" data-menu-title="Where users are"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Where users are</h2> <p>Enterprise customers of SAP -- and everybody else -- are still in the process of reimagining their processes and how they will work, moving forward, as they also tackle their data projects to make AI the connective tissue of their operations, said PwC Digital Core Modernization Platform Leader Jennifer Colapietro and her colleague Munish Gupta, Principal, SAP Customer Experience Lead.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/sap_sapphire25Orl-f.jpg"> <img data-src="https://www.techtarget.com/rms/onlineimages/sap_sapphire25Orl-f_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/sap_sapphire25Orl-f_mobile.jpg 960w,https://www.techtarget.com/rms/onlineimages/sap_sapphire25Orl-f.jpg 1280w" alt="Photo of SAP CEO Christian Klein at SAP Sapphire 2025 with pro golf's Ryder Cup captains" data-credit="SAP" height="374" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>SAP CEO Christian Klein (shown here, center, at SAP Sapphire 2025 with pro golfers Jim Furyk, right, and Luke Donald, left) hopes to hit a hole in one with new customer experience AI this year. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>"We are seeing a crawl, walk, run situation," Gupta said. Customers are still determining whether to go human-in-the-loop or on-the-loop, and how to orchestrate the processes they are redesigning for AI. "This whole area is moving so fast, and every day there is something new."</p> <p>That said, SAP is well-positioned to enable customers to deploy agents and assistants interspersed among humans in their workstreams.</p> <p>"SAP has a real opportunity in front of them," Colapietro said. "We're already seeing SAP evolve itself from primarily a back-office ERP platform to a connected enterprise platform that can link operations and data -- the back office -- [with] the middle office and the front office.</p> <p>The new SAP CX features debuted today at the company's <a target="_blank" href="https://www.sap.com/events/sapphire/virtual.html" rel="noopener">Sapphire user conference</a> in Orlando, Fla.</p> <p><i>Don Fluckinger is a seasoned B2B technology journalist with over 30 years of experience, specializing in enterprise IT, digital experience and content management. As a senior news writer at Informa TechTarget, he delivers award-winning analysis that helps IT and business leaders navigate complex technologies to enhance customer and employee experiences. Got a tip? </i><a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article" target="_blank" rel="noopener"><i>Email him</i></a><i>.</i></p> </section> SAP woos users with more tools to plug customer experience into back-end ERP data. https://cdn.ttgtmedia.com/rms/onlineimages/customer_service03.jpg https://www.techtarget.com/searchcustomerexperience/news/366642687/SAP-rolls-out-customer-experience-AI-agents-assistants Tue, 12 May 2026 08:30:00 GMT <p>SEO ruled the roost in internet marketing and content promotion for decades, ever since the first search engines came into being, even if the practice of optimizing content for web consumption and discovery was not always called SEO at the time.</p> <p>Answer engines change that familiar model.</p> <p>Answer engines are AI systems that synthesize answers for users, often reducing the need to click through to individual websites. AEO, or answer engine optimization, is the emerging practice of shaping content so that those systems understand, trust and include a company's perspective in their answers. It is often discussed alongside GEO, or generative engine optimization, a broader term for optimizing content so generative AI systems can understand, synthesize and surface it in AI-generated responses.</p> <p>For readers still sorting out how AI search changes discovery, this overview of GenAI search engines helps explain why marketers are rethinking traditional SEO assumptions.</p> <p>Rather than <a href="https://www.techtarget.com/searchcontentmanagement/feature/Is-SEO-dead-How-GenAI-changed-search">replacing SEO outright</a>, AI-driven discovery reshapes many of the assumptions marketers have relied on for decades.</p> <p>AI has simplified many marketing tasks, including campaign copywriting, audience segmentation, lead scoring, sales outreach, social post generation and customer-data analysis. But it has also complicated how marketers reach people and build awareness online.</p> <p>SEO is a skill that requires expertise, but its basic goal is straightforward: create content that ranks well when people search for specific terms or phrases.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/LKmGM8zxKTY?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <p>Answer engines make discovery less direct. Systems such as ChatGPT, Google Gemini, Perplexity and <a href="https://www.techtarget.com/whatis/feature/Mastering-AI-search-optimization-Key-trends-and-strategies">AI search summaries</a> synthesize information from multiple sources, sometimes with fewer clear paths back to the original material.</p> <p>That makes topical authority, already important in SEO, even more important in an AEO environment.</p> <section class="section main-article-chapter" data-menu-title="SEO becomes one slice of a bigger pie"> <h2 class="section-title"><i class="icon" data-icon="1"></i>SEO becomes one slice of a bigger pie</h2> <p>Marketers now must understand what answer engines know about their brand, what questions buyers are asking, where competitors appear, what content gaps exist and how to build enough authority to appear in AI-generated summaries.</p> <p>The question is no longer just whether a page ranks. It is whether a brand shows up when a buyer asks an AI system about a topic, product category or business problem -- and whether that brand is represented accurately.</p> <p>That shift changes the job of marketing software.</p> <p>HubSpot, whose customer platform spans CRM, marketing, sales, service and content tools, recently built <a href="https://www.techtarget.com/searchcustomerexperience/news/366641773/HubSpot-builds-answer-engine-optimization-into-its-platform">answer engine optimization tools into its marketing platform</a>, a sign that AEO is moving from a separate SEO or content exercise into the software marketers already use to manage customer engagement.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The question is no longer just whether a page ranks. It is whether a brand shows up when a buyer asks an AI system about a topic, product category or business problem. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>HubSpot's AEO release is useful because it frames the shift clearly. Whether marketers call the practice AEO, GEO or AI search optimization, the underlying problem is the same: Search visibility is no longer limited to ranking on a results page.</p> <p>SEO is "not going away," but it is becoming "one slice of the pie" as marketers also manage authority, prompts, citations, content gaps, buying-stage questions and AI-generated answers.</p> <p>Marketing tools -- including CRM systems, CMSes, marketing automation platforms, SEO tools, analytics platforms, customer data platforms and campaign management systems -- can no longer be limited to helping teams publish content, manage campaigns or improve search rankings.</p> <p>To be useful in a search environment shaped by both SEO and AEO, they must help marketers understand how AI systems interpret their brand, where the brand appears or disappears in generated answers and what content is needed to earn authority across the buying journey.</p> <p>In that sense, marketing software is becoming more like a broader CX platform.</p> <p>The goal is not just to add AI writing tools or automate isolated tasks. It is to take work that marketing teams often perform episodically and make it more continuous, governed and agent-supported.</p> <p>The pattern is broader than AEO alone. HubSpot shows how answer engines are changing marketing from the outside by forcing teams to rethink brand visibility in AI-generated answers. &nbsp;</p> <p>Lenovo shows how AI can help marketers interpret fragmented internal data across campaigns, UX, e-commerce and customer journeys.</p> <p>Adobe shows how vendors are trying to package AI automation more broadly into CX and marketing platforms.</p> <p>These are not fully autonomous, free-roaming agents. The Adobe example is more about task-based and workflow agents operating inside a specific CX environment, grounded in customer data, brand rules and workflow logic.</p> <p>That distinction matters. It is another sign that AI agents work best, at least for now, when their tasks are narrow enough, their data environment is defined and human oversight remains part of the process.</p> <p>Taken together, these examples show how marketing software is evolving beyond campaign execution into systems that help marketers interpret customer behavior, manage AI-driven discovery and govern agent-supported workflows.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading"></h3> <h3 class="splash-heading">How AI is changing the job of marketing software</h3> <p>Marketing software is being pushed beyond traditional campaign execution. Newer AI-enabled tools increasingly help teams do the following:</p> <ul class="default-list"> <li>Understand how answer engines interpret a brand.</li> <li>Identify buyer questions across the buying journey.</li> <li>Find content gaps that weaken topical authority.</li> <li>Analyze fragmented campaign, UX and website data.</li> <li>Turn scattered internal signals into usable direction.</li> <li>Apply brand rules and business goals to AI-supported workflows.</li> <li>Govern agentic marketing work through data, rules and oversight.</li> </ul> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Marketing software has a new job"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Marketing software has a new job</h2> <p>The changes around answer engines, AI data agents and agent-supported CX platforms point in the same direction.</p> <p>Marketing platforms increasingly need to combine content strategy, customer data analysis, workflow orchestration and AI oversight. They must help teams move from publishing more content to understanding which questions remain unanswered and where the brand is absent or misrepresented.</p> <p>Answer engines are putting pressure on the whole marketing software stack because they change the path between buyer questions and brand visibility. If potential customers increasingly get synthesized answers rather than click through traditional search results, marketers need tools to understand and influence that answer layer.</p> <p>SEO helped marketers compete for search rankings. AEO asks them to compete for inclusion, authority and accuracy inside AI-generated answers. AI data agents help them understand the internal signals behind their content and customer experiences. Agent-supported marketing platforms try to turn those signals into continuous, monitored action.</p> <p>Marketing tools are being pushed to do more than help teams execute. They now must help teams interpret, direct and govern the work.</p> <p>Answer engines are only one part of that shift. But they are a powerful signal that marketing software is being redesigned for a world where discovery, data and customer engagement are increasingly mediated by AI.</p> <p><i>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</i></p> </section> Answer engines are changing how buyers find info, shifting marketing software beyond SEO and campaigns into brand interpretation, data synthesis and AI decisions. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1150454068.jpg https://www.techtarget.com/searchcustomerexperience/feature/Answer-engines-put-marketing-tools-on-notice Fri, 08 May 2026 18:01:00 GMT <p>In 2025, roughly 55,000 job cuts&nbsp;were linked, at least in part, to the proliferation of artificial intelligence.</p> <p>Companies including Meta, Amazon and IBM have made staff reductions citing AI-driven organizational efficiency. More broadly, Google, Microsoft and Salesforce have grown increasingly explicit that AI can enable them to operate with slimmer teams.</p> <p>In some instances, companies have gone further, <a href="https://www.techtarget.com/searchcustomerexperience/tip/AI-creating-new-contact-center-jobs-for-agents">restructuring entire job functions around AI</a> and eliminating roles, which raises bigger questions: Could AI replace contact center agents? And, if so, is that necessarily a bad thing?</p> <section class="section main-article-chapter" data-menu-title="Replacing human agents is 'a mistake'"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Replacing human agents is 'a mistake'</h2> <p>Firing employees to replace them with AI -- especially in the contact center space -- is "a mistake," said Jeff Pulver, who leads The vCon Foundation, a <a target="_blank" href="https://www.pulver.com/vconfoundation" rel="noopener">virtualized conversations group</a>. Pulver is a VoIP pioneer whose advocacy and efforts on the regulatory front paved the way for modern internet-based communications.</p> <p>"The mistake some companies will make is thinking the goal of AI is to remove humans from the experience. The real opportunity is to remove friction from the experience," Pulver said.</p> <p>It is a widely accepted notion that AI is supposed to cut customer service costs. Yet Gartner forecasters <a target="_blank" href="https://www.customerexperiencedive.com/news/ai-cheaper-than-human-customer-service-gartner/813413/" rel="noopener">note otherwise</a>. They say that&nbsp;by&nbsp;2030, costs per resolution for generative AI will exceed $3, which could exceed the cost of some outsourced agents.</p> </section> <section class="section main-article-chapter" data-menu-title="New human role in the contact center"> <h2 class="section-title"><i class="icon" data-icon="1"></i>New human role in the contact center</h2> <p>Humans are expected to step into more of an advisory role, according to contact center experts at The Office Gurus, a provider of call center services. Human agents would focus on empathy and managerial roles, while AI performs daily, repetitive tasks like ticketing and notetaking.&nbsp;Jaimie Bell, vice president of client solutions at The Office Gurus, described the transition as AI takes a more prominent role in the customer experience.</p> <p>"It's a managed transition, and that's by design," she said. "AI handles the tactical aspects: the knowledge, the process, the procedure. But humans focus on the actual conversation. AI strengthens the human element by removing distractions, not replacing the people who deliver empathy."</p> <p>Brian Peterson, co-founder and CTO of Dialpad, described a broader shift in responsibilities, from human agents doing the work to orchestrating it. Instead of handling every interaction themselves, agents increasingly guide AI systems using their experience and judgment, turning frontline knowledge into structured workflows.</p> <p>According to Bell, The Office Gurus,&nbsp;a RingCentral customer, saw measurable gains in <a href="https://www.techtarget.com/whatis/definition/Average-handle-time-AHT-What-is-it-and-how-to-improve-it">average handle time</a>, which dropped by 45 seconds, allowing agents to manage 27% more volume without adding head count. Customer satisfaction scores also rose by as much as 25%, nixing the need to hire additional human agents.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The moment a customer needs reassurance, judgment or accountability, the human voice becomes the brand. </figure> <figcaption> <strong>Jeff Pulver</strong>Chief evangelist officer, The vCon Foundation </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Contact centers have long been under pressure to do more with fewer resources. Paired with high turnover rates, rising customer expectations and the stress of handling frustrated callers, these environments are often complex to manage and even more taxing to staff.</p> <p>"Customers rarely contact a support center because things are going well. They call when something is broken, confusing or urgent," Pulver said. "Automation can resolve many routine requests quickly. But the moment a customer needs reassurance, judgment or accountability, the human voice becomes the brand."</p> </section> <section class="section main-article-chapter" data-menu-title="AI reality and points of tension"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI reality and points of tension</h2> <p>Businesses care about efficiency and cost, and AI is already changing how contact centers operate. This notion aligns with what Peterson sees in the market. Most C-suite leaders, he said, are not trying to cut head count, but rather "stop the bleeding" from constant <a target="_blank" href="https://www.freshworks.com/customer-service/support-tiers/" rel="noopener">Tier 1</a> agent churn. By offloading repetitive work to AI, companies aim to retain experienced agents and reduce burnout.</p> <p>For many leaders, the focus has shifted from whether AI will replace humans and toward where it makes sense to deploy it.&nbsp;Gartner found that more than 80% of organizations expect some reduction in agent head count over the next 18 months. Most reductions are gradual and not solely driven by AI, Gartner noted.</p> <p>Often, AI does not free up&nbsp;time for&nbsp;workers, according to a Harvard Business Review <a target="_blank" href="https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it" rel="noopener">article</a>. The promise is that AI will lighten workloads, but it has not consistently delivered time savings. This effect compounds when teams have to navigate fragmented systems of record like a CRM system.</p> <p>Some companies face integration challenges, while others see real gains in productivity and agent retention when AI is used as a tool to assist rather than replace agents.</p> <p>Vendors are eager to show AI as transformational. But, for buyers, what matters most is whether these tools solve day-to-day problems inside the contact center. Here is where Pulver said humans have a leg up if they use voice communication.</p> <p>"Voice remains the most natural interface humans have. When a situation becomes emotional, complicated or urgent, people reach for the phone. That will not change. What is changing is what happens to the conversation," he said.</p> </section> <section class="section main-article-chapter" data-menu-title="The evolution of the contact center"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The evolution of the contact center</h2> <p>For decades, communications networks carried conversations but had no memory of them.&nbsp;A call&nbsp;happened, people spoke and when&nbsp;the call&nbsp;ended, the insight disappeared.&nbsp;Businesses have millions of customer conversations every day but learn little from them. "That era is ending," Pulver said.</p> <p>When conversations can be <a href="https://www.techtarget.com/searchcustomerexperience/tip/Customer-interaction-analytics-spurs-better-business-results">transcribed, structured and analyzed</a>, the interaction is no longer a fleeting event and starts becoming a signal the organization can respond to.</p> <p>"Communications systems are finally gaining memory," Pulver added. "At that point, the contact center stops looking like a cost center and starts looking like a listening system for the entire company.&nbsp;Every conversation becomes a source of operational insight about what customers want, where processes break and how products perform in the real world."</p> </section> <section class="section main-article-chapter" data-menu-title="The AI vision in the contact center"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The AI vision in the contact center</h2> <p>A spike in billing complaints can now be flagged in real time. With the help of AI, this speed gives product teams immediate feedback instead of waiting weeks for reports. AI can also handle much of that initial interaction, or information gathering, assisting agents when they are requested or required to resolve issues.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Some companies see productivity gains and agent retention when AI is used to assist rather than replace agents. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>"When companies start learning from their conversations, the organization becomes more adaptive. Executives who understand this shift begin to see the contact center differently," Pulver said. "Instead of measuring it only by cost per call or average handle time, they start asking a different question: What are our customers actually telling us?"</p> <p>The next step is conversations themselves start to take on structure, he added.</p> <p>Instead of disappearing once they end, conversations are a persistent record that systems can reference, analyze and learn from over time. At that point, Pulver noted, the economics of communication change. The call is no longer just a moment between two people.</p> <p>"It becomes part of the&nbsp;memory of the organization," he said. "The companies that learn from their conversations will improve faster than the ones that let those conversations disappear. We're entering a period&nbsp;where&nbsp;conversations become part of the&nbsp;intelligence of the network.&nbsp;The network used to carry conversations. Now it will help organizations learn from them."</p> <p>As companies adapt to a world where AI is everywhere, the challenge is learning how humans and machines can work together. Only time will tell if total human replacement will become a reality as AI advancements persist.</p> <p><i>Moshe Beauford is a writer with nearly a decade of experience covering enterprise technology, including AI, unified communications and customer experience.</i></p> </section> No, AI will not fully replace contact center agents. Human, voice-based customer conversations that are transcribed are becoming a data gold mine for organizations. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1206801125.jpg https://www.techtarget.com/searchcustomerexperience/feature/AI-should-remove-friction-not-agents-from-contact-centers Fri, 08 May 2026 08:55:00 GMT <p>Two years after a brutal activist investor battle that brought about change at the top, this week, Twilio made its case to line-of-business leaders as a more fully formed customer experience cloud.</p> <p>Twilio, of course, also needs to retain its loyal developer customer base. It hopes to pull all that off with the release of what it calls its "next generation platform," which includes several features, among them Conversation Memory, which aggregates customer data across channels such as email, phone, chat and text; Conversation Orchestrator, which combines that data into a continuous conversation narrative; and Agent Connect, which plugs AI into voice and messaging channels.</p> <p>Twilio has long been a <a href="https://www.techtarget.com/searchcustomerexperience/news/366623464/Twilio-updates-conversational-intelligence-expands-CDP">developer-friendly platform</a>, with popular tech building blocks around its Flex <a href="https://www.techtarget.com/searchcustomerexperience/definition/contact-center-as-a-service-CCaS">contact center as a service</a>, <a href="https://www.techtarget.com/searchunifiedcommunications/news/252450884/Twilio-buys-SendGrid-for-email-APIs">SendGrid email tools</a> and <a href="https://www.techtarget.com/searchcustomerexperience/news/252490974/CEOs-discuss-Twilios-Segment-customer-data-platform-buy">Segment</a> marketing-oriented customer data platform. Co-founder and former CEO Jeff Lawson coded apps live from the keynote stage at the company's annual Signal user conference. But he was pushed out in 2024 after two activist shareholders won their quest for changes at the company.</p> <p>The new regime, led by new CEO Khozema Shipchandler, rewrote the company's strategy to focus on infrastructure to support a conversation layer connecting data warehouses and CX tools, and to simplify the deployment of Twilio's technologies, said Inbal Shani, Twilio's chief product officer and head of R&amp;D.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/twilio_signal_2026-f.jpg"> <img data-src="https://www.techtarget.com/rms/onlineimages/twilio_signal_2026-f_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/twilio_signal_2026-f_mobile.jpg 960w,https://www.techtarget.com/rms/onlineimages/twilio_signal_2026-f.jpg 1280w" alt="Picture of Twilio CEO Khozema Shipchandler at Signal 2026 " data-credit="Twilio" height="294" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Twilio's CEO Khozema Shipchandler at Signal 2026, where the company's refreshed customer engagement platform was unveiled. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>At the time, Twilio's new leadership immediately had to solve another puzzle, like everyone else in Silicon Valley: how to incorporate the rapidly emerging generative and agentic AI into the platform.</p> <p>"We started looking into the new way[s] of customer engagement," Shani said. "What is truly a conversation that is happening now between humans? Humans and AI? And, in the future, AI-to-AI conversation? That's where we invested a lot in building this foundational layer."</p> <p>With foundational CX pieces in place, such as messaging and voice, as well as customer data and contact center, the stage was set for Twilio to layer AI across everything to connect communications, data and automation, said Paul Nashawaty, analyst at TheCube Research.</p> <p>He said the next generation platform will make Twilio more competitive with the likes of Salesforce and Genesys. For joint customers, though, Twilio also strives to make CX operations systems work together more efficiently as a composable infrastructure layer, Shani said.</p> <p>With that approach, the company has begun appealing to customers outside its developer orbit.</p> <p>"Twilio's moving from a developer-first API company into a more complete, AI-powered customer engagement platform," Nashawaty said. "What's changing is who's buying. While developers are still key, AI is attracting more business and CX leaders because its use cases tie directly to revenue and customer experience."</p> <p>That said, Twilio still focused heavily on developers at <a target="_blank" href="https://signal.twilio.com/" rel="noopener">Signal 2026</a> this week, with flashing graphics and myriad messages around the "build" theme, such as "Build moments that people never forget."</p> <p><i>Don Fluckinger is a seasoned B2B technology journalist with over 30 years of experience, specializing in enterprise IT, digital experience and content management. As a senior news writer at Informa TechTarget, he delivers award-winning analysis that helps IT and business leaders navigate complex technologies to enhance customer and employee experiences. Got a tip? </i><a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article" target="_blank" rel="noopener"><i>Email him</i></a><i>.</i></p> The next-generation platform comes after a couple of years of soul-searching at Twilio. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1206801125.jpg https://www.techtarget.com/searchcustomerexperience/news/366642826/Twilio-revamps-updates-customer-engagement-platform Thu, 07 May 2026 12:21:00 GMT <p>For exceptional customer experiences, organizations must understand what customers want and need. Equally important, customers should feel like organizations listen to them, and organizations should make customers feel special with personalized service.</p> <p>Collecting customer feedback can help brands <a href="https://www.techtarget.com/searchcustomerexperience/tip/Customer-experience-strategy-tips-to-build-a-valuable-CX">improve their customer experience strategies</a> and lead to better personalization.</p> <section class="section main-article-chapter" data-menu-title="What is customer feedback?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is customer feedback?</h2> <p>Customer feedback comprises the ideas, opinions and suggestions that customers have about an organization and its products or services. Feedback can be reactive, meaning it follows a service or support interaction. Or it can be proactive, meaning it was not driven by an interaction. It can also be positive, negative or neutral, depending on a customer's experience with the brand.</p> <p>For many organizations, customer feedback now pertains to service or support interactions with human agents and customer-facing AI agents. Nearly 60% of companies measure the performance of their human agents against AI agents, according to a global Metrigy CX study. Among those companies, the assessments most often come via customer feedback surveys. Half of companies are collecting customer feedback for this purpose.</p> </section> <section class="section main-article-chapter" data-menu-title="Why is customer feedback important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is customer feedback important?</h2> <p>Customer feedback is important because it provides insights that organizations can use to improve their business. This data encompasses customer-facing interactions, agent experiences, AI agent optimization and product development. It also helps brands better understand customers, so they can more easily&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/tip/How-to-comprehensively-personalize-the-customer-experience">create personalized experiences</a>.</p> <p>Personalization is now critical as it relates to a growing CX trend, namely proactive engagement. The evolution from reactive customer service to proactive engagement is a strategic shift for nearly 60% of businesses today, according to Metrigy's research. By extracting insights from customer feedback, AI can make proactive outreach more timely and personalized.</p> </section> <section class="section main-article-chapter" data-menu-title="Types of customer feedback"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Types of customer feedback</h2> <p>Customer feedback can be qualitative or quantitative. Those categories break down as follows:</p> <ul type="disc" class="default-list"> <li><b>Qualitative feedback</b> comes from customers' open-ended comments. Organizations can collect this information in focus groups, surveys, online reviews, social media posts and, increasingly, through AI applications. Today, surveys are the top way to track customer satisfaction, but a close second is <a href="https://www.techtarget.com/searchcustomerexperience/tip/Customer-interaction-analytics-spurs-better-business-results">interaction analytics</a>, which gathers insights from customer feedback. At 59.2%, surveys are the top method, followed by interaction analytics at 53.2%, according to Metrigy research.</li> <li><b>Quantitative feedback</b> comes through numerical ratings, such as one to five stars. Increasingly, <a href="https://www.techtarget.com/searchcustomerexperience/tip/How-AI-inferred-sentiment-analysis-unlocks-customer-insights">companies are using inferred sentiment</a> to determine customer ratings rather than relying on fickle customers themselves to click on a star, so to speak.</li> </ul> <p>Inferred sentiment uses AI and large volumes of data to estimate what a customer's level of satisfaction is on every call. AI can <a target="_blank" href="https://www.qevalpro.com/blog/ai-sentiment-analysis-improves-customer-experience/" rel="noopener">detect sentiment</a> and word choice and assign a rating, based on actual customer feedback for similar customers. The result is a customer sentiment score for every call -- some actual from the customers, some implied via inferred sentiment.</p> <p>Nearly 40% of companies are using AI-enabled inferred sentiment today.</p> </section> <section class="section main-article-chapter" data-menu-title="What is a customer feedback loop?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is a customer feedback loop?</h2> <p>A customer&nbsp;<a href="https://www.techtarget.com/searchitchannel/definition/feedback-loop">feedback loop</a>&nbsp;comprises the request for information, data analysis, actions taken based on the analysis and letting customers who shared feedback know what changes resulted from their input. This final part shows customers that organizations appreciate their feedback and that it can make a difference.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Though 78.8% of companies gather customer feedback, only 59.1% act on it. </figure> <figcaption> <strong>Metrigy research</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Feedback loops are continuous. Organizations should always assess customer feedback and, based on insights from that information, adapt as necessary. However, Metrigy's data shows a significant execution gap: Though 78.8% of companies gather customer feedback, only 59.1% act on it. Interaction analytics can help businesses close this gap by analyzing transcripts, recordings and conversations to discover issues and trends in near real time.</p> </section> <section class="section main-article-chapter" data-menu-title="5 methods to collect customer feedback"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5 methods to collect customer feedback</h2> <p>Collecting customer feedback can happen&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/tip/Why-customer-journey-touchpoints-matter">at any touchpoint</a>&nbsp;and is often simple and straightforward. However, some methods may need to incentivize customers to get results.</p> <p><b>1. Use qualitative and quantitative feedback.</b>&nbsp;Organizations can gather feedback from interactive, responsive and implicit mechanisms. Those break down as follows:</p> <ul type="disc" class="default-list"> <li>Interactive feedback comes from one-to-one interviews either in person or over video, focus groups and live chats. This option lets customers share their opinions and ideas about set topics, such as new products or services, changes in pricing or new interaction channels.</li> <li>Responsive feedback means&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/tip/How-to-gather-and-evaluate-customer-sentiment">customers share how they feel</a>&nbsp;about customer service interactions through a survey, SMS polls, online reviews, social media comments or ratings.</li> </ul> <ul type="disc" class="default-list"> <li>Implicit feedback requires organizations to analyze statistics, such as website visits and call data, and apply advanced technologies like natural language processing and sentiment analysis to gain insights from recordings. This analysis can uncover trends and get ahead of issues before they escalate.<b> </b>AI-enabled inferred sentiment represents the biggest gap between successful and unsuccessful companies today. This technology enables brands to get ahead of issues before they escalate.</li> </ul> <p><b>2. Request feedback immediately after an interaction.</b>&nbsp;If organizations deliver a survey or feedback request form in the moment, customers can more accurately convey their sentiment. They can better understand and relay their feelings at the time of the interaction rather than providing feedback later. Additionally, gathering feedback right after an interaction correlates to increased business success, according to Metrigy.</p> <p><b>3. Add surveys at various touchpoints.&nbsp;</b>This strategy can maximize the potential for gathering feedback, as customers can&nbsp;contact a business in any way they choose. Survey requests can be at the bottom of a receipt, through an SMS poll or at the end of a call.</p> <p><b>4. Offer a reward for completing surveys.&nbsp;</b>Even a small incentive can trigger responses from customers. Rewards can include a discount, a free gift or an exclusive promotion.</p> <p><b>5. Request feedback from everyone -- not a select few.&nbsp;</b>Organizations shouldn't let agents select who receives a post-interaction survey. Thanks to AI, businesses no longer have to rely on small, manual samplings. Tools like AI-enabled inferred sentiment can evaluate the words and sentiment of all customer conversations to provide an accurate reflection of human and AI agent performance and overall customer satisfaction.</p> <p>If agents self-select customers, they may choose people who had positive experiences. This can lead to an inaccurate reflection of an agent's performance and overall customer satisfaction.</p> </section> <section class="section main-article-chapter" data-menu-title="How to use collected data"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to use collected data</h2> <p>Using data from customer feedback requires organizations to analyze it and identify what actions to take based on the intelligence gained. The vast majority of companies Metrigy has studied now consider customer interaction data either vital or important for improving business metrics. Some examples of how to use this data include the following:</p> <ul type="disc" class="default-list"> <li>Adjust sales and marketing strategies&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/tip/7-customer-experience-trends-to-have-on-your-radar-in-2023">based on trends discovered</a>.</li> <li>Advise product development to determine updates and revisions that will meet customer demand and improve revenue.</li> <li>Help executives make strategic decisions using customer feedback data.</li> <li>Craft proactive engagement strategies and deliver personalized outreach using insight from customer feedback.</li> <li>Analyze and compare the effectiveness of AI agents vs. human agents, which companies rank as the most valuable use for customer interaction analytics.</li> <li>Share feedback with service and support agents so they understand what they do well,&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/feature/5-examples-of-bad-customer-service-and-how-to-avoid-them">or not so well</a>, during customer interactions. Couple this with AI-based training to identify coaching opportunities.</li> <li>Determine which interaction channels are most successful and which customer-facing technologies to use.</li> <li>When a customer leaves a positive rating, such as five stars, ask them to share an online review.</li> <li>If a customer expresses dissatisfaction or other negative sentiment during an interaction, use AI to offer a discount or credit in real time, or follow up proactively to solve the issue before it escalates into a viral social media complaint.</li> <li>Integrate customer feedback into marketing automation tools.</li> </ul> <p>Collecting customer feedback is essential for understanding experiences and improving business practices. Customer feedback drives product improvements and enhances customer satisfaction. Using multiple collection methods, including surveys and social media, is essential for gathering diverse insights.</p> <p><i>Beth Schultz is vice president of research and principal analyst at Metrigy. She focuses her research on unified communications, collaboration and digital customer experience.</i></p> </section> Businesses should collect customer feedback to address customer issues and create positive experiences. AI tools can help show deeper insights into customer sentiment. https://cdn.ttgtmedia.com/rms/onlineimages/customer_service06.jpg https://www.techtarget.com/searchcustomerexperience/tip/How-to-collect-customer-feedback Thu, 07 May 2026 03:00:00 GMT <p>ServiceNow continued its fusillade against Salesforce -- and, to a lesser degree, Oracle, Microsoft and other integrated CX platforms -- with the release of Autonomous CRM, marketing automation features and vertical-industry customizations.</p> <p>The CRM addition to its <a href="https://www.techtarget.com/searchcustomerexperience/news/366629754/AI-agents-evolve-how-automated-customer-service-works">customer service</a> and <a href="https://www.techtarget.com/searchitoperations/news/366639250/ServiceNow-touts-AI-governance-for-its-Autonomous-Workforce">AI automation</a> suite has been something ServiceNow has been talking about <a href="https://www.techtarget.com/searchcustomerexperience/news/366623581/ServiceNow-rolls-into-Salesforce-territory-with-CRM-agentic-AI">for some time</a>. Today, the company advanced that idea further with a bundle of AI agents for field service, case management and sales.</p> <p>ServiceNow has "service" in its name, as its roots are in IT service management (<a href="https://www.techtarget.com/searchitoperations/definition/ITSM">ITSM</a>). Over the last few years, however, it has built out sales-friendly features such as order management and configure-price-quote, forming a CRM. Now the company must demonstrate its worthiness to current and prospective users to expand beyond the boundaries of customer and employee service, said Rebecca Wettemann, founder of independent research firm Valoir.</p> <p>"ServiceNow's challenge with CRM is not a technical one -- it's been doing many of the key CRM pieces for a while," Wettemann said.</p> <p>"It's about convincing business leaders who think of ServiceNow as an ITSM platform that it understands the CRM space and not only can technically meet the needs of sales and service leaders but can speak their language and give them guidance on how to [deploy] the tech to best do their jobs."</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/servicenow_autonomous_crm_case_manager-f.jpg"> <img data-src="https://www.techtarget.com/rms/onlineimages/servicenow_autonomous_crm_case_manager-f_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/servicenow_autonomous_crm_case_manager-f_mobile.jpg 960w,https://www.techtarget.com/rms/onlineimages/servicenow_autonomous_crm_case_manager-f.jpg 1280w" alt="Screenshot of ServiceNow Autonomous CRM Case Management AI Specialist" data-credit="ServiceNow" height="319" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The ServiceNow Autonomous CRM Case Management AI Specialist is one of the features released today. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <section class="section main-article-chapter" data-menu-title="Embedding AI in workflows"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Embedding AI in workflows</h2> <p>ServiceNow customer Kyle Seiter is CIO of medical mobile medical diagnostics company TridentCare. His company dispatches medical professionals and equipment such as X-rays, ultrasound and lab services to patient-care settings in places like nursing homes, rehab hospitals and correctional facilities in 46 U.S. states. TridentCare is an early adopter of ServiceNow AI tools to sharpen lead-to-cash (<a href="https://www.techtarget.com/searchcustomerexperience/definition/Customer-Life-Cycle">customer lifecycle</a>) processes, automating scheduling of people and equipment, and rescheduling as well -- one of those complex processes that is difficult to manage manually.</p> <p>One of TridentCare's initial AI projects has been to streamline X-ray dispatching, a medical service that represents a sizeable chunk of its business.</p> <p>"It's really a cost-weighted algorithm that gets applied to our particular business needs, which has allowed us to automate and remove the cognitive load that all of our dispatchers have today and move to near 100% automation in the first step of dispatching," Seiter said. "That means tens of thousands of manual touches have been eliminated from our business, adding scale and future opportunity."</p> <p>Having gone through this process so far, Seiter said the idea of a <a href="https://www.techtarget.com/searchitoperations/news/366639662/SaaSpocalypse-Maybe-not-but-SaaS-applications-are-changing">SaaSpocalypse</a>, where AI codes a new custom enterprise stack that replaces traditional applications, is a red herring.</p> <p>Established platforms like ServiceNow will have to orchestrate automation of fragmented back-end systems, which will not be managed by -- or replaced with -- one-off apps once enterprise IT stacks have been rebuilt for AI. Many stacks might look fragmented right now, but that is not the end-state companies like his are working toward.</p> <p>"The market has gotten a little sideways on how AI has the potential of disrupting the enterprise suite of software, saying that there is no need for [SaaS applications]," Seiter said. "I see that as a farce."</p> <p>ServiceNow also plans to evolve vertical-specific Autonomous CRM features to address process automation across industries such as financial services, telecommunications, healthcare, manufacturing, government and retail, among others.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/EUKVlxHyw-k?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Tenon marketing integration"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Tenon marketing integration</h2> <p>ServiceNow also made first moves toward a more fully developed CX platform, thanks to an OEM deal with marketing automation startup Tenon. The platform will incorporate natively embedded Tenon features, including customer journey building, audience segmentation, and email and text marketing channels.</p> <p>Tenon received funding in multiple rounds from ServiceNow Ventures and built its marketing automation features on ServiceNow. Some observers might wonder why ServiceNow doesn't just acquire Tenon, but there's a good reason it doesn't, said Terence Chesire, group vice president, ServiceNow CRM and Industry Workflows.</p> <p>"The reason we value them being independent is that they have a strong heritage in marketing," Chesire said. "We want them to form a strong opinion about how they should approach marketing and educate us in that process. We think that's the best way that we can make sure that they bring a distinct view."</p> <p>Will all this fly with technology buyers? Wettemann said that user trust in ServiceNow's AI guardrails, mixing deterministic business rules with the probabilistic nature of large language models, will be key to the success of Autonomous CRM.</p> <p>"ServiceNow's pitch is increasingly going to be, 'The people you trust with your business-critical IT operations should be the ones you trust with AI,'" Wettemann said. "A lot of initial DIY efforts didn't give much thought to issues of governance, permissions, data leakage or auditability. Organizations are now realizing this is a key piece of the overall AI value puzzle."</p> <p>Autonomous CRM and other CX features were released in conjunction with ServiceNow's <a target="_blank" href="https://www.servicenow.com/events/knowledge.html" rel="noopener">Knowledge 2026</a> user conference May 5-7 in Las Vegas.</p> <p><i>Don Fluckinger is a seasoned B2B technology journalist with over 30 years of experience, specializing in enterprise IT, digital experience and content management. As a senior news writer at Informa TechTarget, he delivers award-winning analysis that helps IT and business leaders navigate complex technologies to enhance customer and employee experiences. Got a tip? </i><a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article" target="_blank" rel="noopener"><i>Email him</i></a><i>.</i></p> </section> ServiceNow adds CRM and marketing automation features to its stack. https://cdn.ttgtmedia.com/rms/onlineimages/iot_g1182604383.jpg https://www.techtarget.com/searchcustomerexperience/news/366642658/ServiceNows-Autonomous-CRM-takes-aim-at-Salesforce Tue, 05 May 2026 13:00:00 GMT <p>The way buyers make purchase decisions has changed significantly, and so has the map businesses use to understand them. Buyers now encounter brands across more channels, in more formats, and at more stages of the decision-making process than ever before. While traditional search engine use is still strong, a growing share of that initial research is happening through generative AI tools like ChatGPT and Perplexity rather than the company's website or a sales rep's outreach.</p> <p>That research kicks off the <a href="https://www.techtarget.com/searchcustomerexperience/tip/5-customer-journey-phases-for-businesses-to-understand">buyer's journey</a>, represented as a series of touchpoints that span from initial awareness to post-purchase engagement. Each one is a moment of contact between customers and a brand, and each one shapes whether that relationship deepens or stalls.</p> <p>These touchpoints are crucial moments that directly influence customer experience. Understanding, optimizing and tracking them is essential for businesses seeking to build strong customer relationships, improve satisfaction&nbsp;and drive sustainable growth.</p> <section class="section main-article-chapter" data-menu-title="What is a customer touchpoint?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is a customer touchpoint?</h2> <p>A&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/definition/customer-touch-point">customer touchpoint</a>&nbsp;is a critical point of interaction between a customer and a business throughout the customer journey. It encompasses every instance where a customer engages with a brand, product or service. These touchpoints can occur through various channels, including:</p> <ul type="disc" class="default-list"> <li>Websites.</li> <li>Phone calls.</li> <li>Email.</li> <li>Social media.</li> <li>Physical stores.</li> <li>Customer service interactions.</li> <li>Advertisements.</li> <li>AI chatbots and virtual assistants.</li> </ul> <p>At each touchpoint, customers form impressions, gather information and make decisions that influence their satisfaction, loyalty and&nbsp;<a href="https://www.techtarget.com/whatis/definition/purchase-intent">purchase intent</a>. Successful businesses recognize the importance of delivering consistent, seamless and valuable experiences across these touchpoints, ensuring customers feel engaged, valued and supported throughout their journey.</p> </section> <section class="section main-article-chapter" data-menu-title="How do customer touchpoints work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How do customer touchpoints work?</h2> <p>Customer touchpoints are the individual interactions that move a buyer from initial awareness to a purchase decision and beyond. Each one is an opportunity for a business to engage, inform or influence. Increasingly, <a href="https://www.techtarget.com/searchenterpriseai/tip/How-AI-personalization-creates-customized-user-experiences">AI-driven personalization</a> is shaping which touchpoints get served to which customers, and when. The sequencing and timing of these moments matters as much as the interactions themselves.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/compliance-touchpoints_for_customer_engagement.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/compliance-touchpoints_for_customer_engagement_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/compliance-touchpoints_for_customer_engagement_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/compliance-touchpoints_for_customer_engagement.png 1280w" alt="Chart depicting six common customer engagement touchpoints." height="213" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Customers can use several channels to interact with businesses before, during and after their purchase. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Effective customer touchpoints align with customer expectations and provide seamless transitions between&nbsp;stages of the journey. They should deliver relevant and valuable information, address customer pain points and offer a consistent brand experience. By orchestrating touchpoints, businesses can nurture customer relationships, build trust and create positive associations with their brand.</p> <p>A well-executed touchpoint can create a memorable experience, leaving a lasting impression that encourages customers to return and recommend the business to others. In contrast, poor or inconsistent touchpoints can lead to customer dissatisfaction, trust erosion and potential business loss. Therefore, businesses must carefully manage and optimize each touchpoint to ensure a cohesive and memorable customer experience.</p> </section> <section class="section main-article-chapter" data-menu-title="The importance of customer touchpoints"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The importance of customer touchpoints</h2> <p>These interactions are significant for businesses, as they play a central role in shaping the customer experience. Customer touchpoints are important for several reasons, including the following:</p> <ul type="disc" class="default-list"> <li><b>Influence perception.</b>&nbsp;Touchpoints can directly affect how a customer perceives a brand, product or service. Positive touchpoints create trust, credibility and a favorable image of the business.</li> <li><b>Build relationships.&nbsp;</b>Touchpoints are crucial for&nbsp;building and nurturing relationships with customers. Each interaction provides an opportunity to engage with customers, understand their needs and deliver personalized experiences. Businesses can foster trust, loyalty and advocacy by providing exceptional touchpoints, leading to repeat purchases and positive word-of-mouth.</li> <li><b>Foster customer satisfaction.&nbsp;</b>Well-designed touchpoints address customer pain points, provide seamless experiences and offer relevant information. Meeting and exceeding expectations at each touchpoint drives satisfaction. Satisfied customers are more likely to remain loyal, make repeat purchases and become brand advocates.</li> <li><b>Drive revenue growth.&nbsp;</b>Optimized touchpoints contribute to increased sales and revenue growth. By delivering exceptional experiences, businesses can differentiate themselves from competitors and attract more customers. Positive touchpoints can lead to higher conversion rates, larger average order values and increased customer lifetime value.</li> <li><b>Enhance customer loyalty.&nbsp;</b>Consistent and positive touchpoints&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/tip/How-to-create-a-customer-loyalty-program-in-9-steps">build customer loyalty</a>. When customers have positive experiences throughout their journey, they are more likely to remain loyal to a brand, resist switching to competitors and become advocates. Loyal customers make repeat purchases and refer new customers, amplifying the business's growth.</li> <li><b>Improve customer retention.&nbsp;</b>Touchpoints play a crucial role in retaining existing customers. By continually engaging and delivering value at each touchpoint, businesses can reduce customer churn and increase customer lifetime value. Keeping customers is more cost-effective than acquiring new ones, making touchpoints before, during and after a sale an essential element of&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/feature/13-customer-retention-strategies-that-work">customer retention strategies</a>.</li> <li><b>Gather customer insight.&nbsp;</b>Every touchpoint generates data. And now AI-powered analytics tools and large language models connected to data sources can synthesize that data across the customer journey in real time. <a href="https://www.techtarget.com/searchbusinessanalytics/definition/opinion-mining-sentiment-mining">Sentiment analysis</a>, behavioral pattern recognition and predictive modeling enable businesses to surface what customers need before they explicitly say it. These insights feed directly into product development, messaging strategy and experience improvements.</li> <li><b>Customer-centric approach.&nbsp;</b>Understanding touchpoints helps businesses become more customer-centric. Businesses can align their touchpoints with customer needs and preferences by analyzing customer interactions.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How to identify and track customer touchpoints"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to identify and track customer touchpoints</h2> <p>Understanding customer touchpoints is crucial for businesses to design effective strategies that enhance customer experiences. By identifying and optimizing touchpoints, organizations can create personalized interactions, address customer needs and exceed expectations.</p> <ul type="disc" class="default-list"> <li><b>Map the customer journey.&nbsp;</b>Begin by&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/tip/How-to-create-a-customer-journey-map-with-template">mapping the customer journey</a>, documenting each stage and touchpoint that customers encounter. This process helps visualize the entire customer experience and identify potential gaps or areas for improvement.</li> <li><b>Utilize analytics tools for data collection.&nbsp;</b>Use analytics tools, such as web analytics platforms,&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/definition/marketing-automation">marketing automation tools</a>&nbsp;or a CRM database to track customer interactions on digital channels. These tools provide data on website visits, page views, click-through rates and conversion rates to help identify key touchpoints. AI-powered revenue intelligence and analytics platforms can layer on top of these systems to identify patterns across touchpoints that manual analysis would miss.</li> <li><b>Monitor social media.&nbsp;</b>Monitor social media platforms to identify customer interactions, mentions and external sentiment toward a brand.&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/definition/social-media-listening">Social listening tools</a>&nbsp;can help track and analyze conversations related to the business, highlighting touchpoints where customers engage and express their opinions.</li> <li><b>Implement customer feedback vehicles.&nbsp;</b>Seek customer feedback at different touchpoints through surveys, feedback forms or follow-up emails. This allows customers to express their experiences and opinions, providing valuable insights into touchpoints that need refinement or enhancement.</li> <li><b>Review sales and conversion funnels.&nbsp;</b>Evaluate data from sales and conversion funnels to identify touchpoints where customers drop off or convert. Understanding these touchpoints helps optimize them to facilitate smooth progression through the customer journey.</li> <li><b>Collaborate across departments.&nbsp;</b>Establish cross-functional collaboration within an organization. Engage marketing, sales, customer service and product development teams to identify and track touchpoints. Their diverse perspectives and insights can contribute to a more comprehensive understanding of customer interactions.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Customer journey touchpoint examples"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Customer journey touchpoint examples</h2> <p>Since customer touchpoints happen throughout the buyer's journey, there are endless examples of where and how these interactions occur. The following are example touchpoints that occur pre-purchase, during and post-purchase.</p> <h3>Pre-purchase touchpoints</h3> <ul type="disc" class="default-list"> <li><b>Online research.</b>&nbsp;Buyers increasingly begin their research through generative AI tools. By querying ChatGPT or Perplexity and perusing Google AI overviews of searched results, buyers can evaluate products before visiting a website. Company websites, product review platforms and comparison sites still remain important touchpoints, but they are often reached later in the research process.</li> <li><b>Social media engagement.</b>&nbsp;Customers may interact with a brand's social media posts, ask questions or seek recommendations from their social network.</li> <li><b>Email marketing.</b>&nbsp;Businesses can use targeted email campaigns to provide product information, offers and incentives to potential customers.</li> <li><b>Advertising.</b>&nbsp;Customers may encounter advertisements through various channels -- such as search engines, social media platforms or display ads -- that generate awareness and interest in a product or service. AI-driven targeting and personalization have made these touchpoints <a target="_blank" href="https://www.stackadapt.com/resources/blog/ai-advertising-targeting" rel="noopener">more precise</a>, serving relevant messages based on behavioral signals rather than broad demographic assumptions.</li> <li><b>In-store visits.</b>&nbsp;For brick-and-mortar businesses, customers may visit physical stores to browse products, ask questions and seek assistance from sales representatives.</li> </ul> <h3>Purchase touchpoints</h3> <ul type="disc" class="default-list"> <li><b>Website or app checkout.</b>&nbsp;Customers go through the checkout process on a website or mobile app to complete their purchase, including adding items to the cart, entering payment information and confirming the order.</li> <li><b>Point-of-sale (POS) interaction.</b>&nbsp;In a physical retail environment, customers interact with the POS system to finalize their purchase, make payment and receive their product.</li> <li><b>Customer service support.</b>&nbsp;Customers may contact customer service representatives for help during the purchase process to clarify product details, confirm availability or resolve any issues.</li> </ul> <h3>Post-purchase touchpoints</h3> <ul type="disc" class="default-list"> <li><b>Order confirmation and delivery updates.</b>&nbsp;Customers receive order confirmation emails or notifications with details about their purchase and updates on the delivery status of their product.</li> <li><b>Customer onboarding.</b>&nbsp;For certain products or services, businesses may provide onboarding materials or tutorials to guide customers on how to best use and maximize the benefits of their purchase. AI-powered onboarding tools -- including interactive walkthroughs, chatbot-guided setup and personalized in-app prompts triggered by user behavior -- have made this touchpoint more adaptive and less reliant on static documentation.</li> <li><b>Customer surveys.</b>&nbsp;Companies may send&nbsp;<a href="https://www.techtarget.com/searchcustomerexperience/feature/5-tips-for-deploying-surveys-and-collecting-customer-feedback">post-purchase surveys</a>&nbsp;to gather feedback on the experience, product satisfaction and any areas for improvement. AI sentiment analysis tools can complement or replace traditional surveys, processing feedback signals from support tickets, reviews and product usage data to surface patterns at a scale that manual review cannot match.</li> </ul> <p>The customer journey has never been a straight line, and the number of touchpoints buyers encounter before and after a purchase continues to grow. Businesses that map, measure and actively optimize these interactions are most likely to build customer relationships that compound over time.</p> <p><i>Griffin LaFleur is a RevOps and GTM Engineering leader at Granite GTM, where he works with B2B technology companies on go-to-market strategy, systems architecture and revenue operations.</i></p> </section> Customer journey touchpoints enable businesses to create excellent customer experience and drive long-lasting customer loyalty -- if understood and optimized properly. https://cdn.ttgtmedia.com/rms/onlineimages/customer_service11.jpg https://www.techtarget.com/searchcustomerexperience/tip/Why-customer-journey-touchpoints-matter Wed, 29 Apr 2026 10:00:00 GMT <p>Salesforce today released Agentforce Operations, a bundle of agents designed to automate back-office tasks across multiple applications, including spreadsheets and email.</p> <p>Agentforce Operations includes out-of-the-box agents that perform tasks such as extracting data from complex documents or identifying compliance gaps. Also, it comes with <a href="https://www.techtarget.com/searchitoperations/definition/What-is-workflow-orchestration">workflow orchestration</a> based on a "blueprint" metaphor that ingests documents such as lists, tables and spreadsheets that describe manual processes and -- with generative AI interpreting plain language -- devises automations that take on tasks such as acquiring data and getting approvals to move a task along and sidestep bottlenecks when they were done manually.</p> <p>The features are built from Regrello, a startup Salesforce acquired late last year. While Regrello came from -- and continues to specialize in -- manufacturing ERP integrations and automations, Salesforce plans to cross-pollinate Agentforce Operations across industries, with some prebuilt agentic blueprints for common supply chain processes -- and potentially more to come -- for verticals such as insurance, healthcare and financial services.</p> <p>Salesforce has workflow automation already through <a href="https://www.techtarget.com/searchcustomerexperience/news/252522135/Salesforce-users-get-more-low-code-automation-including-RPA">MuleSoft RPA </a>and features such as Salesforce Flow. But those last-generation tools, in theory, require more maintenance and developer bandwidth to keep up to date than new agentic AI features.</p> <p>Furthermore, said Sanjna Parulekar, senior vice president of product marketing at Salesforce, Agentforce Operations can take on more complex workflows that might be broken down into more steps than those optimized with current tools.</p> <p>"You might go from a 10-step process to a 50-step process, but it's more efficient because you have agents working for you," Parulekar said.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/agentforce_operations_product_screen-f.jpg"> <img data-src="https://www.techtarget.com/rms/onlineimages/agentforce_operations_product_screen-f_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/agentforce_operations_product_screen-f_mobile.jpg 960w,https://www.techtarget.com/rms/onlineimages/agentforce_operations_product_screen-f.jpg 1280w" alt="Salesforce workflow orchestration tool Agentforce Operations screenshot" data-credit="Salesforce" height="313" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Agentforce Operations automates back-office workflow orchestration with a plain-language interface and without code. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>A host of other companies currently are enticing Salesforce users to automate mixed deterministic and probabilistic workflows with generative AI, including <a href="https://www.techtarget.com/searchitoperations/tip/Task-automation-tools-to-increase-productivity">Zapier</a> and <a href="https://www.techtarget.com/searchcio/opinion/OpenClaw-Moving-the-perimeter-to-the-reasoning-boundary">OpenClaw,</a> which are often used together. Pegasystems has an AI workflow builder product, <a href="https://www.techtarget.com/searchcustomerexperience/news/366639857/Pegasystems-adds-vibe-coding-to-Blueprint-app-builder">also named Blueprint</a>, that enables line-of-business users to create apps by applying business rules to agentic AI outputs.</p> <p>It also did not escape the notice of Rebecca Wettemann, founder of independent research firm Valoir, that Salesforce dropped Agentforce Operations prior to ServiceNow’s user conference, ServiceNow Knowledge, being held May 5-7 in Las Vegas. ServiceNow might be Salesforce's biggest competitor of all for enterprise technology buyers' workflow automation budgets; the two are battling on multiple fronts, including customer service, <a href="https://www.techtarget.com/searchcustomerexperience/news/366632554/Salesforce-rolls-into-ITSM-with-Slack-based-agentic-AI-platform">ITSM</a>, <a href="https://www.techtarget.com/searchcustomerexperience/news/366623581/ServiceNow-rolls-into-Salesforce-territory-with-CRM-agentic-AI">CRM</a> and <a href="https://www.techtarget.com/searchitoperations/news/366639250/ServiceNow-touts-AI-governance-for-its-Autonomous-Workforce">agentic orchestration</a>.</p> <p>"As ServiceNow talks more and more about 'CRM being broken' and going to head-to-head with Salesforce, Salesforce needs a stronger back-office story," Wettemann said. "This gives them that."</p> <p>The Regrello acquisition also gives Salesforce users agentic AI hooks into <a href="https://www.techtarget.com/searcherp/tip/Learn-why-ERP-data-quality-is-important">ERP data</a>. It can be done with the original Agentforce tools -- but can be a struggle for many customers, Wettemann added. Regrello's technology can potentially speed time-to-value for Salesforce customers working with agents that integrate with ERP systems.</p> <p>Agentforce Operations is available today and was released in conjunction with the <a href="https://www.salesforce.com/events/world-tour/nyc/">Salesforce Agentforce World Tour New York</a> marketing event.</p> <p><i>Don Fluckinger is a senior news writer for Informa TechTarget. He covers customer experience, digital experience management and end-user computing. Got a tip? </i><a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article" target="_blank" rel="noopener"><i>Email him</i></a><i>.</i></p> Agent bundle, with some vertical-industry customizations, reaches across back-office applications to automate processes. https://cdn.ttgtmedia.com/rms/onlineimages/folder-files11.jpg https://www.techtarget.com/searchcustomerexperience/news/366642340/Agentforce-Operations-tackles-workflow-orchestration Wed, 29 Apr 2026 08:00:00 GMT 60 webmaster@techtarget.com