Identifying Key Customer Experience Metrics

Over the last year, I’ve seen many people fall into the same trap: They launch an AI-powered agent (chatbot, assistant, support tool, etc.)… But only track surface-level KPIs — like response time or number of users. That’s not enough. To create AI systems that actually deliver value, we need 𝗵𝗼𝗹𝗶𝘀𝘁𝗶𝗰, 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 that reflect: • User trust • Task success • Business impact • Experience quality    This infographic highlights 15 𝘦𝘴𝘴𝘦𝘯𝘵𝘪𝘢𝘭 dimensions to consider: ↳ 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 — Are your AI answers actually useful and correct? ↳ 𝗧𝗮𝘀𝗸 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲 — Can the agent complete full workflows, not just answer trivia? ↳ 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 — Response speed still matters, especially in production. ↳ 𝗨𝘀𝗲𝗿 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 — How often are users returning or interacting meaningfully? ↳ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗥𝗮𝘁𝗲 — Did the user achieve their goal? This is your north star. ↳ 𝗘𝗿𝗿𝗼𝗿 𝗥𝗮𝘁𝗲 — Irrelevant or wrong responses? That’s friction. ↳ 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗗𝘂𝗿𝗮𝘁𝗶𝗼𝗻 — Longer isn’t always better — it depends on the goal. ↳ 𝗨𝘀𝗲𝗿 𝗥𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 — Are users coming back 𝘢𝘧𝘵𝘦𝘳 the first experience? ↳ 𝗖𝗼𝘀𝘁 𝗽𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 — Especially critical at scale. Budget-wise agents win. ↳ 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝘁𝗵 — Can the agent handle follow-ups and multi-turn dialogue? ↳ 𝗨𝘀𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 𝗦𝗰𝗼𝗿𝗲 — Feedback from actual users is gold. ↳ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 — Can your AI 𝘳𝘦𝘮𝘦𝘮𝘣𝘦𝘳 𝘢𝘯𝘥 𝘳𝘦𝘧𝘦𝘳 to earlier inputs? ↳ 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 — Can it handle volume 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 degrading performance? ↳ 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 — This is key for RAG-based agents. ↳ 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗰𝗼𝗿𝗲 — Is your AI learning and improving over time? If you're building or managing AI agents — bookmark this. Whether it's a support bot, GenAI assistant, or a multi-agent system — these are the metrics that will shape real-world success. 𝗗𝗶𝗱 𝗜 𝗺𝗶𝘀𝘀 𝗮𝗻𝘆 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗼𝗻𝗲𝘀 𝘆𝗼𝘂 𝘂𝘀𝗲 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀? Let’s make this list even stronger — drop your thoughts 👇

Surveys can serve an important purpose. We should use them to fill holes in our understanding of the customer experience or build better models with the customer data we have. As surveys tell you what customers explicitly choose to share, you should not be using them to measure the experience. Surveys are also inherently reactive, surface level, and increasingly ignored by customers who are overwhelmed by feedback requests. This is fact. There’s a different way. Some CX leaders understand that the most critical insights come from sources customers don’t even realize they’re providing from the “exhaust” of every day life with your brand. Real-time digital behavior, social listening, conversational analytics, and predictive modeling deliver insights that surveys alone never will. Voice and sentiment analytics, for example, go beyond simply reading customer comments. They reveal how customers genuinely feel by analyzing tone, frustration, or intent embedded within interactions. Behavioral analytics, meanwhile, uncover friction points by tracking real customer actions across websites or apps, highlighting issues users might never explicitly complain about. Predictive analytics are also becoming essential for modern CX strategies. They anticipate customer needs, allowing businesses to proactively address potential churn, rather than merely reacting after the fact. The capability can also help you maximize revenue in the experiences you are delivering (a use case not discussed often enough). The most forward-looking CX teams today are blending traditional feedback with these deeper, proactive techniques, creating a comprehensive view of their customers. If you’re just beginning to move beyond a survey-only approach, prioritizing these more advanced methods will help ensure your insights are not only deeper but actionable in real time. Surveys aren’t dead (much to my chagrin), but relying solely on them means leaving crucial insights behind. While many enterprises have moved beyond surveys, the majority are still overly reliant on them. And when you get to mid-market or small businesses? The survey slapping gets exponentially worse. Now is the time to start looking beyond the questionnaire and your Likert scales. The email survey is slowly becoming digital dust. And the capabilities to get you there are readily available. How are you evolving your customer listening strategy beyond traditional surveys? #customerexperience #cxstrategy #customerinsights #surveys

CSAT measurement must be more than just a score. Many companies prioritize their Net Promoter Score (NPS) as a measure of Customer Satisfaction (CSAT). But do these methods truly give us a complete understanding? In reality, surveys are not always accurate. Bias can influence the results, ratings may be misinterpreted, and there's a chance that we didn't even ask the right questions. While a basic survey can indicate problems, the true value lies in comprehending the reasons behind those scores and identifying effective solutions to improve them. Here’s a better way to look at CSAT: 1. Start with Actions, Not Just Scores: Observable behaviors like repeat purchases, referrals, and product usage often tell a more accurate story than a survey score alone. 2. Analyze Digital Signals & Employee Feedback: Look for objective measures that consumers are happy with what you offer (website micro-conversions like page depth, time on site, product views and cart adds). And don’t forget your team! Happy employees = Happy customers. 3. Understand the Voice of the Customer (VoC): Utilize AI tools to examine customer feedback, interactions with customer support, and comments on social media platforms in order to stay updated on the current attitudes towards your brand. 4. Make It a Closed Loop: Gathering feedback is only the beginning. Use it to drive change. Your customers need to know you’re listening — and *acting*. Think of your CSAT score as a signal that something happened in your customer relationships. But to truly improve your business, you must pinpoint the reasons behind those scores and use that information to guide improvements. Don’t settle for simply knowing that something happened, find an answer for why it happened. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

If you’re still building your CS dashboard around CSAT and NPS (and half a dozen other typical metrics), you're not leading — you’re looking in the rearview mirror. 💥 Real talk: As we've been discussing for almost 2 years, Customer Success is no longer the renewals safety net. It’s a revenue-generating, margin-conscious, outcome-driving machine. But most teams are still measuring it like it’s 2022. That’s a leadership gap — and it starts with us. 📊 What should we be measuring instead? 🔹 Adoption Depth: How broadly — and how strategically — are customers engaging across their org? 🔹 Expansion Efficiency: What’s the ratio of post-sales revenue to incremental investment? 🔹 Time-to-First-Value Velocity: Speed to impact isn’t a nice-to-have. It’s a competitive advantage. CSAT and NPS still matter — but they’re lagging indicators. They can’t be the headline. 💬 To my fellow CCOs and CS leaders: What’s one metric you’ve added in the last 12–18 months that’s changed how your org operates? I’ll share mine in the comments 👇 Would love to hear yours.

Design metrics shape decisions and lead to better business results. We're getting closer to launching Helio Glare, our open data-informed design framework. A key focus is connecting design metrics to business results. In it, we show you how to use a design metrics tree built with UX metrics. This structures how UX metrics influence broader product and business outcomes. Here’s how it connects: UX metrics as the foundation ↳ UX metrics like desirability, comprehension, usefulness, sentiment, usability, and success act as the leaves of the metrics tree. These represent the measurable aspects of user experience that indicate how well a design performs in terms of user perception, interaction, and effectiveness. Design initiatives as the branches ↳ Concept areas bridge UX metrics and product performance. These represent specific design initiatives: changes, optimizations, or experiments in design that are directly influenced by UX metric insights. Example: If usability scores are low, a design initiative might focus on streamlining navigation or reducing cognitive load. If desirability is lacking, the initiative could involve refining branding elements or UI aesthetics. Product metrics as the trunk ↳ Product metrics are most impactful with multiple design initiatives. They measure how well these initiatives contribute to product success, such as engagement rates, task completion, or feature adoption. Business metrics as the roots ↳ Business metrics ground the design work in measurable business outcomes like revenue, retention, conversion rates, or customer lifetime value (CLV). Great user experiences make products perform better, which leads to business success. A well-structured design metrics tree connects UX efforts to business goals. Design metric trees help teams: → Focus on UX improvements that drive business results → Show why investing in design makes business sense → Continuously improve design by measuring UX We’ve found this approach especially useful for teams to align design with business strategy. We use Helio to collect metrics and ensure the design isn’t just about looks—it’s measurable, impactful, and supports business growth. As Jodah Jensen shared with me, "we’re actually prompting the business to define what success looks like in the first place." #productdesign #productdiscovery #userresearch #uxresearch

Leaders, Stop Letting Your CX Metrics Get Ignored! Here is when it all changed for me, when the CEO looked me straight in the eyes and asked this one question: “What does this have to do with the business?” In that moment, I realized I wasn’t speaking the language of the business—I was just presenting numbers without a real story. I made a decision that day: I would never show up with “insights” again unless I could tie them to revenue, cost, or risk. Here’s why this mindset shift is critical: ✅ Execs care about impact, not just insights (but, always remember to keep the human in the process!) ✅ You need to connect customer, employee, or patient experience to the bottom line ✅ Without a business case, you’re just adding noise, not value Here’s how to lead like you really want to impact the top or bottom line: ✅ Stop leading with CX metrics—tie every number to financial outcomes ✅ Translate customer pain into operational costs and revenue opportunity ✅ Become the internal influencer your business can’t ignore This isn’t just theory or a framework. It’s the approach I’ve used for years, and I've always been able to get the resources I needed. Your Experience Evangelist, Shawn Follow ➡ #experienceevangelist ♻️ Repost to help your network. 🔔 Follow Shawn Nason to learn more on authentic, heart-centered leadership and transformative customer experiences. #whatinspiresme #happiness #bestadvice #inspiration #motivation #leadership #transformation #cx #customerexperience #innovation —— 📌 PS – If you're ready to lead with more heart, grit, and fire, hit “Subscribe” to Experience Matters in the feature section, and join 68,000+ others on the journey.

The customer support team hit every KPI last quarter. 99.2% CSAT. 2.3 minute average handle time. 94% first-call resolution. The CEO said "exceptional performance!" Then I read the actual tickets: Ticket #47291: Customer called about wedding catering delivery that never showed. 150 guests. No food. Reception ruined. Support response: "Sorry for the inconvenience. Here's a full refund and 20% off your next order." Ticket closed in 90 seconds. Satisfaction survey: 5 stars. Metrics: Perfect. But here's what the dashboard couldn't measure: That couple will never use our service again. They'll tell this story at every dinner party for the next decade. Their friends will choose the competitors. The reality: One "perfectly handled" ticket. Lifetime value lost: $12,000. Word-of-mouth damage: Immeasurable. I started digging deeper into other "high-performing" tickets. Found dozens of these stories hidden behind green metrics. A birthday party disaster marked as "resolved." A business meeting catastrophe labeled "satisfied customer." Anniversary dinner failure tagged "case closed." Each one a perfect score in our system. All of them a brand-damaging story in real life. Yesterday, someone watched Sarah from the support team handle a similar call. Customer: "The flowers for my mom's funeral never arrived." Sarah didn't offer a refund. Sarah didn't close the ticket in 90 seconds. Instead, she said: "I'm going to personally make sure we get flowers to the service. What was your mom's favorite color?" Handle time: 18 minutes. Resolution metrics: Failed. Customer retention: Guaranteed for life. We're measuring efficiency when we should be measuring empathy. Tracking speed when we should be tracking stories. The best customer support doesn't show up in quarterly reports. It shows up in customer conversations five years later.

As CX programs are being cut, it’s becoming clear that those focused solely on survey scores are at risk. To truly drive value, B2B CX programs must tie their efforts to financial outcomes—a critical connection many programs miss. One simple but powerful metric to consider is order velocity—the frequency of customer orders, regardless of size or type. By combining the order data with good survey questions, you can track how improved customer experiences lead to faster order velocity. While it’s not the final financial metric, it gives you an early indication of CX impact. Order velocity works especially well in industries with less frequent transactions, like B2B insurance. For example, if brokers typically average six policies yearly, an improved experience should lead to more orders the following year. If not, it could signal that your surveys aren’t targeting the right issues or that other factors, like pricing, are having a larger impact. Remember, there’s often a delay between shifts in customer attitudes and changes in behavior. In industries like health insurance, a boost in CX scores during mid-year could drive more orders by Q4. In manufacturing, the timeline might vary—tactical orders may rise quickly, while long-term sales like turbines could take years to reflect the change. For a more holistic view, pair order velocity with client-specific metrics like margin per client or number of categories ordered. Order velocity is relatively easy to track and is a great entry point for deeper insights. Reporting on this invites questions from leadership—and when the right questions are asked, it paves the way for gathering more valuable data. #CX #CXROI #Customerexperience

UX metrics work best when aligned with the right questions. Below are ten common UX scenarios and the metrics that best fit each. 1. Completing a Transaction When the goal is to make processes like checkout, sign-up, or password reset more efficient, focus on task success rates, drop-off points, and error tracking. Self-reported metrics like expectations and likelihood to return can also reveal how users perceive the experience. 2. Comparing Products For benchmarking products or releases, task success and efficiency offer a baseline. Self-reported satisfaction and emotional reactions help capture perceived differences, while comparative metrics provide a broader view of strengths and weaknesses. 3. Frequent Use of the Same Product For tools people use regularly, like internal platforms or messaging apps, task time and learnability are essential. These metrics show how users improve over time and whether effort decreases with experience. Perceived usefulness is also valuable in highlighting which features matter most. 4. Navigation and Information Architecture When the focus is on helping users find what they need, use task success, lostness (extra steps taken), card sorting, and tree testing. These help evaluate whether your content structure is intuitive and discoverable. 5. Increasing Awareness Some studies aim to make features or content more noticeable. Metrics here include interaction rates, recall accuracy, self-reported awareness, and, if available, eye-tracking data. These provide clues about what’s seen, skipped, or remembered. 6. Problem Discovery For open-ended studies exploring usability issues, issue-based metrics are most useful. Cataloging the frequency and severity of problems allows you to identify pain points, even when tasks or contexts differ across participants. 7. Critical Product Usability Products used in high-stakes contexts (e.g., medical devices, emergency systems) require strict performance evaluation. Focus on binary task success, clear definitions of user error, and time-to-completion. Self-reported impressions are less relevant than observable performance. 8. Designing for Engagement For experiences intended to be emotionally resonant or enjoyable, subjective metrics matter. Expectation vs. outcome, satisfaction, likelihood to recommend, and even physiological data (e.g., skin conductance, facial expressions) can provide insight into how users truly feel. 9. Subtle Design Changes When assessing the impact of minor design tweaks (like layout, font, or copy changes), A/B testing and live-site metrics are often the most effective. With enough users, even small shifts in behavior can reveal meaningful trends. 10. Comparing Alternative Designs In early-stage prototype comparisons, issue severity and preference ratings tend to be more useful than performance metrics. When task-based testing isn’t feasible, forced-choice questions and perceived ease or appeal can guide design decisions.

The MOST critical metric you can use to measure customer satisfaction: (This changed everything for my company) We had a daily deal site with 2 million users. Sounds great, right? But about 18 months in we had a massive problem: → Customer satisfaction was TANKING (we were in the daily-deals business, largest Groupon competitor) Why? Our customers weren't getting the same experience as full-paying customers. They were treated as “coupon buyers”, so they: - Had long wait-times - Didn't get the same food - Got given the cr*ppy tables at the back They went for the full service and they got very low-quality service. And it was KILLING our business model. We tried everything - customer service calls, merchant meetings, forums. Nothing worked. Then I learned about NPS (Net Promoter Score) at EO and MIT Masters. It was an ABSOLUTE revelation. NPS isn't a boring survey asking "How happy are you with our service?" It's way more powerful. It asks, on a simple scale of 0-10: → "How likely are you to recommend this service to a friend or colleague?" 10-9 → Promoters (Nice!) 8-7 → Passive (no need to do anything) 6-0 → Detractors (fix this NOW) It’s such a simple shift on our end and so easy to respond on the customer end: “Hey, would you recommend me or not, out of 10?” “Hm, 7.” “Ok, thank you” — that’s it. Simple reframe, massive impact. We implemented it immediately. But here's the real gold: → We contacted everyone (one-on-one customer service) who used our service and provided a NPS score. They scored us less than 6? - Give them gift cards - Interview them to make them feel heard - Do ANYTHING to flip detractors into promoters Because if they’re scoring you less than 6, they’re actually HARMING your business. These are going to be like e-brakes in your company. NPS became our most important metric, integrated into everything we did. The results? - Improved customer satisfaction - Increased repeat business and customer LTV - Lower CAC (because happy customers = free marketing) - Higher AOV (people were willing to spend more) But it's not just about the numbers. It's about understanding WHY people aren't recommending you and fixing it fast. (Another great feature is that people can also add comments to get some real feedback, but just using the number is POWERFUL). If you're not using NPS, stop what you're doing and implement it tonight. Seriously. And if you are already using it? Double down on those 0-6 scores. Turning your detractors into promoters is where the real growth potential lies. Remember: in business, what gets measured gets managed. And NPS is the ultimate measure of how satisfied your customers REALLY are. So, what's your score? — Found value in this? Repost ♻️ to share to your network and follow Ignacio Carcavallo for more like this!