Key Metrics for Understanding Customer Expectations

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 👇

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!

The SLA report says green. The users say, “IT dropped the ball.” So… who’s right? If you’re only measuring tickets, you’re missing the moment expectations broke. Here are the top 5 metrics Grove Teams use to expose the real disconnects—before they escalate: 1. Expectation Gap Score ↳ Measures the difference between what users expected and what they actually experienced. 2. % of Missed Expectations ↳ Shows how often users felt let down—even when everything looked “on time” in the dashboard. 3. Root Cause of Expectation Failures ↳ It’s not enough to know something went wrong. ↳ This shows which failures caused the most damage to trust. 4. SLA vs. Satisfaction Delta ↳ A high SLA and low CSAT? ↳ You’re measuring what’s easy—not what matters. 5. Proactive vs. Reactive Recovery Rate ↳ Fixing is reactive.  ↳ But preventing is respected. 📌 This isn’t about vanity metrics. It’s about visibility. If your team keeps getting blindsided by escalations, start measuring what breaks expectations—not just what breaks systems. 💬 If you only had 1 slide to justify your team’s budget, which metric would be on it? 🔁 Repost if you're done guessing why users are upset. 🔔 Follow Bob Roark for Grove-style leadership that turns chaos into clarity. ✶✶✶✶✶✶ Grove Method for ITSM Excellence Find it in my Featured/About section or search “Grove Method ITSM” on Amazon ✶✶✶✶✶✶

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

I used to think I was measuring customer loyalty the right way. Every quarter, I’d report out our NPS score, and every quarter, I’d get the same pushback from leadership: “If our NPS is so high, why are sales down?” “If customers love us, why is churn up?” And honestly? I didn’t have a good answer. I felt dejected as I could feel my credibility and social capital with the execs slip away. I was stuck in the CX trap of measuring advocacy, not behavior. NPS told me customers said they’d recommend us—but it told me nothing about whether they’d actually buy from us again. The lightbulb moment came when I stopped chasing how much customers liked us and started tracking how much they actually spent. That’s when I realized: Loyalty isn’t a feeling. It’s a behavior. So, I pivoted. Instead of leading with NPS, I built our CX strategy around three core metrics that actually predict revenue: 🔺 Likelihood to Purchase Again (Intent) – Are they signaling they’ll come back? 🔺 Repeat Purchase Rate (Behavioral) – Are they actually returning? 🔺 Time to Repeat Purchase (Behavioral) – How long does it take? And guess what happened? 💡 Our CX efforts finally had credibility in the boardroom. When we improved post-purchase experience, I could prove it led to faster repeat purchases. 💡 Marketing and Finance finally saw CX as a growth lever. Instead of reporting on ‘customer happiness,’ I was driving revenue conversations. 💡 We made better investments. Instead of obsessing over ‘improving NPS,’ we focused on shortening the time to second purchase—and sales shot up. The reality is: NPS won’t save you when revenue is down. If you want to be taken seriously as a CX leader, you have to connect the dots between emotion, intent, and action. It’s time to stop measuring how much customers like you and start measuring how much they buy from you. If you’ve had this realization too, let’s talk. Let’s get your CX unf*cked.