Analyzing Customer Experience Metrics for Continuous Improvement

Crowning a New Term: “Iceberg Metrics” 🧊 ✨ I’m calling it: Iceberg Metrics represent KPIs that only reveal the tip of what’s really happening below the surface. Metrics like abandoned carts seem simple but often mask much more—checkout friction, hidden costs, trust issues, and more. To truly understand and optimize, we need to dig deeper. Here’s how to dive into the “iceberg” of abandoned cart rates: 1. Establish Baseline Metrics: Start by gathering data on current abandoned cart rates, session times, and bounce rates using heat maps and session recordings to see where users drop off. 2. Segment the Audience: Analyze users by behavior (first-time vs. repeat visitors, mobile vs. desktop) and traffic source (organic, paid, email). 3. Experiment Hypotheses: Develop hypotheses for abandonment reasons—shipping costs, checkout friction, distractions, or lack of trust signals—and test them. 4. Run A/B Tests: Test variations like simplifying the checkout process, showing shipping costs earlier, adding trust badges, or retargeting abandoned cart emails. 5. Use Heat Maps & Session Recordings: Examine user behavior in real time. Look for confusion or hesitation, where users hover, and whether they engage with key information. 6. Contextualize Results: Analyze how changes impact overall user flow. Did simplifying checkout help, or did other metrics like bounce rate increase? 7. Ecosystem Approach: Examine how tweaks affect the full journey—from product discovery to checkout—balancing short-term improvements with long-term goals like lifetime value. 8. Iterate: Refine solutions based on experiment findings and continuously optimize the customer journey. This one’s mine, folks! #IcebergMetrics #OwnIt #DataDriven #EcommerceOptimization #NewMetricAlert Cheers, Your cross-legged CAC and CLV buddy 🤗

So, how much did being genuinely nice to our customers earn us this quarter? Now imagine asking this question to your CFO. Today we are well aware and sometimes even obsessed with metrics: NPS, CSAT, churn rates…all perfectly calculated. But translating the warmth of customer happiness into cold, hard financial results? Well, that's not so simple. After all, it is not easy to connect a ‘smiling support rep’ to ‘higher EBIT’. However, the truth bomb here - Top CX performers consistently outperform their competitors. But the magic they create is not just in making customers smile. It is about connecting every delighted customer with revenue, retention, and even willingness to pay a little extra. The question for us to answer is - Are we connecting dots, or just coloring the margins? As business leaders, are we digging deep enough? What would happen if CX was tagged to every financial review, not just a customary part of the annual presentation? You could be walking into your next review, armed with not just satisfaction scores, but a clear graph of what those scores added to the bottom line. If you think ROI from customer experience is not just fairy dust, then here are 4 metrics to add gravitas to your next board meeting: ☘️ C - Customer Retention Track repeat purchase rate/ renewal rate. Know how many customers come back. Even a 5% increase in retention can boost profits considerably. ☘️ T - Ticket Size Happier customers spend more. We all do that. Measure if your CX improvements lead to higher average order value. ☘️ S - Share of Voice Delighted customers talk. Track organic referrals, online reviews and social media mentions. Don't forget - word of mouth reduces marketing costs. ☘️ S - Service Cost Zero-effort experiences reduce complaints and rework. When customers don't need to call back, your cost to serve drops. Measure cost per support ticket and first contact resolution rate. These may not happen in a day, but start somewhere. One step of transition a day leads to transformation over a quarter or a year. Let’s get past the vanity metrics and start making CX pay its own bills. About time no? #cx #customerexperience #serviceexcellence

A critical part of journey management in any large organisation is measuring how your journeys perform. 📊 By setting clear goals, monitoring performance, identifying gaps, and measuring improvement impact, you create a continuous cycle of management and enhancement. Measurement surfaces opportunities and kickstarts improvements. 🚀 Yet many organisations struggle: data sits in silos, teams measure inconsistently, and dashboards report numbers without a coherent story. Product, marketing, sales, service, and digital teams collect valuable insights, but without a common language, they never combine into a unified performance view. The result? Plenty of activity, little clarity on what actually improves customer experience and business performance. Measuring performance along specific journeys—rather than isolated KPIs—provides the right context: the journey itself. 🗺️ This approach transforms your journey framework into an engine for improving both customer experience and business performance holistically, creating a shared structure and language where different KPIs unite. 🧭 Inspired by the Balanced Scorecard, this pragmatic 3x3 Matrix structures performance measurement across two dimensions: 👉 First, it distinguishes 3 performance metric categories: - Customer performance (behavior and sentiment) - Commercial performance (conversion, customer base, revenue) - Operational performance (cost, efficiency, reliability) 👉 Second, it distinct three journey hierachy levels: - Overall customer lifecycle - End-to-end product or service journey - Individual customer tasks These intersecting dimensions ensure each metric sits logically within a complete, coherent view. The visual below shows example metrics for all nine sections, helping you build a balanced measurement framework for journeys. This matrix delivers three immediate benefits: ✨ 1. It aligns siloed KPIs and contextualizes them into a shared journey 2. It enables drill-down and aggregation through connected KPIs across journey levels 3. It surfaces trade-offs and synergies between performance metrics A few quick tips to take into account when drafting or structuring your own journey-driven measurement framework 👇👇👇 🐌 Consider both leading and lagging indicators for a robust measurement approach that balances early warning signs with outcome metrics.  🤲 Don’t collect everything. Start with a North Star KPI for each journey, and add a small set of supporting metrics. Less is more. 💬 Always mix performance metrics with more qualitative feedback and insights that will help you determine why performance is down and how to fix it. Happy measuring! 🎉

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.

How many customers did we make work too hard today? I've sat in hundreds of CX leadership meetings over three decades. We dissect CSAT scores. We analyze call handle times. We celebrate cost-per-contact reductions. But I've rarely heard anyone ask: "How much unnecessary effort did we create for our customers this week?" Here's why that question matters more than your NPS: A customer can rate you 8/10 and still switch because interacting with you feels like work. They got their issue resolved (high satisfaction), but they had to: Repeat information three times Navigate a confusing IVR Explain their problem to multiple people Follow up twice to confirm it was actually fixed Resolution? Yes. Loyalty-building experience? Not even close. Stop optimizing for internal efficiency metrics and start measuring customer effort. Not through surveys asking "was this easy?"—through actual analysis of where customers struggle, pause, repeat themselves, or give up. Because effort is the silent killer of loyalty. And most companies don't even know they're creating it. If you removed one step from your most common customer journey tomorrow, what would it be? . . . #CustomerExperience #CXLeadership #CustomerEffort #CXStrategy #CXTransformation

🔎 UX Metrics: How to Measure and Optimize User Experience? When we talk about UX, we know that good decisions must be data-driven. But how can we measure something as subjective as user experience? 🤔 Here are some of the key UX metrics that help turn perceptions into actionable insights: 📌 Experience Metrics: Evaluate user satisfaction and perception. Examples: ✅ NPS (Net Promoter Score) – Measures user loyalty to the brand. ✅ CSAT (Customer Satisfaction Score) – Captures user satisfaction at key moments. ✅ CES (Customer Effort Score) – Assesses the effort needed to complete an action. 📌 Behavioral Metrics: Analyze how users interact with the product. Examples: 📊 Conversion Rate – How many users complete the desired action? 📊 Drop-off Rate – At what stage do users give up? 📊 Average Task Time – How long does it take to complete an action? 📌 Adoption and Retention Metrics: Show engagement over time. Examples: 📈 Active Users – How many people use the product regularly? 📈 Churn Rate – How many users stop using the service? 📈 Cohort Retention – What percentage of users remain engaged after a certain period? UX metrics are more than just numbers – they tell the story of how users experience a product. With them, we can identify problems, test hypotheses, and create better experiences! 💡🚀 📢 What UX metrics do you use in your daily work? Let’s exchange ideas in the comments! 👇 #UX #UserExperience #UXMetrics #Design #Research #Product

📊 If your CX metrics don’t change decisions, they don’t matter. Most organizations are measuring customer experience. Very few are managing it. ⚠️ We collect NPS, CSAT, CES, health scores, retention rates… Then we admire the dashboards. 👀 And go right back to doing the same things. 🔁 That’s not strategic CX. That’s low-level reporting. 🧾 A metric only earns its place if it answers one question: ❓ “What decision will this force us to make differently?” If a score goes down and: • 🚫 No leader is accountable • 💸 No investment is reprioritized • 🛠️ No process is redesigned • 🧠 No behavior changes Then the metric is might as well be corporate wallpaper. 🖼️ Real CX management looks different: ✅ Metrics are owned, not observed ➡️ Every score is tied to a decision, action, or tradeoff 🧭 Leadership debates what to change, not why the number moved 🎯 Teams know exactly what they control—and what they don’t Measurement tells you what happened. 📈 Management determines what happens next. 🚀 Until CX metrics drive decisions with real consequences, they aren’t indicators of experience. They’re indicators of comfort. 🛋️ 🤔 If your metrics disappeared tomorrow, would your decisions change? If not, that’s your answer. #CustomerExperience #CustomerSuccess #CXLeadership #CXTransformation #MetricsThatMatter