Measuring trust and satisfaction in digital platforms

Ever looked at a UX survey and thought: “Okay… but what’s really going on here?” Same. I’ve been digging into how factor analysis can turn messy survey responses into meaningful insights. Not just to clean up the data - but to actually uncover the deeper psychological patterns underneath the numbers. Instead of just asking “Is this usable?”, we can ask: What makes it feel usable? Which moments in the experience build trust? Are we measuring the same idea in slightly different ways? These are the kinds of questions that factor analysis helps answer - by identifying latent constructs like satisfaction, ease, or emotional clarity that sit beneath the surface of our metrics. You don’t need hundreds of responses or a big-budget team to get started. With the right methods, even small UX teams can design sharper surveys and uncover deeper insights. EFA (exploratory factor analysis) helps uncover patterns you didn’t know to look for - great for new or evolving research. CFA (confirmatory factor analysis) lets you test whether your idea of a UX concept (say, trust or usability) holds up in the real data. And SEM (structural equation modeling) maps how those factors connect - like how ease of use builds trust, which in turn drives satisfaction and intent to return. What makes this even more accessible now are modern techniques like Bayesian CFA (ideal when you’re working with small datasets or want to include expert assumptions), non-linear modeling (to better capture how people actually behave), and robust estimation (to keep results stable even when the data’s messy or skewed). These methods aren’t just for academics - they’re practical, powerful tools that help UX teams design better experiences, grounded in real data.

AI changes how we measure UX. We’ve been thinking and iterating on how we track user experiences with AI. In our open Glare framework, we use a mix of attitudinal, behavioral, and performance metrics. AI tools open the door to customizing metrics based on how people use each experience. I’d love to hear who else is exploring this. To measure UX in AI tools, it helps to follow the user journey and match the right metrics to each step. Here's a simple way to break it down: 1. Before using the tool Start by understanding what users expect and how confident they feel. This gives you a sense of their goals and trust levels. 2. While prompting  Track how easily users explain what they want. Look at how much effort it takes and whether the first result is useful. 3. While refining the output Measure how smoothly users improve or adjust the results. Count retries, check how well they understand the output, and watch for moments when the tool really surprises or delights them. 4. After seeing the results Check if the result is actually helpful. Time-to-value and satisfaction ratings show whether the tool delivered on its promise. 5. After the session ends See what users do next. Do they leave, return, or keep using it? This helps you understand the lasting value of the experience. We need sharper ways to measure how people use AI. Clicks can’t tell the whole story. But getting this data is not easy. What matters is whether the experience builds trust, sparks creativity, and delivers something users feel good about. These are the signals that show us if the tool is working, not just technically, but emotionally and practically. How are you thinking about this? #productdesign #uxmetrics #productdiscovery #uxresearch

Green CSAT can still hide red flags. The momentum metric your CFO actually feels: Trust Delta™. A 4.7 CSAT score looks great on a dashboard. But it only shows how someone felt once — in a single interaction. It doesn’t tell you how much confidence they lost after an outage. It doesn’t show if trust recovered after a rocky release. And it doesn’t prove whether they’ll believe in you next time. That’s where Trust Delta™ comes in. It tracks how trust changes before and after key events — outages, incidents, major changes — so you can see the direction of the relationship, not just the temperature of a moment. 📈 +18% jump in confidence after a seamless change window. 📉 –27% dip following a poorly communicated outage. 🔁 +42% climb over three months as automation reduced ticket noise. Those aren’t satisfaction numbers. They’re momentum signals — and momentum is what executives actually fund. Because here’s the truth: CSAT tells you how you did yesterday. Trust Delta™ shows whether they’ll believe in you tomorrow. How to Use Trust Delta™ in Practice 1. Measure trust before and after every major event ↳ Add a simple confidence question after outages, changes, or releases: 2. “How much do you trust IT to deliver reliably?” Track the change, not just the score ↳ A shift from 62% to 80% is more valuable than a flat 78%. Momentum matters more than the moment. 3. Link trust movement to business decisions ↳ Use positive deltas to support funding conversations, and negative deltas to guide communication or process changes. Trust Delta™ isn’t about replacing CSAT. It’s about turning satisfaction into strategic insight — the kind that shapes decisions, earns influence, and moves IT from support to leadership. You can ONLY track CSAT or Trust Delta™ next quarter. Which one — and why? 📘 Trust Delta™ is one of the Grove Metrics I explore in The Grove Method for ITSM Excellence™ — where IT evolves from reactive service to trusted business partner. ♻️ Repost this if you’re ready to move beyond snapshots and start measuring momentum Follow Bob Roark for more Grove Metrics that turn IT from background noise into a business driver. #ITSM #CIO #Metrics #Trust #GroveMethod

❓ What compounds like interest, breaks like glass, & travels faster than your next product update? You can ship product. You can run ads, go viral, get thousands of users. But if you don’t have trust—you're not in #fintech. You're in tech that happens to handle money… temporarily! Because in fintech, trust isn’t a feature—it’s the entire business model. 🔍 After the hype comes the audit We’ve seen it play out: FTX. Celsius. Signature. Terra. Each one a masterclass in how fast “innovation” turns to incineration when trust goes missing. & now? Every regulator, every LP, every institutional buyer is asking the same thing: “Can I trust this company?” They're not asking if you’re fast. Or cool. Or crypto-native. They’re asking if you’re licensed, audited, & resilient—because that’s the new fintech stack. 📊 Let’s talk data: Trust is quantifiable 1. Edelman Trust Barometer 2024 • Institutions with transparent regulatory practices score +20% higher in trust • 68% of people now say “licensed status” impacts their choice of financial product 2. McKinsey’s “Building Trust in Digital Finance,” 2023 • Fintechs with visible compliance frameworks saw 2.1x customer LTV • Trust-led platforms reached 27% faster adoption among institutional partners • 91% of B2B customers cited “regulatory readiness” as a top trust signal 3. Deloitte 2023: Institutional Readiness Report • 83% of institutional investors now require proof of license before even entering commercial talks • 74% flagged “unclear regulatory posture” as the reason they walked away from a deal Let that sink in: You can be first to market… & still be first to fail if you're last to gain trust. 🛠️ So how is trust actually built in fintech? (It’s not vibes) Here’s what boards, regulators, & clients now expect: ✅ Licenses in trusted jurisdictions (VARA, ADGM, FCA, MAS—not basement-registered shellcos) ✅ Real-time compliance policies, not recycled PDFs ✅ Operational transparency—CCSS, penetration tests, recovery plans ✅ Zero heroism—teams with depth, not a one-person compliance army ✅ Governance that works—because trust without oversight is a PR campaign, not a strategy #Trust is no longer just a brand promise. It’s a balance sheet asset. 📈 Trust isn’t sexy—but it scales You don’t see founders celebrating a new policy manual on Twitter. But you should. Because those documents? That risk matrix? That early regulator engagement? That’s what unlocks: • Faster partnerships • Bigger checks • Cross-border access • Higher M&A multiples You don’t need to be perfect. But you need to be provably trustworthy. 🧠 The smartest play in fintech? If you’re building in fintech, forget the vanity metrics. Trust is the real KPI. It compounds like interest, breaks like glass, & travels faster than your next product update. & it lives in your regulatory posture, your governance discipline, & your willingness to be held accountable. Because in fintech, trust doesn’t just unlock the door. It is the door.