Posts tagged "Metrics"

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Customer satisfaction is a hierarchy, not a metric

7 min read

Why do customers churn despite green dashboards? Three layers determine retention: friction (anger), outcomes (indifference), resonance (loyalty).

We have all been in that strategy meeting. The dashboard is green. Uptime is 99.9%, support ticket volume is down, roadmap is on schedule. And yet, customers are churning. The problem isn't the data. It's the definition. We treat "customer satisfaction" as a single bucket. We dump everything into it: bug fixes, new features, polite support emails, brand colors. If the bucket is full, we assume we are winning. But satisfaction isn't a bucket. It's...
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The Feature Factory Problem AI Amplifies

4 min read

AI accelerates shipping but not learning. Teams build faster without validating if they're solving the right customer problems.

Your team just shipped three features this week. Last quarter, that would have taken a month. AI tools turned your engineers into feature factories. Your designers generate variants in minutes. Your PMs prototype without waiting for engineering resources. Everyone's celebrating velocity. Who's checking if you're solving the right problems? Creation velocity isn't validation velocity Recent research shows contradictory results on AI's impact. Some studies report significant productivity gains, others find developers actually slow down when...
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Fast Teams Don't Ship More, They Learn Faster

3 min read

Velocity isn't about shipping more features. It's about running faster learning loops that turn uncertainty into validated decisions.

Two teams both ship every week. One is learning. The other is just busy. The difference isn't work ethic or talent. It's what they optimize for. Slow teams measure velocity by features shipped. Fast teams measure it by hypotheses validated. One counts outputs. The other measures learning rate. The Learning Rate Problem Shipping is easy. Learning is hard. Most teams can release code weekly but take months to figure out if it worked. They ship...
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Traffic Metrics Are Lying to You

3 min read

Webflow's AI search data reveals why aggregate traffic is misleading and what product teams should measure instead.

Your traffic is down. Your growth team is panicking. And your product metrics might be telling you absolutely nothing useful. Kyle Poyar's 2025 State of B2B GTM report uncovered something fascinating: Webflow's aggregate traffic is declining while their business is accelerating. ChatGPT referrals convert at 24% compared to 4% from Google. Two-thirds convert within 7 days. This isn't a Webflow-specific anomaly. It's what happens when AI search reshapes discovery. The death of aggregate traffic as...
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Evals in AI Product Development

3 min read

Evals make AI products measurable. Traces, annotations, and layered tests turn evaluation into a practical loop for reliability.

AI models don’t break like code, but they can drift, hallucinate, or mislead — which is why teams are turning to evals. The debate over whether every team needs them signals that we’re still learning how to measure quality in systems that learn on their own. What Evals Are For someone not familiar with evals, here’s a quick overview. Evals are structured tests that measure how well a model performs on real-world tasks. Unlike conventional...
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The Feedback Loop Fallacy in AI Products

2 min read

AI feedback loops can lie. Learn why engagement metrics fail and how product managers can rebuild truth-centered measurement systems.

For years, product managers have lived by a simple gospel: ship, measure, learn. The faster your feedback loop, the quicker your product improves. But AI is quietly breaking this law of motion. The feedback loops we’ve trusted for decades no longer tell the truth. When feedback starts lying In traditional software, user behavior is a reliable proxy for value. If conversion rates increase or churn decreases, the product has likely improved. With AI, that assumption...
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When to Trust Intuition vs. Metrics

3 min read

Intuition is a compass, metrics are a map. Here’s how product managers can decide which to trust, depending on the product stage.

This is a follow-up from an earlier post on the limit of metrics. Product managers often wrestle with a familiar question: Should I trust the numbers, or should I trust my instincts? The truth is, both matter — but their weight changes depending on where your product is in its lifecycle. Intuition plays a bigger role early, while metrics take over later. Knowing when to lean on which can be the difference between chasing noise...
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The Limit of Metrics

4 min read

Metrics measure the present, but intuition imagines the future. Here’s why great product managers need both — and how to define intuition.

Product managers love metrics. Dashboards, OKRs, funnel charts — these tools are everywhere. They give us a sense of control, objectivity, and accountability. But metrics have limits. They can only measure what already exists. They tell you how a current feature is performing, but they can’t tell you what to build next. This is where intuition comes in. What Intuition Really Means in Product Work In product management, “intuition” often gets dismissed as gut feel....
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How to Make OKRs Work

3 min read

Practical tips to make OKRs work: writing strong objectives, measurable key results, and avoiding common pitfalls in execution.

This is Part 2 of a two-part series on OKRs inspired by John Doerr’s book Measuring What Matters. You can read Part 1 here: Why OKRs Matter. OKRs are simple to understand, but deceptively hard to get right. Many teams write OKRs once, post them in a slide deck, and never look back. Others confuse them with KPIs or use them as a laundry list of tasks. The result is disappointment: OKRs become busywork rather...
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Why OKRs Matter

3 min read

Learn why OKRs matter, how they align teams, and the four superpowers that make them a proven framework for execution.

This is Part 1 of a two-part series on OKRs inspired by John Doerr’s book Measuring What Matters. In Part 2, we’ll explore how to make OKRs work in practice. Most organizations don’t fail because of a lack of effort. They fail because energy is scattered across too many priorities. Objectives and Key Results, or OKRs, provide a way to channel focus toward what truly matters. An OKR has two parts: Objective: a clear, inspiring...
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