product-analysis

# Product Analysis ## Purpose Understand how a product is actually used and decide what to do about it. The failure mode is a dashboard full of numbers that go up, none of which are connected to whether the product is working. ## When to Use - Deciding what to build next. - A metric moved and nobody knows why. - Assessing whether a feature worked. - Setting up product analytics. ## Capabilities - Metric selection: the one that matters versus the ones that flatter. - Funnel analysis and drop-off diagnosis. - Retention and cohort analysis. - Feature-adoption measurement. - Prioritization on evidence. ## Inputs - Usage data, at the event level. - What the product is meant to do for the user. - The decision this analysis informs. ## Outputs - The metric that actually reflects value, and where it stands. - The specific point of failure in the funnel, or the specific cohort that churns. - A prioritized recommendation. ## Workflow 1. **Choose the metric that reflects value received** — Not signups, not page views, not "engagement". What is the action that means the user got what they came for? That is the metric. 2. **Look at retention before acquisition** — A product with a leaking bucket does not need more water. If week-4 retention is 8%, acquisition spend is being poured into a hole. 3. **Segment before concluding** — An aggregate number hides everything. A flat retention curve can be two cohorts: one that retains at 60% and one at 2%. Those require completely differ...