Analyze Product Metrics

Turn raw analytics into structured quantitative evidence — the numeric counterpart to interview research. This is the discovery toolkit's quantitative half: it sizes problems, moves assumptions off weak evidence, and supplies the data ICE weights most heavily.

When to Use

• Sizing an opportunity or reading whether a metric moved (and why)
• Producing strong evidence to validate an assumption or feed an ICE score
• Reviewing baseline vs target metrics for an initiative
• Investigating a funnel drop, retention change, or A/B result

Input

• Primary: Raw analytics — funnel/conversion data, retention cohorts, event/usage data, A/B test results, dashboard exports
• Required: The question or metric in focus (e.g., "why does checkout drop at step 3?")
• Context: company-level-context/ for the strategic metric tree / OKR targets