Review and analyze product metrics with trend analysis and actionable insights. Primary input is user-provided data (table, CSV, or description). Outputs metric scorecard, trend analysis, bright spots, areas of concern, and recommended actions. Invoke as $metrics-review.
Review and analyze product metrics, identify trends, and surface actionable insights.
With a connected analytics tool (Amplitude/Mixpanel/Pendo/Heap): Pull key product metrics for the relevant time period. Get comparison data (previous period, same period last year, targets). Pull segment breakdowns if available.
Without connected tools: Ask the user to provide:
Ask the user:
Structure the review using the metrics hierarchy from the metrics-tracking-knowledge skill: North Star metric at the top, L1 health indicators (acquisition, activation, engagement, retention, revenue, satisfaction), and L2 diagnostic metrics for drill-down.
If the user has not defined their metrics hierarchy, help them identify their North Star and key L1 metrics before proceeding.
For each key metric:
Identify correlations:
2-3 sentences: overall product health, most notable changes, key callout.
Table format for quick scanning:
| Metric | Current | Previous | Change | Target | Status |
|---|---|---|---|---|---|
| [Metric] | [Value] | [Value] | [+/- %] | [Target] | 🟢 On track / 🟡 At risk / 🔴 Miss |
For each metric worth discussing:
What is going well:
What needs attention:
Specific next steps based on the analysis:
After generating the review:
Use tables for the scorecard. Use clear status indicators. Keep the summary tight — the reader should get the essential story in 30 seconds.