What are Product Metrics?
Product metrics are quantitative measures of your product's health and performance. They track user behavior (how many, how often, how deeply), business outcomes (revenue, retention, conversion), and product quality (performance, reliability, satisfaction).
Metrics serve as the product team's instrumentation panel. Just as a pilot monitors altitude, speed, and fuel level, PMs monitor activation, retention, and engagement to know whether the product is on course.
Why Product Metrics Matter
Without metrics, product decisions are opinions. "I think users like the new feature" becomes "the new feature increased daily active usage by 12%." Metrics transform subjective judgments into objective assessments.
Metrics also enable prioritization. When you can compare the retention impact of Feature A versus Feature B, you can allocate resources based on evidence rather than politics.
How to Choose the Right Metrics
Organize metrics by stage using the AARRR framework:
- Acquisition: How do users find you? (Signups, traffic sources, cost per acquisition)
- Activation: Do they get to value? (Activation rate, onboarding completion, time to value)
- Retention: Do they come back? (Retention rate, DAU/MAU ratio, cohort retention curves)
- Revenue: Do they pay? (Conversion rate, ARPU, LTV)
- Referral: Do they tell others? (Viral coefficient, NPS, share rate)
Identify your weakest stage. If activation is 20%, fixing that has more impact than optimizing revenue from the 20% who activated. Focus on the bottleneck.
Select one north star metric that captures overall value delivery. Build a metric tree beneath it showing how input metrics combine to drive the north star.
Product Metrics in Practice
Spotify tracks "time spent listening" as their north star, decomposed into sessions per user, tracks per session, and listening duration. Each squad owns input metrics within this tree.
Shopify monitors "GMV" (gross merchandise value) processed through their platform. This metric captures value delivery: when merchants sell more, Shopify is working. They decompose GMV by merchant segment, geography, and product surface.
Common Pitfalls
- Vanity metrics. Total registered users, page views, and app downloads feel good but may not correlate with product health. Focus on engagement and retention.
- Too many metrics. A dashboard with 40 metrics leads to cherry-picking favorable numbers. Track 3-5 that matter most.
- No baseline. A metric without context is meaningless. Always compare against a baseline, benchmark, or prior period.
- Metrics without action. If a metric drops, what do you do? If you cannot answer that question, the metric is not actionable.
Related Concepts
Product metrics are collected through product analytics tools and organized using the north star framework and metric trees. They feed into OKRs as key results. Understanding leading vs. lagging metrics helps you choose metrics that predict outcomes.