Product metrics deep guide
How to define, choose, and avoid vanity metrics
Every product team measures things. Few measure the right things. Here is how to identify your north star metric, build a metric tree, avoid vanity metrics, and set OKRs that drive decisions.
1. The north star metric
Every product should have one north star metric — the single number that best captures the value delivered to users and correlates with long-term business success.
A good north star metric:
Measures value delivered — not just transactions or impressions.
Is leading — it predicts future revenue, not just records the past.
Is understandable by the whole team — not just the data science team.
Is actionable — the team can actually influence it with their work.
2. The metric tree
A metric tree breaks the north star metric into its component inputs. Each node can be further decomposed, giving the team a complete view of every lever they can pull.
Example: Daily Active Users
New Users
· Organic signups
· Paid acquisition
· Referrals
Retained Users
· D7 retention
· D30 retention
· Habit loops
Churned Users
· Deactivations
· Inactive 30d+
· Cancellations
Teams that only track the north star cannot diagnose why it moved. Teams with a metric tree can immediately see whether a drop in DAU is from acquisition, retention, or reactivation — which determines the response.
3. Vanity metrics vs actionable metrics
Vanity metrics look impressive in a slide deck but do not drive product decisions. Actionable metrics tell you what to do next.
Vanity metrics — avoid these as primary signals
Total registered users
Does not tell you if they are active or churned. A database of inactive accounts is not traction.
Page views
Without conversion context, this is noise. A spike in page views that does not move activation or revenue means nothing.
App downloads
With low activation, this means nothing. Downloads measure marketing reach, not product value.
Actionable metrics — use these to drive decisions
Activation rate
% of new users who complete the key action in the first session.
Activation is the first proof that your product delivers value. A low activation rate means users are not reaching the aha moment.
D7 / D30 retention
% of users who return 7 or 30 days after acquisition.
Retention is the single best proxy for product-market fit. If users come back on their own, the product has value.
NPS
Net Promoter Score — % promoters (9-10) minus % detractors (0-6) on a 0–10 satisfaction question.
A lagging indicator of satisfaction, but useful for diagnosis. Combine with qualitative follow-up to understand the why.
LTV / CAC ratio
Customer Lifetime Value divided by Customer Acquisition Cost.
Tells you whether the business is acquiring customers profitably. A ratio below 3:1 is a warning sign.
4. OKRs — Objectives and Key Results
OKRs are the bridge between strategy and metrics. They connect qualitative ambition to quantitative targets.
Objective
“Become the go-to resource for career changers breaking into tech.”
Qualitative, ambitious, directional. Inspires without prescribing the path.
Key Results
Increase D30 retention from 28% to 40%.
Increase NPS from 32 to 48.
Grow organic sessions from 50k to 120k/month.
Quantitative. 3–5 per objective. Each tells you unambiguously whether the objective was achieved.
Common OKR mistakes
KRs that are outputs, not outcomes
'Launch 3 features' is an output. 'Increase activation rate from 22% to 38%' is an outcome.
Sandbagging
Setting KRs you know you will hit. Healthy OKR achievement is 70% at stretch — 100% means the goal was too easy.
Too many OKRs
Three OKRs with three KRs each is the maximum. More than that and the team loses focus.
KRs that do not connect to the north star
If hitting all your KRs would not move the north star metric, the OKRs are misaligned.
Keep learning
New to product metrics?
Start with the foundational guide — it covers DAU, MAU, churn, NPS, CAC, and LTV with formulas and benchmarks for each.