Product Metrics and KPIs

If You Cannot Measure It, You Cannot Improve It

One of the most important shifts from junior to senior product thinking is moving from "Is the feature built?" to "Is the feature working?"

Building a feature and shipping it is only half the job. Understanding whether it achieved its intended outcome -- and why or why not -- is what separates truly impactful product managers from those who just ship code.

Product metrics are the numbers that tell you whether your product is creating value for users and for the business. KPIs (Key Performance Indicators) are the specific metrics your team commits to tracking as the primary measures of success.

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The North Star Metric

The North Star Metric is the single metric that best captures the core value your product delivers to users. Everything the product team does should ultimately move this number.

Examples of North Star Metrics:

• Airbnb: Number of nights booked
• WhatsApp: Daily active users sending messages
• Spotify: Time spent listening
• Paystack: Transaction volume processed

Why a single metric? It aligns the entire team. When every decision is evaluated against one number, debates about priorities become much clearer.

Choosing your North Star

A good North Star metric:

• Reflects genuine user value (not just engagement for its own sake)
• Can be influenced by the product team's decisions
• Leads to business outcomes (revenue, growth)
• Is measurable and trackable

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Categories of Product Metrics

Acquisition Metrics

How many new users are you getting, and from where?

• New user registrations: Total new sign-ups per period
• Customer Acquisition Cost (CAC): Total marketing and sales spend divided by new customers acquired
• Channel attribution: Which channels (organic, paid, referral) drive the most valuable users?

Activation Metrics

Are new users experiencing the core value of the product quickly?

• Activation rate: Percentage of new users who complete the defined activation event (e.g., making their first transfer)
• Time to first value: How long does it take from sign-up to the first meaningful action?
• Onboarding completion rate: What percentage of users complete the onboarding flow?

The "aha moment" is the moment when a user first experiences the core value of your product. Products that get users to this moment faster have dramatically better retention.

Engagement Metrics

How often and how deeply do retained users interact?

• DAU (Daily Active Users): Number of unique users active in a day
• MAU (Monthly Active Users): Number of unique users active in a month
• DAU/MAU ratio: Percentage of monthly users who are active daily. A DAU/MAU of 50%+ indicates strong daily engagement. WhatsApp is ~70%.
• Session frequency: How often users open the app
• Session length: How long users spend per session

Retention Metrics

Are users coming back?

• Day 1, Day 7, Day 30 retention: Percentage of users who return 1, 7, and 30 days after registration
• Churn rate: Percentage of users who stop using the product in a given period
• Retention curves: Graphs showing the percentage of users who remain active over time

Retention is the most important growth lever. A product that retains users well grows faster because acquisition builds on a base that does not leak.

Revenue Metrics

Is the product generating business value?

• MRR (Monthly Recurring Revenue): Total predictable monthly revenue from subscriptions
• ARR (Annual Recurring Revenue): MRR x 12
• ARPU (Average Revenue Per User): Total revenue divided by number of users
• LTV (Lifetime Value): Total revenue expected from a customer over their entire relationship
• LTV:CAC ratio: Revenue from a customer vs. cost to acquire them. Generally aim for 3:1 or higher.

Customer Satisfaction Metrics

How do users feel about the product?

• NPS (Net Promoter Score): "How likely are you to recommend this product?" scored 0-10. NPS = % Promoters (9-10) minus % Detractors (0-6).
• CSAT (Customer Satisfaction Score): "How satisfied were you with this experience?" (1-5 scale)
• Qualitative feedback: App store reviews, support tickets, user interviews

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Vanity Metrics vs Actionable Metrics

Not all metrics are equally useful. Beware of vanity metrics -- numbers that look impressive but do not indicate real business health.

Rule of thumb: If a metric can go up while the product is getting worse, it is probably a vanity metric.

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Setting Up a Metrics Framework

A structured approach to metrics prevents teams from tracking everything and acting on nothing.

The Input-Output Framework

• Output metrics (lagging): The business results you care about (revenue, retention)
• Input metrics (leading): The user behaviours that drive outputs (activation, session frequency)

Focus on input metrics because they can be influenced by your product decisions. Output metrics follow.

OKRs (Objectives and Key Results)

A goal-setting framework used by Google, Intel, and most modern tech companies:

• Objective: Qualitative direction ("Significantly improve user onboarding")
• Key Results: Measurable outcomes ("Increase Day 7 retention from 25% to 40%" and "Reduce time to first transfer from 4 days to 1 day")

OKRs create alignment: everyone on the team knows what success looks like and can direct their work accordingly.

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Using Data to Make Better Decisions

Having metrics is not enough. Product managers need to develop the habit of:

1. Establishing baselines: Know your current numbers before launching anything, so you can measure change.
2. Setting hypotheses: "We believe that improving the onboarding flow will increase Day 7 retention from 25% to 35%."
3. Running experiments: A/B tests, phased rollouts, feature flags.
4. Interpreting results: Did the metric change? Was the sample large enough? Are there confounding factors?
5. Acting on findings: Ship what worked. Learn from what did not. Document both.

The most effective PMs combine quantitative data with qualitative user research. Numbers tell you what is happening; user research tells you why.