Growth and engagement metrics for PMs
Use Conversion Rate to measure defined actions, Retention Analytics to compare cohorts, DAU/MAU to examine usage frequency, and NPS to summarize recommendation responses. Together they provide context for investigating how people use and value the product.
Suggested learning order
Start with the funnel, then look at cohorts over time, then at habit, then at sentiment. You can investigate each measure without assuming the others are healthy.
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Frequently asked questions
Compare the same conversion action, traffic source, and audience. Unbounce’s 2024 report gives a 3.8% median for SaaS landing pages; that is not a trial-to-paid or checkout benchmark. Use relevant external data alongside your own baseline and the value of a conversion. Source: https://unbounce.com/conversion-benchmark-report/saas-conversion-rate/
DAU/MAU compares daily with monthly active users. With average DAU over a 30-day month, 20% corresponds to an average of six active days per monthly active user, not necessarily a typical individual’s pattern. Mixpanel’s 2024 report gives 37% across industries for 2023, using mean DAU divided by mean MAU. Compare the same activity definition and intended usage cadence. Source: https://mixpanel.com/wp-content/uploads/2024/01/2024_Benchmarks_Report.pdf
A cohort curve that levels off can indicate a group continues to find value. A flat 30% is a useful observation, not proof of product-market fit. Interpret it with the return-event definition, cohort age, paid retention, and customer feedback. Exact-day activity retention does not show that everyone absent on a given day permanently left.
NPS comparisons depend on the customer group, survey question, timing, and sampling method. Use a sourced reference that matches those conditions rather than a universal good or elite cutoff. Track your own segments and follow-up feedback alongside the score.
If acquired users leave quickly, investigate retention before assuming more acquisition spend will pay back. Acquisition tests can still help you find the right audience. Compare retention, acquisition costs, customer value, and cash needs rather than following a fixed order.
Count users at each defined step and calculate both the number lost and the step conversion rate. A large drop is worth investigating, but the most valuable improvement also depends on user intent, downstream value, implementation cost, and whether the drop is avoidable. Use consistent cohorts and windows across steps.
Use a metric that matches the intended cadence, such as WAU/MAU for a weekly product. A tax product can have low daily use without a retention problem. Define the useful action and review whether users return when they need it.
Use several measures that answer different questions. Conversion records a defined action, retention records later returns or continued subscriptions, DAU/MAU measures frequency, and NPS summarizes recommendation responses. None identifies the cause of a change on its own; investigate the underlying cohorts and feedback.
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