Monthly active users is a vanity metric. You can have 50,000 MAUs and be about to go out of business if none of them are converting to paid, expanding their usage, or bringing in other users.
PLG companies need a different metric stack — one that maps to the actual health of the product-led engine, not just its top-line activity.
The PLG Funnel
Product-led growth lives across four stages:
Acquire → Activate → Retain → Expand
Each stage has a metric that matters. Optimizing the wrong metric at each stage is the most common PLG analytics mistake.
Acquisition: Signups Aren't the Metric
Signup rate is necessary but insufficient. The metric that matters at acquisition isn't how many people sign up — it's the quality-adjusted signup rate.
Time-to-activation by acquisition channel: How long does it take for users from each channel to reach your activation milestone? Users from your best channel might activate 3x faster than users from a generic paid channel. That means your best channel is delivering 3x more activation value per signup.
Signup-to-activation rate by source: What percentage of signups from each source reach your activation milestone? If you're optimizing signup volume without tracking activation rate by source, you might be filling the funnel with users who will never convert.
Track both. Prioritize channels with the highest signup-to-activation rate, not just the highest signup volume.
Activation: Time-to-Value is the Only Thing
Activation is the stage where most PLG products have the most leverage. The metric:
Time to first key action: How long does it take a new user to perform the action that predicts retention? This is usually 24–48 hours for the best-performing PLG products.
But "first key action" only tells you something if you've correctly identified the action. The way to identify it: cohort your users by which action they completed in their first session and compare 30-day retention across cohorts.
If users who sent their first message in session 1 retain at 65%, and users who only viewed the dashboard retain at 12%, "sent first message" is your activation milestone. Time-to-first-message is your activation metric.
Activation rate: What percentage of new signups reach the activation milestone within 7 days? This is your top activation metric. It should be on your weekly metrics dashboard.
Retention: Engagement Curves, Not Just DAU/MAU
Daily active users divided by monthly active users (DAU/MAU ratio, sometimes called "stickiness") is a useful high-level metric but tells you nothing about whether your retention is improving or degrading.
The metrics that tell you more:
Retention curves by cohort: Plot the 7-day, 30-day, 60-day, and 90-day retention for each weekly or monthly cohort. A product with improving retention will have newer cohorts sitting higher on the curve than older cohorts. A product with flat or declining retention will have cohorts converging at similar levels regardless of when they joined.
Feature-specific retention: Which users are most retained? What features do they use that less-retained users don't? This analysis usually surfaces 2–3 features that are disproportionately associated with retention — features worth investing in and promoting during onboarding.
Reactivation rate: What percentage of churned users come back within 90 days? A high reactivation rate is a signal that users recognize the product's value but have a usage pattern problem, not a value problem. These users are win-back targets.
Expansion: Product-Qualified Accounts
The expansion metric for PLG is the product-qualified account (PQA) rate:
PQA rate: What percentage of your active accounts show expansion signals in a given month?
Expansion signals vary by product but typically include: approaching a usage limit, using the product across multiple team members, regularly using features available only in higher tiers, and high engagement frequency (daily or multiple times daily active usage).
A rising PQA rate means your product is creating more upgrade-ready accounts — which is predictive of expansion revenue before it appears in MRR.
Net revenue retention (NRR): The ultimate expansion metric. If NRR > 100%, your existing customers are growing your revenue even without new customer acquisition. If NRR < 100%, new customer acquisition is just offsetting contraction.
The One Dashboard to Rule Them All
A PLG metrics dashboard doesn't need to be complex. The core weekly view:
| Metric | This Week | Last Week | 30-day Trend | |--------|-----------|-----------|--------------| | Signups | | | | | Activation rate (7-day) | | | | | Day 7 retention | | | | | Day 30 retention | | | | | PQA rate | | | | | Free-to-paid conversion | | | | | NRR | | | |
Review this weekly. Each metric tells you which stage of the PLG funnel needs attention. A dropping activation rate is a product or onboarding problem. A dropping Day 30 retention is a value delivery problem. A dropping PQA rate is an expansion motion problem.
FAQ
How do I identify the right activation milestone if I don't know what it is?
Run a cohort analysis: group users by which actions they completed in their first session, and compare 30-day and 60-day retention across groups. The action most strongly associated with retention is your activation milestone.
What sample size do I need for reliable cohort analysis?
At minimum, 50 users per cohort for week-over-week analysis, 100+ for month-over-month. Below these thresholds, individual user behavior creates too much variance for reliable conclusions.
Should I track DAU/MAU?
Yes, but as context, not a primary metric. DAU/MAU above 20% is generally considered healthy for SaaS (Slack targets 50%+). Below 10% suggests engagement frequency is low, which is a risk factor for churn regardless of what your retention curves show.
Written by
Michael
Lead Engineer, Greta Agency
Michael has audited and rebuilt onboarding flows for over 40 SaaS products. He's obsessed with the gap between signup and first value.