Growth and engagement metrics for PMs
Four calculators that move you from "users showed up" to "users came back." Start with Conversion Rate to find where the funnel leaks. Then use Retention Analytics to see if cohorts flatten or fall off a cliff. DAU/MAU tells you whether daily use is a habit. NPS tells you whether the people who stayed would recommend you. Each one answers a different question. Run them together and you have a picture of growth that's actually honest.
Suggested learning order
Start with the funnel, then look at cohorts over time, then at habit, then at sentiment. Each layer assumes the previous one is healthy.
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Frequently asked questions
It depends on the product and the step. The all-industry average for ecommerce sits near 1.9%, with most stores in the 1.5 to 3% range. SaaS landing pages cluster around 3 to 4% median. SaaS free trials usually convert at 2 to 5%, with top-quartile teams hitting 8% or higher. The number that actually matters is whether you're improving against your own baseline, not whether you beat someone else's report.
DAU/MAU is daily active users divided by monthly. It measures habit. Roughly 20% means a typical user shows up about 6 days a month. Mixpanel's 2024 benchmark report puts cross-industry stickiness at around 37%, but that's heavily skewed by social and messaging apps. For most B2B SaaS, 10 to 20% is normal. For consumer social, 50%+ is the bar. The real value is the trend in your own product. A ratio that climbs from 12% to 18% over a quarter is a stronger signal than the absolute number.
Look at whether the cohort line flattens. A retention curve that keeps falling forever means people try the product, leave, and don't come back. A curve that flattens at, say, 30% means there's a stable group who keep using it. Sequoia and a16z both use the flattening retention curve as a working signal of product-market fit. Higher flatten-out level is better. SMB SaaS teams aim to keep monthly logo retention above 85 to 90%, with top-quartile B2B SaaS above 92%.
The B2B SaaS average sits in the 30 to 41 range depending on which benchmark report you read. Above 40 is generally treated as good, above 50 as excellent, above 80 as elite. Industry matters more than the absolute number. EdTech and FinTech tend to score higher, healthcare and ML/AI tools lower. The trend in your own NPS, segmented by plan or persona, is more useful than chasing the number itself.
Retention. Acquisition is the metric that looks good in dashboards. Retention is the metric that decides whether you have a business. If your cohort curve is falling off a cliff, every dollar you spend on acquisition is leaking back out faster than you can pour it in. Andrew Chen's "leaky bucket" is the standard metaphor and it's right. Fix the bucket, then turn on the tap.
Map every step, count users at each one, then compute step-to-step conversion. The biggest absolute drop is the most valuable fix. For SaaS onboarding, the first 1 to 3 screens often lose 30 to 50% of users by themselves, with one report citing roughly 38% drop after the first screen. Fixing that step first usually beats polishing later steps that 90% of users never reach.
DAU/MAU under-reports for weekly products. Use WAU/MAU instead, or define "active" against the natural cadence of the product. A tax tool with 100% yearly retention might have a DAU/MAU of 1%. That doesn't mean it's broken. The signal you want is how often a user comes back relative to how often they should.
No. Each one has a blind spot. NPS rewards loud fans, ignores quiet quitters. DAU/MAU misses depth of use. Conversion rate ignores quality of the converted user. Retention misses why people leave. The fix is to track three or four together and watch for patterns. A product with high NPS, high stickiness, falling retention, and rising churn has a real problem behind the friendly headline.
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