Stickiness ratio
The share of monthly or weekly active users who show up on a typical day, revealing whether use is occasional or habitual.
See it
What it is
Stickiness divides a short active-user window by a longer one, usually DAU by MAU or DAU by WAU. If 200 of the 1,000 people active in the last 30 days were active today, DAU/MAU is 20%. It is a quick read on how much of the broader audience shows up on a typical day. Facebook made the pair famous by printing DAU and MAU in every quarterly filing, which is why investors ask for the ratio by name.
Reach for it when repeat frequency matters, and judge it against the job's natural rhythm. A chat app can reasonably aim for daily use; tax software cannot. Pin down the qualifying activity and use rolling windows, because changing either one changes the ratio.
Gotcha: a rising ratio does not always mean a healthier product. MAU can shrink faster than DAU and make the fraction climb while both counts fall. Read the ratio beside DAU, WAU, MAU, and a retention curve, and never compare two products whose definitions of 'active' differ.
Ask AI for it
Build a stickiness report in PostHog for the [core value event]. For each UTC date, count unique users who fired the event that day, in the rolling 7 days ending that date, and in the rolling 30 days ending that date. Plot DAU/WAU and DAU/MAU as percentages, plus the three raw user counts underneath. Use PostHog's resolved person identity, exclude internal users and test events with explicit filters, and do not average daily percentages into a monthly result. Add a warning when either denominator is below 100.