Retention guides
Working guides for growth and product teams reading cohort retention.
Seven guides that go past the definitions: comparing the three types, reading a retention curve, why paid Day 1 trails organic, cutting retention by channel, choosing the cohort start event, weekly-use apps, and turning retention into budget decisions.
Which guide do you need?
- 01Classic vs rolling vs cumulative retentionClassic, rolling and cumulative retention count different users on the same day. See the definitions, a ten-user worked example and when to use each one.
- 02How to read a retention curveA retention curve plots one cohort's retention against Day N. Read the early drop, the flattening point and smile curves, and why shape depends on definition.
- 03Why paid D1 retention is lower than organicPaid D1 retention below organic is partly normal, as organic users arrive with intent. See the causes, from targeting to measurement errors, and how to check.
- 04Retention by channel and campaignBlended retention hides what each channel does. Learn to cut a cohort table by channel, campaign and creative, keep naming clean and spot a channel mix shift.
- 05Choosing the cohort start event: install or first purchaseHow to define cohorts by choosing a start event: install, first open, sign-up or first purchase, what each answers, survivorship bias, day boundaries, channels.
- 06Retention for weekly-use vs daily-use appsWhy classic Day N retention undercounts apps people use weekly, and how cumulative windows, weekly cohorts and DAU/MAU give a fairer read of weekly-use apps.
- 07Turning retention into decisions: LTV, payback and budgetHow to turn app retention into decisions: which definition feeds LTV and forecasts, a simple LTV from a retention curve, cost per retained user and payback.
Questions
What is the difference between classic, rolling and cumulative retention?
Classic counts users active on exactly Day N. Rolling counts users active on Day N or any later day, and cumulative counts users active at least once from Day 1 to Day N. They use the same raw activity but answer different questions.
Why is my rolling retention higher than classic?
Rolling also counts users who skipped Day N but came back later, so it can never be lower than classic. The gap grows the longer a cohort has been observed, because late returns keep adding to it.
What is cumulative retention?
Cumulative retention is the share of an install cohort that opened the app at least once between Day 1 and Day N. It never falls as N grows and it is fixed once Day N has passed, which makes it a good activation measure.
Which retention number should I compare with published benchmarks?
Classic retention, unless the benchmark says otherwise, because most published retention benchmarks count activity on an exact day. Comparing a rolling or cumulative number with a classic benchmark will flatter you.
Are the numbers on this site real?
No. Every chart and table uses one made-up app built to show the method. The numbers are sample data, not benchmarks, so use them to learn the definitions rather than to judge your own app.