What retention answers
Treat a change in the curve as a signal to investigate rather than a measure of what caused it. Many things influence whether someone returns to your app or website, including your messaging. When you want to connect specific messages to what users did next, use Conversion metrics, which attribute conversions to the messages that drove them.A worked example
Follow one cohort through five days to see how the numbers come together. A cohort is a group of people you track over time. Say 1,000 users had a session on July 28. Those 1,000 users become the cohort, and the group stays fixed from that point on. Nobody joins it later and nobody drops out of it. Channel and platform series membership stays fixed even if Subscriptions change during the window. From there, the chart looks at each following day and counts how many of those same 1,000 users came back.
Day 3 is higher than Day 2, which is expected. OneSignal measures each day independently against the original 1,000, so someone who skipped July 30 and returned on July 31 counts on Day 3. The curve tracks how much of the original group is active on each day, so it can rise as well as fall.
Reading the shape
Look at the shape of the curve before you read any single number. Falls, then flattens. Part of the cohort stops returning over the first few days, and the rest keep coming back at a steadier rate. The level where it flattens tells you roughly how much of that day’s audience returns regularly. Stays high and flat. Most of the cohort returns most days. This can happen when your app or website is part of something people do daily, or when the cohort was drawn from a day that skewed toward your most active users. Falls continuously. The cohort keeps thinning across the whole window. A 30-day window shows whether the curve levels off later than a shorter window would reveal. Drops on Day 1. Most of the cohort did not return the next day. Reasons can include onboarding, the expectations set before someone arrives, or a cohort start date that captured a burst of one-time visitors. Comparing the same shape across different cohort start dates tells you more than any single day’s rate. Your own trend over time is the most useful benchmark. The chart plots one cohort at a time, so compare dates yourself or export each to CSV.Comparing channels and platforms
Set Compare by to Channel or Platform to break the cohort into series. Channel series reflect the channels each user is subscribed to on the cohort start date. They overlap, because a user subscribed to both push and email appears in both series, so do not expect them to add up to the total. Read each series against the total rather than against each other. The series for users with no subscribed channels is a useful baseline. Comparing it against a channel series shows how return rates differ for users subscribed to that channel versus users with no subscribed channels. That gap is not the causal effect of messaging. People who subscribe are often already more engaged, so treat the comparison as a signal to investigate. Platform series divide the cohort by device type. Large gaps between platforms can point at differences in the product on each platform rather than in your messaging.How retention is calculated
These rules determine every number on the chart. For filters, UTC day boundaries, data availability, and export, see Retention metrics. Cohorts are snapshots. Channel and platform series membership is fixed on the cohort start date. Someone who unsubscribes from email on Day 5 stays in the email series for the whole window, because they were subscribed on Day 0. This is what makes cohorts comparable over time. Days are counted independently. OneSignal reports whether each cohort member had a session on each day, regardless of the days in between. The curve ends at the last complete day. The chart hides incomplete days and draws no projection. A shorter line means the window is still filling in, not that retention dropped to 0%. Retention counts users. A session on any one of a user’s devices counts as activity for that user, so someone who uses your app or website on a phone and a laptop counts once rather than twice. See Sessions for how OneSignal tracks session data per Subscription and aggregates it at the user level, and Users and Subscriptions for how the two relate.FAQ
My curve goes up on some days. Is that a bug?
No. OneSignal measures each day independently against the original cohort, so a user who skips a day and returns later counts on the day they return. A curve that rises on some days is expected.Which window should I use?
Start with 30 days to see whether the curve flattens, then use 7 or 14 days when you want a closer look at the first few days after the cohort start date. Shorter windows show the early drop-off in more detail.Can I compare two cohorts side by side?
Not in the chart today. Select one cohort start date at a time and compare the curves yourself, or export each to CSV.Related
Retention metrics
Filters, data availability, and export for the Retention chart.
Sessions
How OneSignal defines a session and aggregates session data across a user’s devices.
Users and Subscriptions
How Users and Subscriptions relate, and why retention counts users.
Metrics glossary
Canonical definitions for every metric across the dashboard, API, CSV, and Event Streams.