AppsFlyer's Cohort Report

  • Advertisers


A cohort is a group of people that have common characteristics and are considered as a group.

AppsFlyer's Cohort Report provides advertisers with the ability to view and compare different metrics per multiple cohorts over different time frames.

The Cohort's data is aggregated and LTV-based. It refers to your organic and non-organic user acquisition data only (retargeting data is excluded).

For example, an advertiser can create different cohorts according to different GEOs and compare the average number of purchases per user for each cohort over the first 30 days of each user's activity.

The Cohort Report is comprised of 3 layers:

  • Defining the cohort
  • Selecting the metric to be analyzed
  • Selecting the time frame to be looked at

1. Define the Cohorts

Define the cohort groups you would like to view:

1.1 Select the date range in which the users first launched the app.


1.2 Apply additional filters to divide these users to different cohorts by clicking Filter and defining the filters

1.3 Define the min cohort size. Cohorts which have less users than this value are not displayed


1.4 Define the groups-by (see Cohort Grouping below for details)

1.5 Click Apply

Cohort Groupings

The cohort data is grouped By default by the media source grouping, to compare cohorts from different media sources.

Other available groupings are: campaign name, install date, country (Geo), cohort day (same as install date), site ID and ad group or ad set on Facebook (for Facebook campaigns only). It is also possible to group by the free attribution link macro af_sub1.

You can select up to 4 dimensions to group your data by. The order of the groupings matters, so the first grouping is the primary grouping, the one afterwards is the secondary etc.

 Example - A/B testing using cohorts

You have many creatives you use to advertise your app, and they all have a dominant color: red, yellow or blue. On each attribution link you use the af_sub1 parameter, which states the used dominant color. You decide on using the cohort report to A/B test your results.
By grouping geo and then af_sub1 you get a list of all countries and the results of the 3 colors per each country.


2. Select the Metric to Analyze

Click the Metric dropdown list to select the metric you would like to view per the different cohorts.


The available metrics are:

  • Average sessions per user
  • Average revenue per user
  • Average # of revenue events per user
  • Any in-app event reported by the advertiser (average number of occurrences per user for each event)
  • You can also select "All" to view a snapshot of all metrics per cohort


Revenue always appears in USD, even if the "preferred currency" has been changed.

3. Select the Time Frame

The different metrics are calculated per different time frames, which represent the average cumulative activities in the first X days after install per user. The provided time frames are 1, 3, 5, 7, 14, 30, 60 and 90 days. Example: cohort day 3 of network A shows 10 sessions, meaning the average user attributed to network A performs 10 sessions in the first 4 days after installation (install day, day 1,2 and 3).


AppsFlyer considers the counting of a day based on the UTC +0 calendar date and not based on the number of hours since install. For example, if an install occurs on Feb 1st at 22:44 UTC +0 and a purchase takes place on Feb 5th at 01:12 UTC +0 — the purchase is shown on Day 4 even though it occurred 3 days after the install.

The generated report provides a graph and a data table. The example below is for users from Germany and the UK, grouped by campaign and by the attributed media sources:

Note that the table can be sorted by any timeframe (columns), in this example it is sorted according to the First 14 days timeframe.

When selecting All in the Metric dropdown, you can view a snapshot of all metrics according to a selected timeframe:


  1. The filter values are not dependent. Example: Even when selecting Facebook as a media source, the campaign names from ALL the sources are displayed.
  2. Data Freshness: AppsFlyer aggregates the cohort data on a daily basis. For applications in the UTC - (minus) time zone it may take up to 48 hours for the report to be populated with data. For applications in UTC + (plus) time zone it may take up to 24 hours for the report to be populated.
  3. Cohort data can be calculated for 90 days or less. The data displayed will be based on the time offset between the current date (excluding the 12 hour delay) and the later date in the selected range.
  4. Cohort data is always displayed in UTC +0, regardless of the selected time zone in your AppsFlyer dashboard.
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