Retention Analysis

This report shows the change in the percentage of users returning to the app over time. For instance, you can estimate:

  • User demand for various features of the application.
  • How application updates affected retention.
  • The user's LTV in the application.

The report allows you to pull out certain users by defining data segments. For example, you can create a segment of users who made a purchase in a certain region. With data segments, you can also set the period of the target action for your report.

To build a report, you need to choose the time period, the audience segment, the grouping type, the cohort size (a date range such as a day, week, or month), and the metric to analyze.

By default, the report shows changes in Retention after the app was installed (day 0), on the following day (day 1), a day later (day 2), and so on. This report will show exactly when users start losing interest in the app.

Grouping data

Grouping allows you to evaluate metrics such as the effectiveness of the advertising partner, campaign performance, and the impact of updates on retention.

The data in the report can be grouped by:

  • Installation date.
  • Media source.
  • Tracker and tracking URL parameters.

To exclude negligible partners, trackers, or tracking URL parameters, specify the minimum size of the cohort. This enables you to focus on the key metrics.

Metrics

Retention, Rolling Retention, and Retention Dynamics are available for analysis.

The percentage of users who installed the app during a given day, week, or month (the reference period) and then returned to the app (opened it) on a specific day, week, or month after installing.

This metric is calculated as the ratio of the number of users running the app during the Nth day, week, or month to the number of users who installed the app in the reference period (this number is taken as 100%).

The example above shows the actions of four different users over one week:

  • On Day 0, all 4 users installed the application, so the retention metric is 100%.
  • On the next day after the installation (Day 1), only 2 out of 4 users opened the app again. The retention metric is 50%.
  • On the fourth day after the installation (Day 4), none of these 4 users opened the app. The retention metric is 0%.

The following metrics are displayed in the report:

  • The color key of metrics on the chart. Enables you to show or hide each metric on the chart.
  • Grouping (by date, partner, tracker, and tracking URL parameters).
  • The total number of users in the cohort for the specified period.
  • The Retention metric value.
  • The number of users who returned to the app on Day N.
Retention Dynamics changing

Example of Retention calculation

In the example:
  • Date range is July 1 — October 21.
  • Grouping by sources is enabled.
  • The time range is divided into months.
  • Retention metrics is selected.

Example of calculating the percentage of users who returned in the first month after installation:

The report displays 19.30%. The resulting numbers differ because the interface displays the number of all returned users grouped by the partner, and the percentage of returns is calculated only for the completed time interval.

For example, it's the 21 of October. For installations made in September, the first month (October) is not over yet. So September is not included into the calculation of the final value of the first month. Therefore, to calculate the percentage of returns in the first month, you need to sum only the values of the zero months, which values are taken into account.

To calculate the percentage of returned users in the first month:

  1. Turn on grouping by installation date.
  2. Enable segmentation by the appropriate installation source.
  3. Divide the total number of returned users in the first month by the total number of installations in July and August:

    In the report, the value of 19.34 is rounded to a decimal place.

Data export

You can export data by choosing an item from the Export dropdown list above the chart. The data is exported based on the selected report settings: segmentation, grouping, and time period.

The dropdown list contains the following elements:

  • Cohorts as CSV — Exports the data from the table in the CSV format.
  • Chart as PNG — Exports the chart image in the PNG format.

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