This article documents the Cohort table in Adobe Analytics.
See Cohort table for the Customer Journey Analytics version of this article.
A cohort is a group of people sharing common characteristics over a specified period. A Cohort table visualization is useful, for example, when you want to learn how a cohort engages with a brand. You can easily spot changes in trends, then respond accordingly. (Explanations of Cohort Analysis are available on the web, such as at Cohort Analysis 101.)
After creating a cohort report, you can curate its components (specific dimensions, metrics, and filters), then share the cohort report with anyone. See Curate and Share.
Examples of what you can do with a Cohort table:
Cohort table is available for all Customer Journey Analytics customers with access rights to Analysis Workspace.
See Cohort analysis in Analysis Workspace for a demo video.
Cohort Analysis does not support non-filterable metrics (including calculated metrics), non-integer metrics (such as Revenue), or Occurrences. Only metrics that can be used in filters can be used in Cohort Analysis, and they can only be incremented 1 at a time.
Cohort tables in Customer Journey Analytics support double-based (or any numeric-based) metric. For example, Purchase.Value (a double) can be used as an Inclusion/Return Metric. In addition, all metrics that are passed into Adobe Experience Platform via the Analytics Source Connector are also doubles.
The following sections describe Cohort Analysis features that allow for fine-tuned control over the cohorts you are building.
For more detailed information about creating a cohort and running a Cohort Analysis report, see Configure a Cohort table.
A Retention cohort table returns persons: each data cell shows the raw number and percentage of persons in the cohort who did the action during that time period. You can include up to 3 metrics and up to 10 filters.
A Churn cohort table is the inverse of a retention table and shows the persons who fell out or never met the return criteria for your cohort over time. You can include up to 3 metrics and up to 10 filters.
You can calculate retention or churn based on the previous column, not the included column, which is referred to as rolling calculation.
A latency table measures the time that has elapsed before and after the inclusion event occurred. Measuring latency is an excellent tool for pre- and post analysis. The Included column is in the center of the table and time periods before and after the inclusion event are shown on both sides.
You can create cohorts based on a selected dimension, and not time-based cohorts (which are the default). Use dimensions such as City geo, Marketing channel, campaign, product, page, region, or any other dimension to show how retention changes. Based on the different values of these dimensions.