Analyzing User Behavior in Groups
Cohort analysis is a powerful way for streaming services to move beyond looking at their user base as one giant monolith. A ‘cohort’ is simply a group of users who are segmented based on a shared characteristic or experience within a defined time-span. By tracking and comparing the behavior of different cohorts, platforms can gain deep insights into what drives long-term engagement and retention.
Common types of cohorts in media analytics include:
- Acquisition Cohort: A group of users who all signed up for the service in the same week or month (e.g., the ‘January 2025 signup cohort’).
- Behavioral Cohort: A group of users who all performed a specific action, such as watching a particular movie or series in their first week of subscribing.
What Cohort Analysis Reveals
By tracking these groups over time, platforms can answer crucial business questions:
- Measuring Retention: By following the January 2025 cohort, a platform can see what percentage of those specific users are still subscribed three months, six months, or a year later. This helps them understand and predict ‘churn’ (cancellation rates).
- Identifying ‘Gateway’ Content: A platform might discover that the cohort of new users who watch Show X in their first month are far less likely to cancel their subscription than users who don’t. This identifies Show X as a highly valuable ‘gateway’ title that is effective at converting trial users into loyal subscribers. The platform can then promote this show more heavily to new signups.
- Evaluating Marketing Campaigns: A cohort of users who signed up via a specific marketing campaign (e.g., a TikTok promotion) can be tracked to see if they are as valuable in the long term as users who signed up through other channels.