What is cohort analysis?
Cohort analysis is the process of separating users into groups of people (cohorts) who share common characteristics or attributes in order to analyze their customer behavior.
It usually involves tracking how the specific characteristics of a cohort change over time, which can give you important insights into:
- how your marketing campaigns are performing,
- your user engagement,
- your churn rate,
- and more.
How to use cohort analysis in business analytics?
Cohort analyses can be used for many different purposes depending on how you create specific cohorts and what behavior you’re interested in tracking. In the best cases, cohort analysis can give you actionable insights into the performance of your ecommerce business.
You can divide users into cohorts based on a number of characteristics. On the most basic level, you can consider all your visitors during a certain time period as one cohort, but you can also create cohorts based on:
- people who share demographic characteristics,
- new customers,
- visitors who arrived from the same traffic source,
- and so on.
Once you’ve created your cohorts, you can analyze the behavior of each of these cohorts based on many metrics like conversion rates, page views per user, revenue per user, sessions per user, or transactions per user.
There are cohort analysis tools like Google Analytics that generate basic cohort analysis reports (for example, cohorts based on date of first visit with user retention rate).
Advanced cohort analysis tools provide further segmenting options that allow you to create cohorts based on the many factors discussed above.
What can you learn from a cohort analysis report?
When you perform cohort analysis, you can test out how well you’re converting traffic into sales and what your typical customer lifecycle looks like. Depending on what you’re focusing on, you can learn how specific cohorts tend to behave and make purchases.
Here are three examples of insights you can gain from cohort analysis:
- Analyzing trends in cohort spending can help you gauge how the value of the average customer changes throughout the customer lifecycle. This means you’ll be able to see when your customers tend to stop buying from you and see how your customer lifetime value changes over time.
- You can use cohort analysis to find out who your most loyal customers are and then encourage them to stay with your company longer.
- Cohort retention analysis and acquisition cohort analysis are useful practices for reducing early customer churn. Cohort analysis charts will indicate the period of time after which customers tend to churn.
By comparing different user groups, you can identify trends and discover which price points, marketing strategies, or discount offers lead to the best results.