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Cohort analysis is a powerful tool for businesses that use subscription-based revenue models. This type of analysis allows businesses to group their customers into "cohorts" based on a common characteristic, such as the sign-up date, and track the behavior of each cohort over time. It should be noted that cohort analysis is not a tool unique to SaaS companies.
There are two main types of cohort analysis:
Acquisition cohorts are much more high-level than behavioral cohorts, thus they provide less granular information. Acquisition cohorts can help companies understand how larger groups of users are reacting to product updates and releases, and provide insight into how a business is trending, but they cannot help companies understand which types of users engage with which features.
On the contrary, behavioral cohorts are much more granular. They can help companies understand the differences between users based on their characteristics such as industry vertical, acquisition channel, job titles, or even the amount of time they spend using a product or service each day.
By looking at how a cohort behaves over time, businesses can identify trends and patterns that may indicate areas for improvement.
Cohort analysis can also be useful for identifying customer segments that are more valuable to the business and are more likely to make repeat purchases or refer new customers. With such granular information, businesses can prioritize the allocation of resources and focus on retaining and engaging the most valuable customers as opposed to spending time and resources on a cohort of customers that are more likely to churn.
Take a look at the above graphic showing the retention rate of quarterly cohorts. Let’s say a SaaS company provides project management software to growing startups. The company separates its customers into cohorts based on sign-up date (acquisition cohorts), and their behavior over time (behavioral cohorts). At the end of Q3, the company begins to notice that a cohort of customers who signed up in the first quarter of the year has a higher retention rate compared to customers who signed up in the second quarter.
This information could then be used to identify potential reasons for the difference in retention rates and deploy engagement campaigns to improve retention for the second quarter cohort.
Overall, cohort analysis is a valuable tool for SaaS companies looking to improve customer retention and engagement. By tracking the behavior of different customer segments over time, businesses can gain valuable insights into their customers and make more informed decisions about their marketing and product strategy.