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June 30, 2022

If you’re looking to track your customer retention rate and identify areas of improvement, a cohort retention analysis is a powerful tool. I learned this firsthand when I was working as a marketing consultant for a small business. The owner wanted to know why his customers were leaving and how he could keep them from churning. After doing some research, I recommended that he perform a cohort retention analysis.

The results were eye-opening! We were able to see which cohorts (groups of customers) were more likely to stick around and which ones tended to leave after only making one purchase. This information was invaluable in helping the company improve its customer retention rate. If you’re thinking about using a cohort analysis in your business, read on to learn more about the benefits and how it’s done

What is a Cohort Retention Analysis?

A cohort retention analysis is a tool used by businesses to measure customer loyalty and engagement.

By tracking the behavior of a group of customers over time, businesses can identify patterns and trends in customer behavior and make decisions about how to improve customer retention.

What is a Cohort?

A group of people with common traits is called a “cohort”.

Cohort analysis is a powerful tool that allows you to group your users based on shared characteristics. This type of behavioral analytics provides insights that can help reduce churn and increase revenue. By asking targeted questions and making informed product decisions, you can improve your business outcomes.

You could call this customer churn analysis.

To figure out why users stop using your app, you have to ask three questions:

  • Who is engaging with your app—and who isn’t?
  • When do they churn?
  • Why do they lose interest?

Cohort analysis is the key to answering these questions. By tracking groups of users (cohorts) over time, you can see how they interact with your app and identify patterns in user behavior.

The two most common types of cohorts are:

  • Acquisition cohorts: Groups are divided according to the date of sign-up
  • Behavioral cohorts: Groups are divided according to actions in your product

Acquisition cohorts help you understand who your customers are and when they joined your company. Behavioral cohorts let you explore why.

Let’s take a closer look at how to analyze cohorts.

Cohort Data

Comparing how user acquisition or retention changes over time can be a great way to understand how your users are behaving. By looking at users who were acquired at different times or by looking at which users have stuck around, you can gain valuable insight into your customer base.

But, how to break up your users into cohorts for statistical analysis? There are two ways to do this.

  • Acquisition Cohorts: You can separate your users into groups based on the day, week, or month they signed up for your service. For app customers, you can break them down into groups of users who opened the app on a specific date.

By measuring how long these users use the app from when they first installed it, you can determine their retention rate.

  • Behavioral Cohorts: Divide your users by the actions they’ve taken (or not taken) in your application. These could include, for example, installing the app, launching it, uninstalling it, making a purchase, or some combination of these.

Here, a cohort is a group of people who performed specific activities within a set amount of time. For example, you can track the first 3 days of a user’s activity. You can then see how long people stay in your application after performing those particular tasks.

Let’s look at how we can use both behavioral and cohort analysis to determine what our users are doing and when.

How Cohort Analysis Helps Product Teams

By tracking how different groups of users interact with your product over time, you can identify which features are most popular with each group and make sure that your product is meeting the needs of all of your users.

Identifying groups of users with abnormally low retention can help you figure out which characteristics or behaviors are correlated with high customer turnover.

Here is how it is being used.

When analyzing user behavior, cohort analyses help identify how new users behave within the first few weeks of using a product.

Cohort analysis is an important tool for product teams because it can help them increase adoption by understanding how groups of users interact with the product. By analyzing how different groups respond to different features, marketing initiatives, and support efforts, cohort analysis can uncover patterns that can guide teams in figuring out when to provide support, send emails, or offer in-product tooltips.

This data can then be used to measure the success of each approach. The marketing team can also use this information to understand how each new feature has impacted the user experience and adjust the features in their product’s roadmap.

As people continue to use your product over weeks and months, cohort analyses can reveal how long they remain engaged, and when they are likely to leave.

With product analytics, you can see which groups perform certain actions, such as logging into a session or engaging with a specific feature, before they stop using your product.

They can then dig further into the characteristics of the lowest-performing groups to determine the cause of their attrition.

Conclusion

A cohort retention analysis is a powerful tool that can help you track customer retention rates and identify areas of improvement. If you’re thinking about using one in your business, be sure to keep the benefits in mind. And remember, it’s not just about keeping customers around – it’s also about making sure they’re happy with their experience!

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