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Cohort Analysis: Beginners Guide to Improving Retention

 

 

 

Brand awareness is great, but experienced business owners know that the key to success isn’t about attracting new customers; it’s enticing existing customers to return. Cohort analysis is one way to measure how long users interact with your website or product before leaving and can provide valuable insights into areas where you need to improve features. 

What is a Cohort?

A cohort is a group of users who share common traits based on an event you track. So, for example, you could segment users who visit your website over a period of six months, by which week they visited. 

Why is Cohort Retention Important?

Simply put, cohort retention is important because it’s more expensive to acquire new customers than it is to keep your current ones. To know if you’re retaining specific cohorts, you need to track their behavior. This will give you two types of information: a) it will tell you whether or not you’re retaining users at all or whether new users are masking a major churn issue, and b) it will give you insight into how to keep those cohorts happy. 

What is Churn?

Churn is when a customer decides to stop using your product or services. This might mean they cancel a subscription, cease logging in, or stop buying from your company. A high churn rate is a red flag, even if you continue to reel in plenty of new customers.

What is Cohort Analysis?

Cohort analysis is the process of segmenting your website visitors or users into groups based on their characteristics or interactions within a specified time. Everyone in a cohort has made the same decisions and triggered the same events within the period or they share a trait such as a geographic location or belonging to an age group. To conduct cohort analysis you will put your parameters into your product analytics tool then check the data regularly for trends. 

The purpose of this analysis is to track cohort behavior over time. You’ll see whether you have a high churn rate among existing customers, or perhaps just those that come in on a trial offer. You’ll be able to see whether your consistent MRR reflects a good product or all-star sales and marketing teams (and perhaps a product with problems). 

Cohort Data Types

There are two different types of cohort data: acquisition and behavior. 

Acquisition cohorts are based on when a user initially created an account or first used your product. They provide information about how long a user continues to interact with your product or service after they start. Knowing when your users are leaving your software is essential to see where you need to improve. For example, if users are leaving after a day or two, that could mean they are having difficulty with onboarding or using your software or product. To solve this, you could provide more explicit instructions or offer onboarding assistance. 

Behavioral cohorts are based on behaviors that users have or have not performed within your software. For example, they can be people who visited your website but didn’t sign up for an account or users who signed up for your mailing list but didn’t purchase anything. If you monitor a cohort who visits your website, creates an account, and signs up for the mailing list within a small time frame. You’ll see how long they continue to log in to their account afterward or if customers who create accounts are more likely to purchase your products. 

Cohort Analysis Example

As we noted above, a standard cohort analysis looks at visitors to your website, both new and returning. Over six months, you can measure the number of new visitors who sign up with your website and how many of them returned to the website within that time. 

For example, if you begin measuring on the first day of May, you can see the percentage of new visitors returning in June, July, August, etc. This information can show you how long the average user spends utilizing your product whether it has legs. 

How to Do Cohort Analysis

Performing a cohort analysis requires four steps: 

  • Creating a question – What do you want to know about your users? 
  • Selecting the metrics – Do you measure how many consecutive days they log in to their account? The length of time between creating an account and purchasing a product?
  • Designing cohort identifiers – Are you segmenting your cohorts based on user behaviors or time?
  • Running the analysis – Pulling the data and visualizing it to find the answers to your initial question.

How to Build a Cohort Analysis Report Within Kissmetrics

In Kissmetrics, we offer various parameters to maximize the amount of helpful information in your cohort analysis report. The first step is to specify your date range for people performing the first event. Then you select the events to monitor, like visiting your website, logging into their account, utilizing your software, etc. 

The next option specifies the period of each cell. It lets you narrow the scope of the question, “After doing Event 1, how many hours, days, weeks, or months did it take these people to do Event 2?”. Then, choose whether you want to group people based on time or property. Time looks at when people performed the first event—property groups based on a property you set beforehand.

How to Use Cohort Analysis Data to Improve Retention

Essentially, cohort analysis watches how groups of people interact with your product and how those interactions change over time. Understanding the staying power of your product and how long users interact with it can help you determine where you need to improve it to increase user retention. 

Uncover Friction Points

Acquisition cohort analysis gives you the data to map out a retention curve. So, you can see approximately how many days, weeks, or months your average users stay connected with your product before churning. Typically, the most significant drop-off will be within a few days of starting use since many users may be casual visitors or may not want to continue dedicating time and effort. 

However, suppose the initial drop-off is larger than expected. In that case, it may reveal a friction point where customers may not be getting the information they need to set up the app or to utilize your product’s basic functions and are quitting out of frustration. 

Study Which Actions Drive Retention

Behavioral cohort analysis dives into the “why” of churn. If users who don’t interact with one of your product’s main features are the ones who quit within the first week, that’s an indication that they either need to be prompted to use it, or taught how. 

Alternatively, if users trying to pay with cryptocurrency regularly appear to cancel their subscriptions after the first month, that indicates your payment system may not be working correctly or is not optimized for that type of payment method. 

Benefits of Cohort Analysis For Your Business

Cohort analysis provides a variety of benefits for your business by providing deep insights into your user actions and behaviors. We explore a few of them in the sections below. 

Increase Customer Lifetime Value

Cohort analysis helps to establish your customer lifetime value, or CLV, since it gives you an idea of how many customers continue to engage with your company. Customers often spend the most money during their first month, but you can determine why customers decrease their spending and then take actions to potentially increase their CLV by addressing those issues found in a cohort analysis. 

Identify Loyal Customers

Cohort analysis doesn’t have to focus solely on the users who leave; it also identifies the people who stay. You might find that visitors who spend a week with an active account before purchasing your product are more likely to continue engaging with it for a long time, as opposed to visitors who buy on the same day their account is created. 

Improve Product Testing

When you roll out a new update, cohort analysis can show the percentage of users who decide to leave within a given timeframe after the update was released. Thus, you can test new features, bug fixes, and updates by monitoring when customers leave. 

Conclusion

Cohort analysis allows you to obtain detailed insight into your conversion funnel, how long users interact with your product, and when they start leaving. This information sheds light on actions you should taketo improve your product or website.

 

Visit Kissmetrics for more information about cohort analysis reports and how your business can benefit from them.

 

Sources:

  1. Cohort Analysis: Beginners Guide to Improving Retention
  2. Cohort Analysis: The Key to Improving User Retention for Your App
  3. Cohort Analysis: An Insider Look at Your Customer’s Behavior
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