Cohort Analysis for Mobile Apps

You spend a fortune on marketing your mobile app. You even get a lot of people to install it.

But what if none of the people open your app? All your efforts for nothing. Sigh :(

In the digital spectrum, the lack of engagement by the old users is often masked by the impressive growth of new users - an impending disaster.

This is where measuring user engagement becomes key. You need to be sure whether the user engagement is actually improving or if the numbers are improving just because of growth.

And the best way to do this is through Cohort Analysis.

This article will take you through all the important things you need to know about Cohort Analysis for your mobile apps.

Let us begin!

What is Cohort Analysis?

In simple terms, a cohort is a group of people with similar characteristics. Along that lines, the Cohort Analysis is a kind of behavioral analytics where users are grouped based on their similar characteristics to better track and understand their actions. This analysis allows you to ask specific, targeted questions that will help you make informed decisions. This, in turn, will improve engagement and reduce churn.

Benefits of Cohort Analysis?

The following are the most important benefits of cohort analysis.

You can understand how customers behave over time

Using cohort analysis, you can get a clear understanding of how your app’s users are behaving over a time period. If users are not segmented by cohorts, a company’s growth or decline will fog the impacts of efforts like personalization.

You can better understand the churn rate

Understanding churn rate is important to bring back the people who have stopped using your app and to make sure new users don't leave. Implementing cohort analysis can help you maximize your retention rate.

Identify segments to create personalized experiences

You can't provide personalized experiences to customers if you don’t segment them properly. Cohort analysis can help you do so. Cohort analysis will lead you to ask questions like “What personal experience should you provide for someone who hasn’t used the app in a few weeks versus someone who uses your app once in a few days?”

Track customer life cycle

Cohort analysis lets you track the customer life cycle of specific groups. This approach gives you a clearer view of how and when users engage with your app. This, in turn, lets you determine customer lifetime value.

How to create cohorts?

The breaking up of users into groups can be done in two ways.

Acquisition Cohorts

This approach divides users by when they first installed the app. You can create and track cohorts by the day, weeks, months, or years. By accurately measuring the retention of these cohorts, you can find out how long people continue to use the app from the first time they started using it.

Behavioral Cohorts

This approach divides users based on their behavior within a time period. Sets of actions include app installs, app uninstalls, app launches, transactions, and more. A combination of these individual actions can also be considered.

Cohort analysis and customer retention rate

When it comes to mobile apps, Cohort Analysis is most commonly used to identify reasons why users leave and what actions can be taken to prevent them from leaving. In short, it can be used to calculate Customer Retention Rate (CRR).

The Customer Retention Rate can be calculated using this formula CRR = (E-N)/S X 100

Where,

• E is the number of customers at the end of the time period
• N is the number of customers acquired during that period
• S is the number of customers at the beginning of the period
  

To measure customer retention, subtract the number of app users remaining at the end of the period from the number of app users from the beginning of the period. This can give a realistic picture of the retained customers. Divide the result by the number of customers at the beginning to find the percentage of customers who have been retained since the beginning.

A higher CRR means higher customer loyalty. By benchmarking the CRR with the industry average, you can find out where the app stands from a customer retention standpoint.

Cohort Analysis and other key metrics

Other than CRR, there are other metrics that can be used to analyze data. Cohort analysis can be used to bring attention to important patterns and metrics to come to intelligent conclusions and solutions. The below metrics can help you differentiate cohorts, assuming that yours is an app that sells products or services.  

Repeat Rate

This metric helps track users who interact/purchase/transact with your app repeatedly compared to users who only use the app once. To calculate the Repeat Rate, simply divide the number of customers who have made a purchase more than once by the total number of customers.

Orders per customer

The name of this metric is self-explanatory. It helps ascertain the number of orders placed by one customer. An increased number of orders per customer indicates a strong retention rate for the app.  

Time between orders

This metric measures the average duration between orders placed by customers. The optimum value varies depending on the industry, type of product/service, and the business model the app owner follows. This metric can aid in sending out targeted notifications and emails regarding promotions to dormant users. It can also help in reactivating existing users.

Average Order Value (AOV)

This metric is the key to identifying high-value spenders and loyal customers of the app. Separating them from the rest of the lot will help you strategize marketing campaigns to earn customer trust and build brand loyalty.

Conclusion

This article has given you an in-depth view of cohort analysis and why it is significant for an app’s long-term success. If you are an app owner, cohort analysis should be an important tool in your arsenal.

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