Customer churn is bad. It is clear now. Customer retention is important for growth. Making your customers stick around for a while is recommended. To do that, there are a number of customer retention strategies. One of the primary things to reduce churn is to diagnose the problem. Certain techniques in data analytics such as cohort analysis can help.

What is Cohort Analysis?

A cohort is a bunch of users who have similar characteristics. Cohort analysis is one that helps track user engagement over time. Cohorts are ones where the attributes and experiences are shared. It helps understand whether user engagement is actually improving growth or not. Cohort analysis important to distinguish between engagement metrics and growth metrics. It is another form of customer churn analysis. With specific questions, one can make decisions that will improve revenue.

Cohort analysis works on three basic questions-

• Who is using the app?
• Why are they losing interest?
• When are they looking to churn?

Types of Cohort Analysis

Acquisition Cohorts

In this type of cohort analysis, users are divided based on when they were acquired. It can be tracked daily or monthly. You can understand how long people use your app from the point of starting. This depends on one product to another. One type of app can track its acquisition cohorts daily. Monthly acquisition cohorts can be tracked for subscriptions.

From this data, trends where churn can happen are received. This will help in understanding customer churn patterns and finding plugs to reduce it.

Behavioural Cohorts

Behavioural cohorts are based on the activities that users undertake in a given span of time. This also depends from product to product. A health app will detect changing behaviour everyday. For another app, a quarterly tracking would suffice to understand user behaviour.

From this data, a quantitative, systematic approach can be developed to re-engage your users again.

Need for Customer Cohort Analysis

Cohort analysis is a great way of looking at data. It is helpful to spot potential for growth. The analysis can also identify how feature adoption and churn rates are for a specific set. It helps companies identify why customers are leaving.

Some of the benefits of running a cohort analysis include-

• Identifying activities, features, or changes that work for customers
• Chalking or predicting future behaviour
• Using present data as a benchmark for future actions
• Planning user onboarding activities
• Making sure that marketing activities are data-driven

This information will be helpful in maximising customer retention.

By religiously relying on customer cohort analysis, it is possible to improve customer retention rate.

Customer Retention Rate = {(E-N)/S} multiplied by 100

Where, E= number of customers at the end of the time period

N = Number of customers onboarded in that period

S= number of customers to begin with

With this analysis, it is possible to take corrective measures that will improve CRR.

How to Increase Customer Retention Rates using Cohort Analysis?

Cohort analysis helps companies understand why, when, and how people buy things and why they keep coming back. There is data involved that shows what works for loyal customers and orders. You can understand various factors that affect retention.

1. You can determine what drives retention by categories such as month of purchase, coupons or promotions. Insights such as what keeps them invested during the holiday season or how discount coupons work will be helpful in devising a marketing strategy.
2. With cohort analysis, users can set templates for future behaviour. This can be set for a time stamp at a future period. Take the Black Friday season for example. Some companies may think it is not a great time to promote or market their offerings. A cohort analysis can justify their campaigns or question why they don’t exist.
3. Another great thing is cohort analysis reports is, you will know when to send the customer the next email or push them for repurchase. This makes it easy to push for upselling or cross–selling. This also shows customers who are looking to churn.
4. Make your products stand out. Cohorts enable you to manage what makes people get hooked on to a product. You can understand which part of the audience likes the product and why another does not.
5. Cohort analysis reports also allow you to know which campaigns are successful. With that, you can reuse them for other customers and reduce marketing effort. This is like A/B testing making sure there are wins with abandoned carts.
6. Personalisation is possible at scale. Going back to the definition of cohorts, they are smaller similar segments. It is possible to tailor communication and create meaningful messages. For example, deep discounts can be someone’s driver to purchase more. For others, it can be a free top up.

Cohort analysis can be done via google analytics. There are specific tools available. However, cohort analysis through Google analytics is considered a fair representation.

Are Churn Analysis and Cohort Analysis Same?

Many people get confused and opine that churn analysis and cohort analysis are the same. That is not true. The underlying interest is to understand customers, but they are different.

Bottom Line

Instead of assuming facts about customers, having information backed by data helps. A/B testing cohorts can help you understand what works and aid in reducing churn. With cohort analytics, you will understand where to hit exactly with customer retention strategies. This coupled with an intelligent customer success platform will enable customer retention in the long run. A single platform that tracks, manages and keeps customers invested in your company. SmartKarrot it is.

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