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Using Customer Cohort Analysis to Optimize the Customer Experience

The true success of marketing is not to promote one-off transactions, but to build customer relationships that last as long as possible. This makes customer retention a major goal for any marketer.

But why do marketers need to focus on retention as a measure of marketing success?

First of all, acquiring new customers costs five times more than retaining existing ones. In addition, companies with low customer retention rates quickly run out of new customers, eventually falling into a downward spiral of negative returns. This is where cohort analysis comes in and helps to provide a targeted experience for customers.

In this article, you will learn more about customer cohort analysis, its importance and how to use it for your business.

What is Customer Cohort Analysis?

Customer cohort analysis is an important process that enables businesses to track and investigate user engagement over time. A “cohort” is a group of users who perform a particular set of events over a particular period.

Cohort analysis allows you to ask more specific and targeted questions, make informed product decisions, reduce churn and dramatically increase sales by helping you determine which types of users are most likely to convert. Cohort analysis also helps you to find the best or worst cohort by comparing behaviours and indicators over a period of time. Once you have this data, you can ask targeted questions about your product and make decisions to reduce churn and optimize revenue generation.

Retention by Monthly Cohorts

Cohort analysis consists of four main phases:

  1. Determine the question to answer. The purpose of the analysis is to capture actionable information based on the actions you can take to improve your business, products, user experience, sales, and more. To ensure this, it is important to ask the right questions.
  2. Define metrics that will help you answer your question. Proper cohort analysis requires identifying an event, such as making the payment for a purchase, and specific attributes, such as user payment amount.
  3. Define the specific cohorts that are relevant. You need to define which cohorts are relevant by categorizing users based on certain characteristics such as the date each customer started using the product. 
  4. Perform the cohort analysis.

Why Do You Need to Use Customer Cohort Analysis?

Cohort analysis is a better way to examine your business’ data to improve your customer experience. Most organizations use cohort analysis to track and improve retention rates and reduce churn rates for users of services or products.

Cohort analysis is not limited to a single industry or feature. For instance, e-commerce companies can use cohort analysis to identify products with high potential for sales growth. In digital marketing, it can help you identify high-performing web pages based on the time you spend on your site, conversions, or sign-ups. Product marketing teams can also use customer cohort analysis to identify successful feature adoption rates.

Cohort analysis is widely used in the following industries:

  • eCommerce
  • Online gaming
  • Cloud software
  • Website security
  • Digital marketing

In all of these industries, cohort analysis helps identify how many customers are likely to remain active users in the next period of measurement. This brings us to the calculation of CRR.

Customer retention is calculated using the following formula: CRR = ((E-N) / S) X100 This formula has three elements:

  • E-Number of customers at the end of the period.
  • N-Number of customers acquired during this period.
  • S-Number of customers at the start of the period.

To measure customer retention, determine the difference between the number of customers acquired during the period and the number of remaining customers at the end of the period. This gives you an idea of how many existing customers you have. Divide the result by the number of customers at the start of the period for which you’re making the calculation to find the percentage of customers that are retained from the beginning. This gives you the customer retention rate.

The higher the CRR, the higher the customer loyalty. By comparing your company’s CRR to the industry average, you can see where you stand in terms of customer retention. It takes the efforts of the customer success team to influence the customer journey and increase customer lifetime value, retention, and customer loyalty. If the CRR shows that improvements are needed, corrective action can be taken with the help of data from customer cohort analysis.

How to read a cohort analysis

Metrics to Use for Cohort Analysis

Cohort analysis is one of the most useful ways to experiment for your business. As a marketer, you can launch an advertising campaign and use cohort analysis to measure a few things such as the most effective marketing channel, customer engagement, conversion rate etc.

There are several metrics that you can use such as:

Seasonal (Monthly) Revenue Growth: Companies typically calculate revenue growth on a monthly basis. To do this, subtract the first month’s sales from the second month’s sales.

Then divide what you get by your first month’s revenue and multiply by 100 to get the percentage. The monthly revenue cohort analysis shows you the monthly sales that the cohort generated during its lifetime. It allows you to see if the new cohort is worth more or less than the previous one.

Customer Lifetime Value: Customer lifetime value (LTV) is the gross profit that a customer generates or has generated over a lifetime. Customer LTV calculation is one of the best ways to build an effective acquisition strategy. This is because knowing the expected LTV allows a company to determine how much it can spend to acquire a new customer and make a profit. Tools like HockeyStack can help you uncover insights for LTV so you can acquire more customers with customizable dashboards for your business.

Cohort analysis and customer LTV can be used to accurately assess how a group of users/customers behaved throughout their lives. These metrics will change the way you view the value of your customer base and provide measurable data. You can use this data to determine what type of retention strategy, branding, and targeting you need to proceed with.

How to Measure CLV

Customer Churn: Customer churn is the percentage of customers who have stopped using a company’s products or services during a specific time period. The churn rate can be calculated by dividing the number of customers lost during the period by the number of customers you had when you started the period. Cohort churn analysis looks at how long each cohort has retained its customers for its lifetime. A well-functioning cohort will reveal what to duplicate in the future, and a high churn rate will help you decide which strategy to change.

Customer Retention Rate: Customer retention refers to the percentage of customers who stay in the company for a period of time. It is an important metric for virtually all B2B and B2C businesses. In general, the higher the customer retention rate, the higher the customer loyalty and the longer the business retains more customers, making the business more successful.

How Cohort Analysis Can Help You Optimize the Customer Experience

Weekly Cohort Analysis

Cohort analysis demonstrates how your consumers’ behaviour changes over time, which helps you understand and target them better. If you group users into cohorts, for example, by month or quarter, you can see which group has the highest retention and other key metrics. 

By using cohort analysis to see which groups perform best, and then looking at what they have in common, you can identify the characteristics that are most likely to lead to product success.

The better you know your customers, the more informed decisions you can make about how to reach them and what features to implement into your business. For example, by looking at the success of your top cohorts and determining what made them successful, you can reach similar audiences and create features that appeal to more customers.

Although customer cohort analysis is complex and requires a lot of time, the results of this analysis will be extremely helpful in understanding customers, seasonality, and changes in your business.
Customer cohort analysis helps you better understand your users and can gather insights for your business. With tools like HockeyStack, you can understand which features generate the most revenue so you can focus on marketing those features to your existing customers. By measuring customer retention rate as cohort analysis, you can see the value of each customer group and learn more about how to retain customers for long-term growth.


What is an example of cohort analysis?

Take the example of an e-commerce company that generates large volumes of customer data. The data includes details of products purchased, customer spending, click-through rates, product ratings, product margins, and other metrics.
Cohort analysis done by e-commerce companies will show them behavioural patterns in the customer lifecycle. This helps prepare better targeting strategies to increase customer retention and engagement.

What are the types of cohort analysis?

There are two major types of customer cohort analysis:

1. Acquisition cohort analysis: This cohort divides users based on when they purchased or subscribed to a product. Depending on your product, user conversions can be tracked daily, weekly, or monthly.
2. Behavioural cohort analysis: This type of analysis focuses on grouping user behaviour based on the activities they perform over a certain period of time.

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