Unlock the Secrets of Cohort Analysis: A Comprehensive Guide to Improving Customer Retention

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Are you looking to understand your customer’s journey better and increase customer retention? Cohort analysis is a powerful tool that can help you achieve this goal. It gives you insight into the behaviour of different groups of customers over time, allowing you to track customer loyalty trends and identify improvement opportunities. 

This comprehensive guide will cover the basics of cohort analysis, how it can help you improve customer retention, and the steps you need to take to get started.

What is cohort analysis?

Cohort analysis is a statistical technique that allows you to analyse the behaviour of different groups of customers (cohorts) over a specified period of time. It is often used by e-commerce brands to understand how customer behaviour changes over time and to identify trends or patterns in that behaviour. By grouping similar customers together and monitoring their behaviour, you can gain insight into customer loyalty patterns and identify potential improvement opportunities.

For example, an e-commerce brand might use cohort analysis to understand how customer spending habits change as they age. The brand could group its customers into cohorts based on the year they made their first purchase and then tracked each cohort’s average spending over time. This could help the company identify trends in customer spending and make informed decisions about how to target its marketing efforts.

Different types of cohort analysis

There are a few different types of cohort analysis that you can use to track user retention and behaviour:

  1. Time-based cohort analysis: This involves dividing users into groups based on when they started using your product or service and then tracking their retention and behaviour over time.
  2. Acquisition-based cohort analysis: This involves dividing users into groups based on how they acquired your product or service (e.g. through an ad campaign, referral, etc.) and then tracking their retention and behaviour over time.
  3. Behaviour-based cohort analysis: This involves dividing users into groups based on their behaviour within your product or service (e.g. frequent users, power users, etc.) and then tracking their retention and behaviour over time.
  4. Demographic-based cohort analysis: This involves dividing users into groups based on their demographic characteristics (e.g. age, gender, location, etc.) and then tracking their retention and behaviour over time.

By using different types of cohort analysis, you can get a more comprehensive understanding of your user base and allow you to cater to their needs and requirements. 

How can cohort analysis improve customer retention?

Cohort analysis provides valuable insights into customer behaviour that can help you better understand the customer journey and optimise your marketing efforts. By tracking customer loyalty patterns over time, you can identify potential opportunities to improve customer retention. For example, you may notice that a certain cohort is becoming less loyal over time, which could indicate the need for a targeted retention campaign. You can also use cohort analysis to identify which customers are most likely to churn and focus your efforts on retaining them.

Here are some of the ways that you can leverage cohort analysis to maximise customer retention:

  1. Identify key drivers of retention: By analysing your retention rates over time, you can identify the most influential factors in driving retention. This could include features or aspects of your product or service that users value or customer support experiences that positively impact retention.
  2. Targeted interventions: Once you have identified the key drivers of retention, you can focus on improving those areas to boost retention rates. This could involve implementing targeted retention campaigns to engage and retain your most valuable users.
  3. Personalisation: By using cohort analysis to segment your user base, you can tailor your retention efforts to the specific needs and preferences of different groups of users. This can be especially effective if you can identify sub-groups of users at higher risk of churning.
  4. Monitor changes in retention over time: It’s important to continuously monitor your retention rates and identify any changes or trends over time. This will help you understand how your retention efforts are impacting your user base and allow you to make timely adjustments as needed.

Thus, cohort analysis can help you gain valuable insights into customer behaviour and use this information to improve your customer retention rate.

Cohort analysis in action

Here are some examples of how businesses have used cohort analysis to improve customer retention rates:

  • Netflix: Netflix uses cohort analysis to identify customers at risk of churning. By tracking the behaviour of different cohorts over time, they can identify which customers are most likely to cancel their subscriptions and take steps to keep them engaged with their service.
  • Spotify: Spotify uses cohort analysis to understand how different customer segments interact with their service. By analysing the behaviour of different cohorts, they can identify which customers are most likely to remain loyal and target them with personalised incentives or discounts.
  • Amazon: With cohort analysis, Amazon tracks the behaviour of different customer segments and identifies which customers are most likely to remain loyal. They can then use this information to provide more personalised offers and discounts that will entice customers to stay engaged with their service.

Getting started with cohort analysis

While cohort analysis can seem daunting at first, it’s actually quite simple to get started. Here are some tips for getting started with cohort analysis:

 

  • Define your goals: Before you begin your analysis, take the time to define your goals and objectives. Do you want to understand customer loyalty patterns over time? Identify customers at risk of churning. Or find opportunities to offer personalised discounts and incentives? Knowing your goals enables you to create a more effective strategy.
  • Choose metrics that are relevant: When creating your cohort analysis, make sure to choose metrics that are relevant to your goals. This will ensure that the data is meaningful and can be used to inform your decisions.
  • Use visualisations to analyse data: Using visuals such as graphs and charts can help you make sense of the data more quickly. Visualising your data will make it easier to identify patterns and draw meaningful insights from them.
  • Automate when possible: Automation can save you time and effort while performing cohort analysis. Wigzo can help you automate the process, allowing you to focus on making decisions based on the data.

Cohort analysis can be a powerful tool for improving customer retention rates, but it requires careful planning and data collection. With the right strategy, you can use cohort analysis to gain valuable insight into your customers’ behaviour and use this information to optimise your marketing efforts and improve customer retention.

Key metrics to focus on while using a cohort analysis

When using cohort analysis to track user retention, here are the key metrics that you should focus on:

  1. Retention rate: The percentage of users who continue to use your product or service after a certain period of time.
  2. Churn rate: This is the opposite of retention rate, and it measures the percentage of users who stop using your product or service within a certain period of time.
  3. The time between orders: This metric tracks how long it takes for users to place their next order.
  4. The average revenue per user (ARPU): This measures the average amount of money each user generates for your business over a certain period.

Tracking these metrics over time allows you to identify trends and patterns in user behaviour and make informed decisions about improving retention and growing your business.

Try Wigzo 

Wigzo’s Cohort Analysis tool is designed to help you quickly and easily identify trends in customer behaviour. With it, you can segment customers into different cohorts and track their behaviour over time. This will enable you to gain insight into which customers are most likely to stay loyal and target them with personalised offers or discounts. Wigzo also provides powerful reporting tools that will help you understand the performance of different cohorts, enabling you to make informed decisions on optimising your customer retention strategies.

So, if you want to take advantage of cohort analysis and unlock the secrets to improving customer retention, try Wigzo today!

Anshika Singh

Anshika Singh

An economist by degree and content writer by choice, she is currently working as a content marketing writer at Wigzo Technologies. In her spare time, she loves to binge-watch and spend time with her dogs. Linkedin

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