What is cohort analysis? The beginner’s guide
You’ve achieved your first thousand customers. Congratulations! What do you know about them? What do they need now? Moreover, what will you offer them (and when) to tie them closely to your brand?
To answer these and other important questions, we suggest you try cohort analysis. It will be best for your business if you learn how to apply it as soon as possible to make your retention measures more data-driven.
Table of contents
- Benefits of cohort analysis for businesses
- How to conduct cohort analysis
- Improving retention for real business results
- Wrapping up
In marketing, cohort analysis is a method of processing behavioral data on customers collected from a website, service, app, or game. This analysis creates segments of customers based on shared characteristics, actions, and experiences within a certain period. These segments, called cohorts, are ready-to-use audiences for both lead generation and making decisions to improve your funnel. Cohort analysis is also a great way to research your customer lifecycle and connect it with specific customer actions. While conducting cohort analysis, you’ll find out how user engagement fades over time.
If you want to dive deep into the theoretical part of this theme, read our advanced guide to cohort analysis in Google Analytics and Google Sheets.
After conducting this analysis, you’ll understand the true reasons for your business growth. Are you growing because of an increasing number of new customers or because you’re rekindling the desire to buy in your existing customers? If you know how to read the results, it’s enough to build segments once based on quality data in order to find true insights on customer engagement.
Benefits of cohort analysis for businesses
Predict and increase your LTV
Lifetime value (LTV) is the revenue a company receives from a customer over the course of their relationship. You’ll clearly see when your customers stop buying from you and will be able to calculate LTV for each customer segment to make precise predictions. With this information, you can better plan your advertising expenses, tuning your campaigns for each segment based on acquisition channel.
Retain your best customers
You can use cohort analysis to find out who your most loyal customers are and then encourage them to stay with your company longer. It will be cheaper than acquiring new customers, in any case.
Improve A/B testing
Standard A/B tests won’t tell you how a new design or any other change may affect conversions in the long run. To find out, create a cohort based on interactions with a new design. Then compare its conversion rate with cohorts that didn’t interact with the new design. In this way, you’ll see how the new design affects conversions.
Research app performance
Cohort analysis is a favorite method of mobile app analytics, showing user interest in an app, activity inside an app, etc. It helps app marketers understand bottlenecks and places where users have difficulty using an app so developers can improve it.
Consider OWOX BI as both an advanced solution for cohort analysis and part of your business analytics (BI) toolbox.
How to conduct cohort analysis
Here are five simple steps to conduct cohort analysis:
- Access behavioral data. To make your research results reliable, it’s important to use raw data rather than aggregated or sampled data.
- Choose a set of common characteristics you want to analyze. This set should be extracted from your data store and consist of fields like date of first purchase, customer ID, time of purchase, amount of purchase, a channel where the user came from, etc.
- Place extracted data from your data store in a separate table using Google Sheets or a similar tool.
- Define customer cohorts. Choose an identifier (a period or characteristic) for grouping cohorts. Examples: date of first purchase, amount of purchase, channel attribution.
- Choose the main parameter you want to observe over a certain time period (days, weeks, months). It may be one of your KPIs, such as ROI or CAC.
- Build a pivot table like this one:
Don’t forget to add a cohort size column where you’ll enter the total number of customers in each segment.
- Optionally, visualize your results in graphs. Your cohort analysis report is ready!
That’s pretty much it. In tools like Google Analytics, you can get a ready pivot table and graph. That’s handy, but it means you lose control over your data (which might be partial or sampled) and have less flexibility when setting up parameters. The quality of your data defines the reliability of your research results, so choose your analytical tools and technologies carefully.
Be sure to try OWOX BI to conduct cohort analysis based on comprehensive data and flexibly adjust parameters.
Whatever key metrics you choose to observe, you’ll find they change over the customer lifetime along with how your marketing efforts influence your customers. Depending on what your main research interest is and what metrics you choose, your cohorts can be classified:
- Based on the acquisition date. You can group customers according to the time they first used your service or first bought from your online store.
- Based on actions. You can group customers by actions they’ve taken (or haven’t taken) such as launching a shopping app or using a search bar.
Both of these types of classification are used to decrease the churn rate.
4 ways to evaluate the effectiveness of media advertisingDownload now
Improving retention for real business results
All methods of behavioral research are aimed at improving engagement and retention metrics. Cohort analysis gives you hints on when it’s the best time to remind customers about your company or product with a good-looking offer, who exactly is more likely to buy, and who the best buyers are based on their sequence of actions.
Analyzing your data from the acquisition point of view, you can see how long customers stay interested and continue to buy from you or continue to use your app or service. Segments based on behavioral characteristics let you understand if sending a particular offer changes the behavior of the whole cohort and enlarges its LTV.
To improve retention, you can apply the results of analysis in your bid management, personalized emails and offers, and ad targeting.
There are tens of segmentation methods, but cohort analysis is still one of the most underestimated among marketers. We encourage you to try this method of segmentation to get deeper insights on your customers’ behavior and make your relationship with your customers more intense and more valuable for both sides.
What is cohort analysis?The idea of cohort analysis is to divide users into groups based on certain criteria and examine how the behavior of these groups changes over time. Cohort analysis helps you understand how your marketing efforts affect key performance indicators: conversion and retention rates, LTV, ROI, CAC, etc.
How can you conduct cohort analysis?1. Access behavioral data
2. Define customer cohorts
3. Choose the main parameter you want to observe over a certain time period
4. Build a pivot table
5. Optionally, visualize your results in graphs
How can you read cohort analysis?To find general insights considering your customer lifetime, review the values for a column in your cohort analysis table. Then take the next column and compare its values with those in the previous column. To find additional insights about separate cohorts, analyze the values across your rows.