Cohort Analysis: Explained

Hey there reader, welcome to my latest rant about business analytics! Today's topic is one that is particularly close to my heart: cohort analysis.

I've worked in finance and analytics for years, and I often see companies ignoring cohort analysis or doing it poorly. But once you understand what it is and how to use it, cohort analysis can be a powerful tool for unlocking insights about your business and making data-driven decisions that lead to growth.

So, what is cohort analysis?

Simply put, a cohort is a group of people who share a common characteristic or experience. In business, a cohort can refer to a group of customers who signed up during a specific time period, or a group of employees who started working for the company around the same time, or any other group of people who can be defined by a common experience or trait.

Cohort analysis is the process of analyzing the behavior and characteristics of these groups over time, with the goal of identifying patterns and trends that can be used to improve business outcomes.

For example, let's say you run an online store that sells pet products. You could use cohort analysis to track the behavior of customers who made their first purchase in January, and compare that to the behavior of customers who made their first purchase in February, March, and so on.

By looking at metrics like repeat purchases, average order value, and lifetime value, you can start to identify which cohorts are the most valuable to your business, and make data-driven decisions about how to better target and retain those valuable customers.

Why is cohort analysis important?

Cohort analysis is important because it allows you to go beyond just looking at aggregate data, and instead focus on the behavior of specific groups of customers or users.

By breaking down your customer base into smaller groups, you can start to identify patterns and trends that you might otherwise miss. You can also start to answer more specific questions about your business, like:

• Which marketing channels are most effective at acquiring high-value customers?
• How long does it take for new customers to become profitable?
• Which product categories are most likely to lead to repeat purchases?

How to do cohort analysis

So, now that we've established why cohort analysis is important, let's talk about how to actually do it.

There are a few key steps to follow:

1. Define your cohort: Decide what common trait or experience you want to use to group your customers or users. This could be sign-up date, first purchase date, geographic location, age, or any other characteristic.
2. Align your data: Make sure your data is aligned by the common trait you've defined. This means you'll need to identify the cohorts within your data set, and create a table or spreadsheet that separates the cohorts.
3. Choose your metrics: Decide what metrics you want to use to analyze your cohorts. These could include repeat purchase rate, average order value, customer lifetime value, churn rate, or any other metric that is relevant to your business.
4. Create your cohort analysis: Once you've defined your cohorts, aligned your data, and chosen your metrics, it's time to create your cohort analysis. This can be done using a spreadsheet or a dedicated cohort analysis tool.
5. Draw insights: Finally, it's time to draw insights from your cohort analysis. Look for patterns and trends among the cohorts, and use these insights to make data-driven decisions about how to improve your business outcomes.

Conclusion

Cohort analysis is a powerful tool for unlocking insights about your business and making data-driven decisions that lead to growth. By understanding what cohort analysis is, why it's important, and how to do it, you can start to unlock the full potential of your business data.

So, there you have it, folks! Thanks for sticking with me through this rant about cohort analysis. I hope you found it informative and entertaining. Now go forth and analyze those cohorts!