In this post, you’ll learn definition and benefits of Cohort Analysis. Let’s get started!
Cohort Analysis: What is it?
Cohort analysis is a data analysis technique used to compare similar groups over time.
Cohort Analysis: Why use it?
Here’s the basic idea: Businesses are dynamic and thus are continuously evolving. A customer who joined previous year might get a different experience compared to customer who joined this year. This is especially true if it’s a startup or tech company where the business models change (or Pivot!) often. You might miss crucial insights if you ignore the dynamic nature of businesses in your data analysis. To see if the business models are evolving in right direction, you need to to use cohort analysis to analyze similar groups over time – Let’s see an example to make it a little bit more clear for you.
You decide to analyze “Average Revenue per Customer” by Fiscal Year and came up with following report:
It seems that your “Average revenue per customer” is dropping and you worry that your investors might freak out and you won’t secure new investments. That’s sad! But hold on – Let’s put some cohort analysis technique to use and look at the same data-set from a different angle.
In this case, you decide to create cohorts of customers based on their joining year and then plot “Average Revenue Per Customer” by their year from joining date. Same data-set but it might give you different view. See here:
It seems you’re doing a good job! your latest cohort is performing better than previous cohorts since it has a higher average revenue per customer. This is a great sign – and you don’t need to worry about your investors pulling out either and well, start preparations to attract new investors – all because of cohort analysis! 🙂 WIN-WIN!
Conclusion:
As you saw, cohort analysis is a very powerful technique which can help you uncover trends that you wouldn’t otherwise find by traditional data analysis techniques.
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Author: Paras Doshi
Is this really good news? I see only declining revenue. My conclusion would be that 3 out 4 cohorts are disappointed in our first year performance with little or no recovery.
The good news is that for the latest cohort the decline is slower compared to last year. Also, note that it’s not “revenue” but “average revenue per customer” and it’s a common scenario where your users might not spend same amount of dollars in second year as they did in their first year. I hope that helps.