Using cohorts in your customer analysis is a great way to start segmenting customers.
Cohorts can be confusing though. They sound a lot more advanced then they really are.
What is a cohort?
A cohort is simply a group of people who show similar behavior at the same time.
Everyone who buys an ice cream from the beach store can be added to the cohort “ice cream buyers” and “buyers today”.
In the context of customer analysis, a cohort is typically measuring customers who make purchases in a date range. In this case, the purchases are the behavior you’re measuring.
Everyone who ordered this month, last month, and the month before would be three different cohorts (groups) using that measurement.
One of the most valuable cohort groups for Shopify stores is which year and month a customer first purchases in. The fist purchase is the beginning of many behaviors that make a huge difference in their long-term customer behavior.
By grouping customers into a cohort you can measure how they respond (or don’t respond) to events like promotions, incentives, or retention actions. Not just in their first purchase, all the way through their lifecycle.
For example, it can be very useful (and save you a lot of money) to learn that customers acquired from December don’t respond to most promotions until the next October. That’s your typical holiday shopper, one that you can exclude from campaigns that offer deep discounts (e.g. win-back campaigns).
Cohort reports also let you detect seasonal spikes as well as long-term retention cycles. Repeat Customer Insights automatically creates cohorts and cohort reports for your Shopify store, going back to your very first order.