Cohort analysis is a crucial tool for marketers -- but, as with any analytical tool, it’s important to be aware of its limitations. The primary drawback of cohort analysis is that, unlike predictive analytics, it’s purely historical. If your company’s competitive landscape, business model, product mix, or strategy have changed dramatically over time, past results may not be indicative of future performance. And unless you’re using the forecasting tool outlined in the advanced section of the course (and available as a takeaway here), calculating customer lifetime value (CLV) via cohort analysis may require you to wait around quite a while to observe the behavior of your customers over time!
That being said, cohort analysis is essential for understanding long-term trends in customer engagement and retention. Has your repeat purchase rate been declining over time? Are this year’s back-to-school-sale customers spending as much as last year’s? Cohort analysis serves as a crucial first step in surfacing marketing opportunities -- and, ultimately, building out a Lifecycle Marketing strategy (check out the Custora U course on lifecycle marketing here).
That wraps up Custora U's course on Cohort Analysis. As always, if you have any feedback or suggestions on things to improve, we'd love to hear them.
Enjoy this Cohort Analysis Workbook, a simple spreadsheet that lets you plug in different historical cohort results and see how much a new group of customers will be worth in the future.
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