How many orders will you get from repeat customers next month?
I've spent 10 years figuring out how to predict repeat customer purchases online. Here’s how to do it right and get to 95%+ accuracy: If you want to understand your repeat customers and predict their behavior, it all starts with cohort analysis. This sounds fancy, but it’s just grouping customers based on the date they made their first purchase. From there, you can build a clear picture of what’s happening in your business. Here’s the step-by-step process: 1. Assign customers to cohorts. Start by grouping customers by the month (or week, depending on your volume) of their first purchase. This will be the starting point for tracking retention and repeat purchase behavior. 2. Establish a baseline retention curve. Most customer behavior follows a predictable pattern: orders gradually taper off over time. Plot this out to create a baseline curve—a starting point to measure future cohorts against. 3. Weight for recent behavior. Here’s the thing: the customers you acquired last month are much more relevant to forecasting than the ones you acquired three years ago. Weight your analysis to focus on recent cohorts to get a more accurate picture of what’s next. 4. Segment by customer type. Not all customers behave the same way. You might notice early customers were all over the place—some subscribing, some buying once. Breaking this down by type (e.g., subscribers vs. one-time buyers) makes the data a lot more actionable. 5. Adjust for seasonality. Timing matters. A customer you acquire in October is probably going to shop again in November because… Black Friday. That doesn’t mean they’re inherently “better,” but you need to account for these factors when predicting future behavior. 6. Predict orders, not people. Instead of predicting how many customers will come back, focus on the total number of orders a cohort will generate. Then multiply that by your average order value to get to revenue. Trying to count subscribers, then adjust for churn, reschedules, or payment failure will create lots of inputs to manage and ultimately leads to precision without accuracy. 7. Keep it fresh. The most accurate forecasts come from constantly updating your data. Monthly refreshes are usually the sweet spot—they let you capture new trends without bogging you down with constant updates. Sounds like a lot of work? It doesn’t have to be. Drivepoint does all of this out of the box. Want to see how it works? We can ingest your Shopify and Amazon data into actionable retention and revenue forecasts and show you the results. Link in the comments to book time if you want to learn more. ?? #CohortAnalysis #Forecasting #Shopify #Amazon #DTC