Understanding Your Shopify Cohort Report

The cohort report is one of the most powerful — and most underused — reports in Shopify Analytics. It shows you the purchasing behaviour of customers grouped by the month they first bought from you, letting you track how many returned to buy again over time. It is the clearest possible view of customer retention.

How to Read the Cohort Report

The table shows cohorts (rows) by their first purchase month. Each subsequent column shows the percentage of that cohort who made at least one additional purchase in that month. A cell showing '12%' in the Month 3 column means 12% of customers who first bought in that cohort's launch month came back to buy again in month three.

What Good Retention Looks Like

• Month 1 return rate: 15–25% is average for non-consumable products
• Month 1 return rate: 30–40% is achievable for consumables or subscriptions
• Month 6 retention: 10–15% is a healthy baseline across most categories
• Improving your Month 1 return rate is the highest-leverage retention action

Diagnosing Retention Problems

If your cohorts are flat — the percentages are very similar across all months — you have an acquisition-led business with weak retention. If early months show promise but numbers drop sharply, the post-purchase experience (delivery, packaging, email follow-up) needs work. If cohorts from a specific time period are stronger, examine what was different — a product launch, a promotion, or a change to your email flows.

Actions That Improve Cohort Performance

The post-purchase email sequence is the single biggest lever for Month 1 retention. A well-timed sequence — order confirmation, dispatch notification, delivery check-in, review request, replenishment reminder — can double your return purchase rate within 90 days. Combine this with a loyalty programme that rewards the second purchase specifically.

Using Cohort Data to Forecast Revenue

Once you understand your cohort curves, you can forecast future revenue from existing customers with reasonable accuracy. If you know 15% of customers return in Month 1, 10% in Month 2, and 8% in Month 3, you can model the expected revenue from any given acquisition cohort. This turns retention strategy into a financial planning tool.