Shopify's native reporting handles basic cohort views for one-time purchases, but subscription-specific cohort analysis lives in the subscription app — Joy Subscriptions, Recharge, Bold, etc. The good news: you have all the data you need. The bad news: connecting it into a clean retention curve takes a bit of setup most stores never do.
What data lives where
- Shopify order history — Customer signup date, lifetime spend, channel attribution (if UTM-tagged), products purchased.
- Subscription app data — Subscription start date, current status (active, paused, cancelled), billing history, plan changes, skip and pause events.
- Ad platforms / GA4 — Acquisition source for paid channels, useful for channel-cut cohorts.
The cleanest cohort analysis joins these three sources by customer ID and signup date.
The Shopify-specific cohort views to build
- Signup-month retention. The foundational view. For each month of subscriber signups, track % still active in each subsequent month.
- Channel cohorts. Cut by acquisition source (Meta ads, Google ads, organic, referral, email). Channel quality often varies more than expected — paid social cohorts can retain at half the rate of organic.
- First-product cohorts. If you sell multiple subscription products, retention by first-product often reveals which is the "sticky" entry point worth promoting.
- Discount cohorts. Subscribers acquired with a heavy first-order discount (50%+ off) often churn at 2–3x the rate of full-price signups. This view tells you if your promotions are buying disposable customers.
Tools for Shopify cohort analysis
- Subscription app reports — Most apps include some cohort retention view. Start here; the data is already there.
- Shopify's customer reports — Useful for total-customer cohort views but limited for subscription-specific metrics.
- Lifetimely, Repeat, or similar Shopify apps — Add deeper cohort and LTV analysis on top of Shopify data.
- BI tools — Metabase, Mode, Looker for stores ready to invest in custom analytics. Export from Shopify and the subscription app, join on customer ID.
The trap to avoid
Mixing subscription customers with one-time customers in a single cohort view. The two have completely different retention shapes — a one-time customer who buys once and returns a year later looks like "churn" in a 30-day cohort but is actually normal. Always isolate subscription cohorts from one-time cohorts. For broader context, see customer cohort analysis.