Where do you find customer retention in Shopify analytics?

The retention reports built into Shopify

Everything below lives under Analytics in the left-hand navigation of the Shopify admin (reports in the reports list, headline metrics on the overview dashboard), except customer segments, which live under Customers. All of it is included with your plan — no extra tooling required to get this far.

Returning customer rate

The Analytics overview dashboard shows a returning customer rate among its headline metric cards: the share of customers in your selected date range who had purchased from your store before. You can change the date range and compare against a previous period to see direction. It's the single best pulse metric Shopify gives you — one number that rises when retention improves — but it's a store-wide average, so a strong quarter from old loyalists can mask weak repeat behavior among this year's new customers.

Customers over time

In the reports list, Customers over time tracks how many customers bought in each period, split into first-time and returning. It's the trend view of the same idea: if the returning line grows while the first-time line holds, your base is compounding; if returning stays flat while acquisition climbs, you're refilling a leaky bucket. Use it to see whether growth is coming from new faces or repeat buyers.

Customer cohort analysis

Shopify's customer cohort analysis report groups customers by the month of their first purchase and shows what share of each cohort came back in later months — a genuine retention matrix, in the admin, for free. It's the closest native thing to a true retention rate. Reading one of these tables well is a skill of its own (rows, columns, and diagonals each mean something different) — our guide to cohort analysis for Shopify retention walks a sample table cell by cell.

Customer segments

Under Customers, Shopify includes a segment editor: filter-based groups built from attributes like number of orders, amount spent, and date of last order, with ready-made templates that approximate RFM-style groupings (loyal, at-risk, lapsed, and similar). Segments update as customers qualify, and they can feed Shopify Email directly. What the filters can't do is weigh signals against each other — a rule like "no order in 90 days" treats the weekly buyer and the twice-a-year buyer identically.

Which report answers which question

Churn rate deserves a note: Shopify never reports one, partly because stores without subscriptions have no cancellation event to count. You can compute it from order exports with an inactivity window — the formula and a worked example are in how to calculate customer churn rate for a Shopify store.

What Shopify analytics won't tell you

No per-customer churn risk. Every native report is an aggregate. The cohort report can show you that March's cohort is decaying faster than January's — it cannot name the 45 customers in that cohort who are about to lapse this week, which is the list you'd actually act on.

No forward-looking signal. Native analytics describe what already happened. By the time a customer shows up as "lapsed" in a segment filter, the cheap moment to save them — while they still remembered why they bought — has usually passed.

Limited retention attribution. Shopify's marketing reports attribute sales at the channel and campaign level, but tying a specific win-back send to a specific customer's recovered revenue — and knowing what that save was worth — is beyond what the native reports break out.

No action layer. Even where the reports diagnose a problem, they don't do anything about it. The gap between "returning customer rate fell two points" and "these customers got a timed, margin-aware offer" is entirely yours to bridge.

How retention apps fill the gaps

Retention apps pick up exactly where the native reports stop: scoring churn risk per customer instead of per cohort, maintaining predictive segments that update as behavior changes, launching win-back campaigns automatically, and attributing recovered revenue to the campaign that earned it.

The distinction worth understanding before installing anything is analytics suites versus retention apps. Analytics platforms like Polar Analytics and Triple Whale are built to unify reporting and marketing attribution across channels — broader dashboards, not per-customer churn action. How that plays out feature by feature is covered in ChurnMiser vs Polar Analytics and ChurnMiser vs Triple Whale. For the wider field — loyalty, email, and churn-prediction tools side by side — see the best Shopify customer retention apps roundup.

Frequently asked questions