Track Shopify Repeat Customer Rate, No App

Your repeat customer rate is the single clearest signal of whether your Shopify store is building a business or just renting attention from ad platforms. The good news: you do not need a $30-per-month retention app to see it. A free order export and one formula get you the number in about fifteen minutes, and a simple weekly habit turns it into a metric you actually act on.

Most retention apps charge a recurring fee to surface a figure that already lives inside your Shopify admin. Before you add another line item to your monthly software bill, it is worth knowing the export, the math, and the benchmark, so you can decide whether an app is buying you anything you cannot get for free.

What repeat customer rate actually measures

Repeat customer rate is the percentage of your distinct customers who have placed more than one order. If 1,000 unique people have ever bought from you and 280 of them have ordered at least twice, your repeat customer rate is 28 percent.

It is not the same as repeat purchase rate by order volume, and it is not the same as returning visitor rate in your traffic analytics. Those measure different things and will give you different numbers. Repeat customer rate is a people metric: out of everyone who bought, what share came back. That framing matters because retention is about relationships, not sessions.

The reason it deserves a permanent spot on your dashboard is unit economics. Acquiring a new customer typically costs several times more than selling again to someone who already trusts you, a gap documented across decades of customer-loyalty research, including the foundational work summarized by Harvard Business Review. A store with a 12 percent repeat rate and one with a 35 percent repeat rate can look identical on revenue this month and have completely different trajectories a year out.

The free export method, step by step

Shopify hands you everything you need without a single app install. Here is the path.

• In your Shopify admin, open Orders, then Export, and choose all orders for the period you want to measure (a rolling 365 days is a sensible default).
• Open the CSV in your spreadsheet tool of choice. The columns that matter are the customer email (or customer ID) and the financial status, so you only count paid orders.
• Filter to paid orders, then count the distinct customers (a pivot table grouped by email, or a UNIQUE count, does this cleanly).
• Within that same set, count how many customers appear on more than one order. Divide that second number by the first, multiply by 100, and you have your repeat customer rate.

A practical note on counting. Use the customer ID where you can, because the same shopper may check out under two email addresses, which quietly understates your repeat rate. If you only have email, normalize for capitalization and stray spaces before you count. These small cleanups are exactly the kind of thing a paid app does silently, and exactly the kind of thing you can reproduce in a spreadsheet for nothing.

Reading the number: what is good

A raw percentage means little without a frame. Use this as a working scorecard rather than a hard rule, because healthy retention varies by category. Consumable and replenishable products (coffee, supplements, skincare) should clear a higher bar than considered one-time purchases (furniture, electronics).

As a general rule of thumb across direct-to-consumer ecommerce, many operators treat a repeat customer rate in the low-to-mid 20s as a reasonable baseline, the low 30s and above as a sign of genuine loyalty, and anything under roughly 15 percent as a flag that the business is leaning hard on paid acquisition to stay flat. Replenishable categories should aim noticeably higher than that baseline; durable, infrequent purchases will sit lower and that can still be a perfectly healthy business.

Pair the rate with its timing. A customer who reorders coffee every five weeks behaves differently from one who buys a winter coat once a year. Tracking the median gap between first and second order alongside the headline rate tells you whether your retention problem is "they never come back" or "they come back, but too slowly."

A mini case study: the spreadsheet that found $40K

Consider a 9-person apparel brand doing solid monthly revenue and quietly paying for a retention app that mostly sent it dashboards it never opened. When the owner ran the free export instead, two things surfaced that the app's default view had buried. First, the true repeat rate was 19 percent, not the 26 percent the app reported, because the app counted guest-checkout duplicates as separate people. Second, customers who bought a second time did so within 38 days on average, then went quiet.

That second fact was the lever. A single email sequence timed to land at day 30, before the typical drop-off, lifted second orders enough to add a five-figure annual run rate, on the order of $40,000, with zero new ad spend. The insight cost nothing but a CSV and a pivot table. The app had been charging monthly to hide it.

Turning a one-time check into a weekly metric

The export method has one real weakness: it is a chore, so most owners do it once, feel informed, and never repeat it. A number you check once is trivia. A number you check every week becomes a steering wheel.

The fix is to stop treating it as a manual task and start treating it as a live metric on a dashboard you already glance at. That can be a spreadsheet you refresh on a schedule, or a done-for-you dashboard that pulls your Shopify data and keeps repeat customer rate, average days-to-second-order, and revenue side by side without you touching a formula. MyDashBorg builds exactly that kind of dashboard from a template, so the metric updates on its own and you can simply ask it questions in plain language instead of rebuilding a pivot table every Monday.

Whichever path you pick, the principle holds: the number is free, the formula is simple, and the only thing standing between you and weekly retention visibility is a habit, not a subscription.

Frequently Asked Questions

Do I need a paid app to calculate Shopify repeat customer rate?

No. Shopify lets you export all orders to a free CSV from the Orders page, and a single formula (repeat customers divided by total customers, times 100) gives you the rate. Paid retention apps mostly automate and display this calculation rather than unlock data you could not otherwise reach.

What counts as a "repeat" customer?

A repeat customer is any distinct customer who has placed more than one paid order in the period you are measuring. Count people, not orders, and use the customer ID rather than email where possible so the same shopper checking out under two addresses is not split into two people.

What is a good repeat customer rate for an ecommerce store?

It varies by category, but as a rule of thumb many direct-to-consumer operators treat the low-to-mid 20s as a baseline, the low 30s and up as strong loyalty, and under roughly 15 percent as a warning sign. Replenishable products (coffee, supplements) should aim higher; infrequent durable goods will sit lower and still be healthy.

How often should I check my repeat customer rate?

Weekly is the sweet spot for most stores. Checking it once tells you where you stand today; checking it on a recurring cadence turns it into a metric you can actually move with email timing, post-purchase offers, and product decisions before customers go quiet.

Why is my app's repeat rate different from my export?

Usually because the app and your export count customers differently. Guest checkouts, duplicate emails, and refunded or unpaid orders are common sources of mismatch. Standardize on paid orders and a single customer identifier, and the two numbers should converge.

Want your repeat customer rate, days-to-second-order, and revenue on one screen that updates itself? See MyDashBorg pricing and skip the manual export forever.