Overview
What the store sold, whether it came from more orders or bigger ones, and who was buying.
Everything on this page is Shopify's own order data. No advertising, no Amazon, no Google Analytics — so nothing here needs reconciling against another system.
A panel of generated insight cards sits above the numbers. Read it after the cards, not instead of them.
The cards
This is where you find out whether the store grew, and whether it grew in a way you can repeat next month.
Each card carries a small trend line under the number, and the change against your comparison period beside the name.
Total SalesTotal SalesTax and shipping are collected, not earned, so this sits above what you keep. Most ratios divide by it, so a move here shifts them all · Order RevenueOrder Revenuerefunds and costs not taken off. Expect it above your other sales figures, and never read the difference as profit. · OrdersOrdersCounts purchases, not money, so it moves even when order sizes don't. Compare with sales to see whether growth came from more buyers or bigger baskets · AOVAOVLifting this grows revenue without more traffic. If it slips, look at discounts and at what you're paying to win each order · AOQAOQRead it next to order value: it tells you whether bigger orders come from more items or from pricier ones2.5 or more is healthy · % Returning Customers% Returning CustomersReads high both when loyalty grows and when new buyers stop arriving. Check it next to new customers and total orders before celebrating30% or more is healthy · Returning OrdersReturning OrdersHow much of your order volume rests on people who already bought once. A fall means new buyers are carrying more of the load35% or more is healthy · % New Customers% New Customersit can fall in a month when new buyers actually rose. Read it next to total orders before judging.70% or more is healthy · New OrdersNew OrdersGrowth from first-time buyers costs more to win than repeat business. If this rises, check what you are paying to acquire each new customer65% or more is healthy · % Discounts% DiscountsEvery point here comes straight off margin, with no cost saving to offset it. If it climbs, check whether volume rose enough to pay for itUnder 8% is healthy
Read them in three moves
- Did sales move? Total Sales. Direction first, reasons after.
- More orders, or bigger ones? Orders and AOV. Almost all of the change sits in one of the two.
- Who bought? % New Customers and % Returning Customers. The same sales number means very different things depending on the answer.
Three pairs worth holding together
Total Sales + Order Revenue. Order Revenue does not take refunds off. Total Sales does. Watch the two drift further apart across periods and you are watching returns climb, without a returns report.
AOV + AOQ. AOV up with AOQ flat means people paid more for the same number of items — price or product mix. AOV up with AOQ up means baskets genuinely got bigger. Bundles move the second one; a price rise only moves the first.
% Returning Customers + Returning Orders. One counts people, the other counts orders. When Returning Orders runs well above % Returning Customers, a small group of repeat buyers is carrying a large share of your volume — worth protecting, and risky to depend on.
Total Sales, Order Revenue and Orders carry no grade badge; there is no universal good figure for them. AOV is graded against a band for your own currency.
The tables
The cards tell you the store moved. These tell you who moved it — your repeat buyers, one country, or a single order source.
Each tab carries the same controls: a search box, an Export button, and icons that switch it to a bar, line or pie chart. In a chart view you also get a metrics dropdown — up to three at once — and a Compare checkbox that draws the previous period behind it.
Customer Type
Here you learn whether your repeat buyers come back once, or come back as a habit.
One row = first-time buyers, or returning buyers.
Columns: Customer Type · Total Sales · % Total Sales · Orders · AOV · AOQ · % Customers% CustomersShows how big this segment is in your customer base. · % Orders% OrdersHelps compare usage intensity between segments. · % Discounts, each with a % △ except % Total Sales.
How to scan it
- Look at the returning row.
- Compare its % Orders against its % Customers.
- What it means: % Orders much higher than % Customers says your repeat buyers come back more than once each. % Orders barely above % Customers says they came back exactly once and stopped.
Then read AOV down the two rows. Returning buyers spending less per order than first-timers usually means your discounts are pointed at the wrong group.
Country
This separates the markets you are building from the markets you are renting.
One row = one country, from the shipping address on the order.
Columns: Country · Total Sales · % Total Sales · Orders · AOV · AOQ · % Returning Customers · % New Customers · % Discounts, each with a % △ except % Total Sales.
How to scan it
- Sort by Total Sales, highest first.
- Look across at % Returning Customers.
- The row that matters: a large market with almost no repeat buying. You are renting that country rather than building it, and it will cost the same again next month.
Then run it a second way. Sort by % Discounts, highest first, and read AOV on those rows. A market you are discounting into that still has a low AOV is not a market, it is a habit.
Source of Order
This tells you which way in brings buyers worth having, rather than buyers worth counting.
One row = one order source.
Same columns as Country. This tab is only there with a single store selected — pick an organisation and it disappears.
How to scan it
- Sort by Total Sales, highest first.
- Look across at % New Customers and AOV together.
- The row that matters: high % New Customers with a low AOV. That source brings people through the door cheaply and they buy the cheapest thing you sell.
Filters
The comparison period is the control that turns this page from numbers into a direction. Everything else only changes what you are looking at.
Date Range and Previous period sit at the top right. The comparison feeds both the change beside each card name and every % △ column in the tabs. Without one, all of them are blank.
Filters opens country, customer type and order source. All three work on this page, and all three narrow the tabs as well as the cards — set Customer Type to returning and the Customer Type tab is left with one row. Easy to forget it is on.
There is no Include Amazon checkbox here. This page is Shopify only, by design.
Watch out for
Two of those cards count people and two count orders. % New Customers and % Returning Customers are shares of customers. New Orders and Returning Orders are shares of orders. They sit next to each other and answer different questions, and the four rarely agree.
The Customer Type tab renames the same idea. It uses % Customers and % Orders rather than the new/returning card names, because the row already tells you which type it is. Same measures, shorter labels.
Order Revenue is not a smaller Total Sales. They are built differently, not scaled differently. Don't use one where a report asked for the other.
Total Sales divided by Orders is not AOV. AOV takes gross sales less discounts and divides by orders. Total Sales also adds shipping and tax and takes refunds off. Doing the division yourself gives a different number, and neither one is broken.
Do this first
Read Total Sales, then Orders and AOV, in that order. Then open the Country tab, sort by Total Sales and look across at % Returning Customers — that is where a good month and a repeatable month look different.
See yoursYour sales, your basket size, and who is actually coming back.
Open Overview →