% Orders
What share of your orders came from one slice of customers.
What it means
% Orders is one row's share of every order your store took in the period, written as a percentage. It sits on the Customer Type table, where the only rows are First Time and Returning, so the two shares always add to 100%.
It counts orders, not people and not money. The people split is the % Customers% CustomersShows how big this segment is in your customer base. column beside it; the money split is % Total Sales% Total SalesShows how important this segment is to overall revenue. further left. All three describe the same two segments and none of them will agree, because repeat buyers order more often and spend differently.
Show the math
Formula and a worked example
% Orders = the row's orders ÷ every order in the period × 100.
The row's orders is the count of orders placed by that customer segment — Returning if the buyer already had an order in your store's history, First Time if they didn't.
The denominator is every order in the period, across both rows.
Worked example. March brings 1,000 orders. 300 of them come from customers who had bought before, so the Returning row reads 300 ÷ 1,000 = 30% and the First Time row reads 70%.
In April the returning orders hold at 300 while first orders fall to 300. The Returning row now reads 300 ÷ 600 = 50%. Not one extra repeat order was placed — the share rose because the other row collapsed. Read the Orders column in the same row before you read this one.
It answers the question
Which kind of customer placed this period's orders — the ones you just paid to find, or the ones you already had? The answer decides how much of next month you have to go out and buy again.
Why it matters
Two stores can take the same number of orders and end the month with very different profit, because a first order carries acquisition cost and a repeat order doesn't. This column is the fastest read on which of those two your volume is made of.
It also survives a change in store size. Order counts jump around with seasonality and ad budget, so comparing 620 orders to 890 tells you little on its own. A share strips the size out and leaves the mix.
What good looks like
The app publishes no grading bands for this column, and there is no split that is right for every store. A subscription business and a furniture shop should sit in completely different places, and a store six months old cannot have built a repeat base yet.
Judge it two ways instead. Against your own trend, month over month with the same season in mind. And against the Returning OrdersReturning OrdersHow much of your volume loyalty drives.35% or more is healthy card on the Summary page, which measures the same repeat share for the whole store and does carry the app's bands.
How to improve it
| Lever | What you do | Expect | How long | Watch out for |
|---|---|---|---|---|
| Fast Follow up after the first order | Email everyone who has bought once, at around 14 days and again at 45 | Orders move from the First Time row into the Returning one | 3–6 weeks | If the follow-up carries a code you discount the people most likely to come back unprompted, so those repeat orders arrive on a thinner margin and % Discounts on that row rises. |
| Fast Move budget to prospecting | Shift spend out of retargeting and into cold audiences | The First Time row grows, the Returning row shrinks | 2 weeks | Cold traffic costs more per order, so your cost per order rises immediately. And the Returning row falls without a single repeat customer leaving — you only changed the denominator. |
| Slow Give people a second thing to buy | Add a refill, a consumable or a companion product to the range | A structural shift towards the Returning row | 2 quarters | New stock and cash tied up in it. Second purchases are usually smaller than first ones, so AOV falls on the row that grew. |
Every lever costs something somewhere. The last column is the one to read twice.
Read it with
A share of orders tells you the mix. It cannot tell you whether the mix changed because one segment grew or the other shrank.
The two columns sit next to each other for this comparison. Returning customers order more often than first-timers, so the Returning row's share of orders normally runs above its share of customers. When the gap is wide, a small group of regulars is carrying a lot of volume — good for margin, and a concentration risk worth knowing about. When the two are level, your repeat buyers are buying no more often than strangers do.
Order share says how many, AOV says how much each. A segment holding 30% of orders at half the store's AOV is contributing far less than 30% of the money, which is exactly the mistake this column invites. Read them across the row before you decide which segment matters most.
Common misreads
Different denominators. This counts orders and % Customers counts people, and because repeat buyers order more often the order share sits above the customer share in most stores. Both columns are on the same row, one click apart.
A share moves when either half moves. If first orders fell 30% and repeat orders held flat, this number rises while the store shrinks. The Orders column in the same row settles it in one glance.
It means first ever with your store. Someone whose first order was in 2023 counts as Returning today, whatever dates you set. Narrowing the range changes which orders you are looking at, not who counts as new.
Also called
Order share · share of orders · order mix by customer type
See yoursThe Customer Type table splits your orders into First Time and Returning, with each segment's share of customers and sales beside it.
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