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% New Orders

How much of a row's order volume came from people buying from you for the first time.

60 second readAppears on: Breakdowns, More

What it means

% New Orders is the share of the orders in that row placed by customers buying from your store for the first time — first ever, not first inside the dates you picked. It's a table column, so it's measured per hour, per discount code, per payment method or per shipping type rather than for the store as a whole.

It counts orders, not people. The share of buyers who were new is a separate column, % New Customers% New CustomersHow well you're bringing in new buyers.70% or more is healthy, and the two rarely agree because repeat buyers place more orders each.

Show the math

Formula and a worked example

% New Orders = orders from first-time customers in that row ÷ every order in that row × 100.

First-time customers are buyers with no earlier order anywhere in your store's history.

The denominator is the Orders column in the same row — the same figure % Returning Orders% Returning OrdersShows how much of your order volume depends on loyal customers. divides by, which is why the two columns are directly comparable.

Worked example. The Discount Code table shows a welcome code with 400 orders, 340 of them from first-time buyers: 340 ÷ 400 = 85%. Two rows down, a refill code has 500 orders with 100 from first-timers, so it reads 20%.

Same markdown, two completely different jobs. One is buying customers; the other is discounting people who were coming back anyway.

The store-wide version of the same measure sits on the summary cards under the label New Orders, where the app does grade it.

It answers the question

Which hour, code, payment method or shipping option actually brings you new customers, and which ones are being claimed by the buyers you already had? A discount that goes to a returning customer is a markdown, not acquisition.

Why it matters

A first order carries an acquisition cost and a repeat order doesn't, so two rows with identical order counts can leave you in completely different places. This column is the fastest way to tell them apart without exporting anything.

It also survives a change in store size. Order counts swing with season and ad budget, so comparing 620 orders to 890 tells you very little on its own. A share strips the size out and leaves the mix.

What good looks like

The column carries no bands and shouldn't — a row with 12 orders will land anywhere. The app does grade the store-wide version: the New OrdersNew OrdersHow much volume new customers bring; pair with NCPA for cost.65% or more is healthy card reads strong at 65% or more and weak under 35%.

Use that as the anchor for the whole store, then judge each row against your own store's average rather than against 65%. And read the Orders count in the row first. A 100% share on 4 orders is noise, not a finding.

How to improve it

LeverWhat you doExpectHow longWatch out for
Fast
Point the codes at the right list
Make the welcome code first-order only and give returning buyers a different oneThe new-order share on that code climbs1–2 weeksRepeat buyers who used to claim it stop, so total orders on the row fall. You improved the share by removing volume, not by adding customers.
Fast
Move budget to cold audiences
Shift spend out of retargeting and into prospectingFirst-time orders rise across most rows2 weeksCold traffic costs more per order and converts worse, so NCPA rises immediately and this column only moves after it.
Slow
Reach people who don't know you
Open a channel aimed at discovery rather than at your existing audienceA step change in first-time orders1–2 quartersThose visitors browse more than they buy, so the conversion on those rows gets worse long before the share improves.
Slow
Add something new buyers can start with
Introduce an entry-priced product or a smaller sizeRows carrying it lean towards first-time orders1 quarterEntry products carry smaller baskets, so AOV on those rows falls and each first order pays back less of what it cost to win.

Every lever costs something somewhere. The last column is the one to read twice.

Read it with

A share tells you the mix. It cannot tell you whether the mix changed because new orders arrived or repeat orders stopped — the order count in the same row is what settles that.

% New Orders and Orders, one row on Breakdowns or More
Orders up
Orders down
% New Orders up

Real acquisition

More orders, and more of them from people who had never bought. This row is genuinely bringing the shop new customers rather than re-serving old ones.

Fund the row, and set up the follow-up before the cohort goes cold.

Replacing, not adding

The new share rose because the repeat buyers stopped coming, and total orders fell with them. This corner reads like growth in the column and isn't.

Read the Orders column before you celebrate the share.
% New Orders down

Your regulars carried it

Growth from people who already knew you — the cheapest kind, and the kind that runs out quietly if nothing is replacing the base.

Take it, then check something else is still filling the door.

Both halves fell

Fewer orders and fewer new faces at once. Something moved before the customer reached this row, so the answer isn't in the table.

Check what changed upstream: budget, a channel, or the offer on that row.
% New Orders + AOVAOVYour average order size, and a direct lever on revenue.

A row heavy with first-time orders and a low AOV is a cheap first purchase — fine if the second one comes, expensive if it doesn't. The same high share with a healthy AOV means people are trusting you with a full basket on day one, which is a different offer working. Neither number shows that alone.

% New Orders + % Discounts% DiscountsHow much of your revenue is given back as markdowns.Under 8% is healthy

Read across the Discount Code rows. Heavy discounting next to a high new-order share is money spent winning customers. Heavy discounting next to a low one is money handed to people who had already decided. The first is a cost of acquisition; the second is margin you gave away.

Common misreads

“% New Orders and % New Customers should match.”

Different denominators. One divides by orders, the other by people, and first-time buyers place exactly one order each while repeat buyers place several. The two columns disagreeing is the normal state.

“New means new inside the date range I picked.”

It means new to your store, ever. Someone whose first order was in 2023 never counts as new again, whatever dates you set. Narrowing the range changes which orders you're looking at, not who counts as new.

“Higher is always better.”

A store sitting near 90% every month has almost no regulars and rents its revenue from ads again every month. The card's bands stop at 65% for a reason — you want a busy door and a base, not only the door.

Also called

First-time order share · new-customer order rate · share of orders from new buyers

See yoursThe New Orders card gives the store-wide share. The per-row column sits on Breakdowns by hour, and on More by discount code, payment method and shipping type.

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