Transactions
The number of completed purchases Google Analytics recorded in the period.
What it means
Transactions is the count of purchases Google Analytics saw complete on your site. It counts orders, not items — a basket with five products still counts once. Refunds aren't deducted later, so the figure is gross.
Show the math
Formula and a worked example
There's no division here. Google Analytics adds one each time a purchase event fires, so what you're reading is a raw tally of tracked orders in the date range.
Worked example. In March the site records 1,200 Transactions and €84,000 of tracked revenue — an average order of €70. Shopify shows 1,265 orders for the same month, a 5% gap. That's normal: consent refusals, ad blockers and a payment redirect that loses the tag each cost you a few counts.
A 25% gap is not normal. That's a tracking fault, and every rate on the page is understated by the same amount until it's fixed.
It answers the question
How many orders did the site actually take? It's the count that most other figures on the page are measured against.
Why it matters
Transactions anchors the whole Google Analytics section. Conv. Rate (GA4), revenue per source and every funnel step end at this number, so when it's wrong everything downstream is wrong in the same direction and nothing on the page warns you.
It's also a volume figure, so it moves for two unrelated reasons: more visitors arrived, or more of the same visitors bought. Reading it next to Total RevenueTotal RevenueCross-check against Shopify to confirm tracking is firing. and the traffic counts is what separates those two.
What good looks like
There's no universal target for a count — 200 a month can be excellent and 20,000 disappointing. Judge it against your own last 30 days and the same month last year, adjusting for how much traffic you paid for. One absolute check does apply: it should land within a few percent of your Shopify order count for the same range, and a persistent double-digit gap is a tagging problem, not a sales problem.
How to improve it
| Lever | What you do | Expect | How long | Watch out for |
|---|---|---|---|---|
| Fast Repair the purchase event first | Check the purchase tag fires on every payment method, including wallet and redirect gateways | Transactions rise to within a few percent of Shopify | 3–5 days | Nothing actually changed on the site. Every trend line breaks at the fix date, so weeks either side of it can't be compared. |
| Fast Move budget to the sources that already convert | Sort by source and shift spend towards the ones that finish, not the ones that fill the top | More orders on the same spend | 2 weeks | Spend concentrates on a narrow audience. Frequency climbs and cost per order rises once that audience is saturated. |
| Slow Take a step out of checkout | Guest checkout, fewer required fields, wallet payments enabled | More of the same visitors finish | 3–6 weeks | Fewer accounts get created, so your email list grows more slowly and later flows have fewer people to send to. |
| Slow Widen the top of the funnel | New channels, new audiences, more product pages earning search traffic | Orders grow roughly in line with traffic | 1 quarter | New traffic converts worse than traffic you already have, so the count rises while Conv. Rate (GA4) and cost per order both get worse. |
Every lever costs something somewhere. The last column is the one to read twice.
Read it with
The count and the money it brought in are two different stories. Together they tell you whether growth came from more orders or bigger ones.
Growing properly
More orders and more money. Check revenue grew at least as fast as the count — if it lagged, average order size is quietly slipping.
Selling more for less
Order count rose and takings fell, so baskets got smaller or cheaper. Usually a promotion, a cheap line pulling volume, or a free-delivery threshold set too low.
Fewer, bigger orders
A smaller number of larger baskets. Fine when it's bundling or a premium line, fragile when it's a few wholesale-sized orders holding the month up.
Both directions down
Volume and value fell together. Rule out tracking first, then traffic, then the funnel — in that order, because the first one is free to check.
The two counts either side of the payment step. The distance between them is the only place you can see how many decided shoppers reached the till and left without paying, and that's the cheapest group in the funnel to win back.
A tracked count next to the share of orders coming from repeat customers tells you what the month was built on. The same order total made mostly of returning buyers costs a fraction of one made of first-timers, so two identical months can carry completely different acquisition bills.
Common misreads
A few percent apart is expected. Google Analytics counts what the browser reported, Shopify counts what was paid, and the two use different time zones and different cut-off points for a late-night order. Investigate a gap above 10%, not below it.
It's a count, not a rate. Fewer visitors produces fewer orders with the site behaving exactly as it did last month. Check the traffic figures before you change anything on the page.
It tells you how many times you sold. One order of €900 and one of €9 count the same, so the figure can hold steady through a month where takings collapsed.
Also called
Purchases · orders · completed checkouts
See yoursYour Transactions for the selected range, with the trend line and the sources that produced them.
Open Google Analytics Overview →