In SQL, checkout rate for the whole period is ROUND(100.0 * SUM(checkouts) / SUM(sessions), 2) over the monthly table. On the sample data it returns 4.22.
Checkout rate = Checkouts started ÷ Sessions × 100
What you need
Checkout rate, or sessions-to-checkout rate, is the percentage of website sessions in which the visitor started checkout. You need these columns, here from the sample file monthly.csv:
- sessions: website sessions
- checkouts: checkouts started
CREATE TABLE monthly (
month TEXT, -- 'YYYY-MM'
sessions INTEGER,
checkouts INTEGER
);Step by step
- Load monthly.csv into a table called monthly. The table only needs the month column and the columns below.
- Run the first query to get one row per month.
- Run the whole-period query. It adds up each column first and divides once; averaging the monthly results gives a different, usually wrong, answer.
The queries
SELECT
month,
ROUND(100.0 * checkouts / NULLIF(sessions, 0), 2) AS checkout_rate
FROM monthly
ORDER BY month;SELECT ROUND(100.0 * SUM(checkouts) / NULLIF(SUM(sessions), 0), 2) AS checkout_rate
FROM monthly;What you should get
Run against the sample data, the code above returns these values (in percent):
| Month | sessions | checkouts | checkout_rate |
|---|---|---|---|
| 2026-01 | 31,200 | 1,310 | 4.20% |
| 2026-02 | 33,800 | 1,420 | 4.20% |
| 2026-03 | 36,500 | 1,560 | 4.27% |
| 2026-04 | 34,100 | 1,400 | 4.11% |
| 2026-05 | 38,900 | 1,650 | 4.24% |
| 2026-06 | 41,600 | 1,790 | 4.30% |
| Whole period | 2,16,100 | 9,130 | 4.22% |
9,130 ÷ 2,16,100 × 100 = 4.22%
Notes for SQL
- Integer columns divide as integers in PostgreSQL, SQLite and SQL Server, so 3 / 4 gives 0. Multiplying by 1.0 (or 100.0) first makes the division decimal.
- NULLIF(x, 0) turns a zero denominator into NULL, so the query returns NULL for that row instead of failing with a division-by-zero error.
- Tested on SQLite and DuckDB. SUM, NULLIF and ROUND work the same in PostgreSQL, MySQL and BigQuery; SQL Server uses TOP instead of LIMIT where a query has one.
Where checkout rate misleads
- Accelerated checkouts (one-click wallets) may skip the step your analytics calls "checkout started". Check how they are tracked.
- Count each session once, however many times checkout was opened.
- Changes in what the analytics tool counts as a session change every rate in the funnel at once.
The full explanation, with a calculator, is on the Checkout rate page.
Same metric, other tools
Related metrics in SQL
Learn more about SQL
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- How to find out what changed in your sales data — 2 min read
About the data on this page
The figures come from a small made-up dataset, printed above in full so you can check every number by hand. Download it as monthly.csv. The results are computed from those rows when the page is built, and the Excel formulas, SQL and Python on these pages are run against the same rows before publishing, so the code and the answers agree.
To get these numbers from your own data without writing formulas, try AnalyzeIt: ask in plain words and it shows the working behind every figure.
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