Cart abandonment rate is the percentage of shopping carts that never become an order: carts created minus completed orders, divided by carts created, times 100.
Cart abandonment rate = (Carts created − Orders) ÷ Carts created × 100
On the sample data below, six months come to 72.36%.
Why it matters
Abandoned carts are the cheapest revenue to win back, because the visitor already chose a product. Reminder emails and messages work on them better than on any other audience.
Worked example
The table shows the columns this metric needs from six months of a made-up subscription brand. Add each column up over the six months, then put the totals into the formula:
| Month | Sessions with an add-to-cart | Orders |
|---|---|---|
| 2026-01 | 2,480 | 702 |
| 2026-02 | 2,700 | 748 |
| 2026-03 | 2,950 | 812 |
| 2026-04 | 2,690 | 771 |
| 2026-05 | 3,150 | 846 |
| 2026-06 | 3,380 | 917 |
| Total | 17,350 | 4,796 |
(17,350 − 4,796) ÷ 17,350 × 100 = 72.36%
Add up first, then divide. Averaging the six monthly figures gives a slightly different answer, because it counts a small month the same as a large one.
Month by month
| Month | Cart abandonment rate |
|---|---|
| 2026-01 | 71.69% |
| 2026-02 | 72.30% |
| 2026-03 | 72.47% |
| 2026-04 | 71.34% |
| 2026-05 | 73.14% |
| 2026-06 | 72.87% |
Cart abandonment rate calculator
How to read it
Most carts are abandoned whatever you do; people use carts as wish lists. Watch the trend and the causes you can fix (cost surprises, payment failures) rather than the level.
Common mistakes
- Use sessions with a cart, not add-to-cart clicks, as the denominator.
- An order from a cart created in an earlier session still counts as a recovered cart. Over a month this evens out; over a day it does not.
- Cart abandonment and checkout abandonment are different stages. Do not compare one brand's cart figure with another's checkout figure.
Calculate cart abandonment rate in Excel, SQL or Python
The quickest version, for the sample sheet laid out as in the CSV (headers in row 1, months in rows 2 to 7):
=(SUM(L2:L7) - SUM(N2:N7)) / SUM(L2:L7)- Cart abandonment rate in Excel and Google Sheets — per-month formula and zero-safe version
- Cart abandonment rate in SQL — query by month and for the period
- Cart abandonment rate in Python (pandas) — pandas script with expected output
Related metrics
See all business metrics, or the statistics methods that sit behind them.
Questions people ask
- What is cart abandonment rate?
- Cart abandonment rate is the percentage of shopping carts that never become an order: carts created minus completed orders, divided by carts created, times 100.
- How do you calculate cart abandonment rate?
- Cart abandonment rate = (Carts created − Orders) ÷ Carts created × 100. For example, with six months of sample data: (17,350 − 4,796) ÷ 17,350 × 100 = 72.36%.
- What is the cart abandonment rate formula in Excel?
- With the sample data laid out as in the downloadable CSV, =(SUM(L2:L7) - SUM(N2:N7)) / SUM(L2:L7) gives the figure for the whole period (format the cell as a percentage). For one month, use =(L2 - N2) / L2 and fill it down.
- What is a good cart abandonment rate?
- There is no figure that is right for every business: it depends on your products, prices and channels. Most carts are abandoned whatever you do; people use carts as wish lists. Watch the trend and the causes you can fix (cost surprises, payment failures) rather than the level.
Check how stable it is
A metric moves for ordinary reasons as well as real ones. These methods separate the two: the spread shows what a normal month looks like, the moving average smooths it, the z-score flags a month that is out of line and the trend line shows the direction.
Guides
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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