CTA Button Color A/B Test Example on the Cart Page

Consider this test when the cart page gives you a sign that the main button does not stand out from the elements around it, such as a low click rate, a heatmap that shows the button being skipped, or session recordings of visitors looking for it. The expected behavior is that a button that is easier to notice moves more visitors on to checkout. If the problem is checkout errors, a slow page or an unclear offer, look at those first, because a color change does not replace them.

Click-through rate (CTR)

Compare clicks on the cart CTA between visitors assigned to each color.

How it is counted: Suggested definition: of the visitors assigned to the control or the variant who saw the CTA, the share who clicked it at least once. Repeat clicks by the same visitor count once.

Also track

• Purchase conversion rate (CR)Compare completed orders among all visitors assigned to each experience.
• Checkout start rateCompare assigned cart visitors who proceed to checkout.
• Cart page exit rateCompare the share of assigned visitors who leave the cart page.

• ColorCompare the current CTA color with one preselected, brand-approved alternative. Record both color values before launch.
• ContrastKeep the label easy to read and maintain accessible contrast in both versions.
• Keep constantDo not change the button label, size, position or surrounding design.
• TrackingVerify CTA impressions and clicks, checkout starts and completed orders are attributed to the correct variant.
• DeviceReview mobile and desktop separately.

1. 1More clicks alone are not a reason to ship the change. Check whether the increase carries through to checkout starts and completed orders.
2. 2The result holds for the color pair you tested and for the cart page. Validate it again in the new context before applying it to another page or another color.
3. 3If the difference is small or unclear, note that this sample could not measure it. Look at the size of the effect and the uncertainty around it together. You can check whether the gap could be ordinary sampling variation with the A/B test significance calculator.