Pre-Checked Default Options in Checkout A/B Test

Shoppers stalling on the delivery day or shipping method in session recordings, drop-offs at that point, or data showing most shoppers already pick the same option tell you a neutral choice adds an unnecessary step at checkout. If the default is the right one, most shoppers complete the order without changing it and cancellations do not rise. If shoppers stall because the options are unclear, clarify their descriptions first. Keep marketing consent, data sharing and paid add-ons out of this test, and check the target market's consent rules before launch.

Order completion rate

Compare purchases among visitors shown the predefined default option.

Also track

• Default change rateTrack whether visitors change the preselected option.
• Order cancellation rateCompare cancellations over the same follow-up period in both arms.
• Selection-related support contactsTrack reports that an option was selected without the user's action.
• Revenue per visitor (RPV)Compare revenue across all assigned visitors.

• DefaultPreselect one neutral option that adds no charge; keep the order and content of other options the same.
• SuitabilityCheck whether the default is appropriate for most visitors.
• AwarenessMake sure visitors notice the default and can change it.
• Change rateMeasure how often visitors change the default.
• SegmentsSegment results may inform a future hypothesis, but apply the same predefined default to everyone in this test.

1. 1Read the order completion rate alongside the order cancellation rate, tracked over the same follow-up window in both versions, and support contacts from shoppers who see a choice they did not make. If those rise along with completion, the default may be pushing shoppers toward something they did not want, which argues against shipping it. Measure revenue per visitor across everyone assigned to the experiment.
2. 2The default change rate shows whether the preselected option suits most shoppers, but a default that is too subtle makes that rate look artificially low, so make it clearly visible. Only the single default you tested is covered by this result; segment differences can suggest a new hypothesis for another default, but everyone gets the same default in this test.
3. 3When the gap is small, do not decide from a single number. Enter each arm's visitors and orders in the A/B test significance calculator and look at the p-value; if the gap is not significant, this test has not settled the effect of the default, so do not report it as a gain or a loss.