Category & Listing
Earliest Delivery Date on Product Cards A/B Test
Showing an estimated delivery date on the product card may help visitors assess delivery time before opening the product page. It could speed decisions for time-sensitive purchases, but an inaccurate estimate can create expectations the operation cannot meet.
A/B test scenario. This page is a test plan, not the result of a real experiment.
- Category listing
- Purchase conversion rate
Control vs Variant
Absent on one side, present on the other.
- Changed
- Presence
- Page
- Category listing
- Difference
- added
Hypothesis
If shoppers see the earliest estimated delivery date on the card, they may be able to tell whether a product will arrive in time without opening its page. Purchase conversion rate could rise as a result, most of all for orders that must arrive by a certain date.
Test plan
When to run this test
This test makes sense when delivery time seems to stay unclear at the listing stage, such as shoppers in session recordings who open product pages just to check delivery, support tickets asking how long delivery takes, or cancellations caused by late delivery. If the estimate helps, shoppers pick a product that will arrive in time straight from the listing and make the purchase decision faster. If the estimate logic does not match actual delivery, or operations cannot meet the dates shown, fix that first, because a date the listing cannot keep can turn conversions into cancellations later.
How to measure success
Purchase conversion rate
Compare purchases among eligible visitors who see a delivery estimate in the listing.
Also track
- Listing-to-product click-through rateCheck whether visits to product pages change.
- Delivery estimate accuracyCompare actual delivery with the estimate shown to the visitor.
- Cancellation or return rateTrack cancellations or returns linked to delivery expectations.
- Sales of slower-delivery productsMake sure sales of slower-delivery products do not fall materially.
How to set it up
- EstimateShow the earliest estimated delivery date for eligible products.
- Keep constantKeep delivery operations, estimate logic, shipping fees, sorting and card content unchanged.
- ChoiceCheck whether visitors shift toward products with faster delivery.
- AccuracyCompare the displayed estimate with actual delivery.
- Separate testShowing a date versus a number of days is a separate copy-format test.
What to watch when reading the result
- 1Even if purchase conversion rate rises, do not roll out the variant before you have compared the displayed estimates with actual delivery. Check the cancellation or return rate again once the test orders have been delivered, because the cost of missed dates appears after the conversion is recorded.
- 2A shift toward faster-delivery products is not a failure on its own; compare any drop in sales of slower-delivery products with the loss limit you set before launch. The effect you measure covers only the eligible products that showed an estimate.
- 3If the overall gap looks small, the effect may sit in time-sensitive purchases and get diluted in the overall average. Work out up front how many visitors each variant needs with the sample size calculator, divide that by the daily visitors each arm receives, and round the run up to full weeks so that dates shifting by day of the week do not skew the comparison.
- 4Check that the card clearly labels the date as an estimate and does not present a location-dependent date as certain before the visitor's location is known. Otherwise you are measuring the effect of a promise, not of delivery information.
Frequently Asked Questions
How should the delivery estimate appear on cards?
Use the same estimation logic and operations in both arms. Clearly identify an estimate rather than a guarantee. Do not show location-dependent certainty when the location is unknown.
Can the variant ship immediately if conversion improves?
First assess estimate accuracy against actual delivery. An unrealistic date can turn an initial purchase gain into later cancellations, returns or support contacts.
How can delivery dates affect slower-delivery products?
Use purchase conversion as the primary outcome. Monitor slow-delivery product sales against the predefined guardrail. A shift toward faster delivery is not automatically a failure.
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