All testsAli Demirbaş - Lab

Cart & Checkout

Testing Product Recommendations Inside the Cart

Relevant complementary-product suggestions may increase order value by helping shoppers find items to buy together. Read this alongside order completion so extra suggestions do not distract from checkout.

A/B test scenario. This page is a test plan, not the result of a real experiment.

  • Cart
  • Average order value (AOV)

Control vs Variant

Absent on one side, present on the other.

Changed
Presence
Page
Cart
Difference
added

Hypothesis

If the cart shows in-stock products that genuinely go with what is already in it, some shoppers may add one more item to the same order. While the path to checkout stays clear, average order value (AOV) could rise.

Test plan

When to run this test

Order data showing items used together being bought in separate orders, or support tickets asking which items are compatible, suggest that carts tend to reach checkout with a single item. If the suggestions fit, shoppers add a suggested item and still move on to checkout just as easily. If you already see shoppers dropping off between the cart and checkout, find the cause of that loss first; a recommendation module will not remove it. Also confirm before launch that prices and discount information on the recommendation cards match the product pages.

How to measure success

Average order value (AOV)

Compare revenue per completed order, and read this buyer-only average alongside revenue per visitor.

Also track

  • Add-to-cart rateCheck whether the recommendations change add-to-cart behavior.
  • Order completion rateTrack order completion among assigned cart visitors after recommendations are added.
  • Revenue per visitor (RPV)Check whether any change in AOV also changes revenue per visitor.

How to set it up

  • ChangeAdd a complementary-product recommendation module to the variant.
  • Keep constantKeep checkout flow, prices and the main cart CTA unchanged.
  • RelevanceRecommend only in-stock products that are genuinely related to items in the cart.
  • InterpretationMonitor order completion and revenue per visitor alongside AOV.
  • Separate testsTest recommendation count, order, placement and card design separately.

What to watch when reading the result

  1. 1Do not count recommendation clicks as success. Decide on AOV, and read order completion rate and revenue per visitor (RPV) alongside it; if AOV rises while order completion falls, that does not justify keeping the module.
  2. 2This finding is limited to this module in this cart placement; if you plan to use it elsewhere, such as on product pages, test it there again. In this test the module should not push the checkout CTA into the background or sit above it; recommendation count, order, placement and card design each need their own test.
  3. 3AOV is an average over buyers only, so a few large orders can move it. Do not read a small or unclear difference as either a win or no effect. Test whether the add-to-cart rate gap is beyond chance with the A/B test significance calculator; it does not cover averages, so weigh the AOV gap with the same caution.

Frequently Asked Questions

Which products belong in cart recommendations?

Use in-stock products genuinely related to the cart contents. Keep prices and discounts consistent with product pages. Irrelevant or unavailable recommendations can create misleading expectations.

Do more recommendation clicks mean success?

No. Use average order value as the primary outcome and order completion as a guardrail. Recommendation clicks show interaction, but do not establish incremental purchases or revenue.

How can I tell whether recommendations delay checkout?

Compare time from the cart to order completion and report non-completers separately. Longer time may reflect useful exploration. Examine recommendation use as diagnostic evidence while applying the predefined completion and revenue guardrails.