# Testing Product Recommendations Inside the Cart

Page: https://alidemirbas.com.tr/en/lab/ab-test-library/tests/testing-product-recommendations-inside-the-cart

## 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.

## 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.

## Primary metric

**Average order value (AOV)**: Compare revenue per completed order, and read this buyer-only average alongside revenue per visitor.

## Other metrics

- **Add-to-cart rate**: Check whether the recommendations change add-to-cart behavior.
- **Order completion rate**: Track 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.

## What to check before and during the test

- **Change**: Add a complementary-product recommendation module to the variant.
- **Keep constant**: Keep checkout flow, prices and the main cart CTA unchanged.
- **Relevance**: Recommend only in-stock products that are genuinely related to items in the cart.
- **Interpretation**: Monitor order completion and revenue per visitor alongside AOV.
- **Separate tests**: Test recommendation count, order, placement and card design separately.

## What to watch when reading the result

- Do 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.
- This 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.
- AOV 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](https://alidemirbas.com.tr/en/calculators/ab-test); 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.