# List View vs Grid View on Category Pages A/B Test

Page: https://alidemirbas.com.tr/en/lab/ab-test-library/tests/list-view-vs-grid-view-on-category-pages-ab-test

## Hypothesis

A grid may make quick comparison easier by placing more products side by side, while a list may make close inspection easier by giving each product more room. The layout that fits how shoppers browse this category may be the one that lifts the product detail click-through rate.

## When to run this test

Heatmaps showing card details being skipped, session recordings of visitors opening a product and returning to the list right away, or heavy use of the view switcher suggest that the card layout on the category list makes choosing harder. If the idea holds, one layout brings more product detail visits without a material drop in products viewed. Before launch, decide how to handle visitors with a saved layout preference; if the problem is missing product details or poor image quality, fix that first.

## Primary metric

**Product detail click-through rate**: Compare product-page visits among visitors who see each category-list layout.

## Other metrics

- **Purchase conversion rate (CR)**: Check whether purchases change.
- **Products viewed**: Make sure the number of products actually seen does not fall materially.
- **Page load time**: Ensure the layout change does not slow the page.
- **Return-to-list rate**: Returning to the list can be normal comparison behavior; interpret it alongside subsequent actions.

## What to check before and during the test

- **Layout**: Compare list and grid views with the same product information.
- **Saved preferences**: Decide how to handle visitors with a saved layout preference; do not override it.
- **Keep constant**: Keep sorting, prices, product details and image quality unchanged.
- **Density**: Review the number of products seen alongside clicks.
- **Category**: Check category differences before expanding the result.

## What to watch when reading the result

- Even if product detail visits rise, do not call that layout the winner when products viewed drop materially or the page slows down. Do not treat returns to the list as a problem on their own; read them together with subsequent actions and purchase conversion rate.
- The existing view switcher and preference saving must work the same way in both arms; if either broke, the gap says nothing reliable about the layout. Report separately the share of visitors in each arm who switch views themselves, since that also tells you something about the layout.
- The result may vary by category, so do not apply a winner from one category to all of them. If category-level differences are likely to be small, check with the [sample size calculator](https://alidemirbas.com.tr/en/calculators/sample-size-calculator) whether each category has enough visitors, and leave the result open where it does not.

## Frequently Asked Questions

### What happens to users with an existing layout preference?

Define their eligibility beforehand and preserve explicit saved preferences. Keep the view switcher and preference-storage behavior consistent in both arms.

### Are more returns to the list a problem?

They can be normal comparison behavior. Interpret them with subsequent actions and actual product exposure. Use product-page reach as the primary outcome.

### Can one category’s winning layout be applied everywhere?

Not automatically. Product information needs differ. Assess relevant categories before extending the result rather than treating one experiment as a universal layout rule.