# Redesigned collection filters: +8.7% CR, not significant

- Outcome: Flat / inconclusive
- Page type: Collection page (Ecommerce)
- Elements: Filters, sorting & site search
- Test run by: [Clean Commit](https://liftarchive.com/practitioners/clean-commit/)
- Commentary by: LiftArchive (our analysis, not theirs)
- Original source: https://cleancommit.io/ab-tests/enhanced-collection-filters/
- Page: https://liftarchive.com/test/cc-enhanced-collection-filters/

Redesigning the collection page filters lifted conversion rate by 8.7%, but the result was not statistically significant, so we treat it as inconclusive. Clean Commit ran this test for a Shopify store and published it in its A/B test library, where it was labeled a positive signal. Over 35,108 visitors and 29 days the variant had an 85.6% chance of beating the original, and revenue per visitor slipped 1.5%.

## Result

**+8.7% CR, not significant**

- Conversion rate: +8.7%, with an 85.6% probability of beating the original. Not significant.
- Orders: +7.7%. Mobile drove the gain, with conversion up 12.4% across 27,453 mobile visitors.
- Average order value: -9.0%. Negative.
- Revenue per visitor: -1.5%, mostly from desktop. Slightly negative, so the extra orders did not add revenue.

## Control

Collection pages used the store's original filters.

## Variant

Filters were regrouped into product type, size, color, in stock, rating and price, ordered by relevance, with multi-select where it fit. Controls became checkboxes, swatches, sliders and chips, with Apply and Clear All buttons and a summary of active filters.

## Why it likely came out this way (our reading)

- Clearer groups and familiar controls likely made it easier to narrow a long list, especially on mobile.
- An active-filters summary and Clear All reduce the hassle of undoing choices, which can keep shoppers browsing.
- Narrower results may have led shoppers to buy fewer or cheaper items, which would explain the lower order value.

## Caveats

The test ran 29 days on 35,108 visitors without reaching significance. Several filter changes were tested together, so the result can't be credited to one of them.

## How to run this test

- Hypothesis: If we regroup filters into clear categories with better controls and an active-filters summary, then conversion rate will rise because shoppers reach relevant products with less effort.
- Primary metric: Revenue per visitor
- Guardrail: Conversion rate
- Guardrail: Average order value
- Guardrail: Filter usage rate
- Who should test it: Stores with large, varied catalogs and mostly mobile traffic, where filters are hard to use today. It probably won't matter much if most shoppers never touch the filters.

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Credit: Clean Commit ran this test and owns the result. Summary and commentary by LiftArchive (https://liftarchive.com/test/cc-enhanced-collection-filters/).
Usage: Free to use, quote and build on, with credit and a link: name the practitioner or organization that ran the test and link to its LiftArchive page. The results belong to the practitioners who ran and shared them; the summaries and commentary are LiftArchive's.