# Filters on collection pages: -6.4% conversion, -33.2% revenue/visitor

- Outcome: Lost
- 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/attribute-filters-added-to-collection-pages/
- Page: https://liftarchive.com/test/cc-attribute-filters-added-to-collection-pages/

Adding a filter panel to collection pages lowered conversion rate by 6.4% and revenue per visitor by 33.2%. Clean Commit ran this test for an anonymized Shopify store and published it in its A/B test library. Shoppers browsed more and added to cart more, but the drop in order value, mostly on mobile, outweighed it.

## Result

**-6.4% conversion, -33.2% revenue/visitor**

- Revenue per visitor: -33.2%, driven by average order value falling 29.2%.
- Conversion rate: -6.4%, and orders: -5.3%. The conversion drop is close to a coin flip, with a 52.4% probability the variant was actually better.
- Mobile average order value fell 40.4%, the main source of the revenue loss.
- Add-to-cart rate: +4.8%, and bounce rate: -40.5%. Shoppers engaged more without buying more.

## Control

Collection pages had no filtering.

## Variant

A filter panel let shoppers narrow products by style, color style, text layout, text arch and city. It sat on the left on desktop and in a collapsible top drawer on mobile, allowed several values per filter, and remembered choices.

## Why it likely lost (our reading)

- Filters may have pushed shoppers to narrow down to one exact item, rather than browsing and adding several.
- On mobile, a drawer that changes the listing can hide products that would have been picked up while scrolling.
- With a small sample, a few large orders in the control group could explain much of the order value gap.

## Caveats

About 5,196 mobile visitors were noted and duration was not shared. The conversion drop was near a coin flip, and the revenue loss may be partly due to a few large orders.

## How to run this test

- Hypothesis: If we let shoppers filter collections by the attributes they care about, then more will buy because they reach the right product faster.
- Primary metric: Revenue per visitor
- Guardrail: Average order value
- Guardrail: Conversion rate
- Guardrail: Mobile revenue per visitor
- Who should test it: Stores with large collections where products differ on clear attributes. If your collections are small or shoppers tend to buy several items, filters may cut browsing and order size, as here.

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Credit: Clean Commit ran this test and owns the result. Summary and commentary by LiftArchive (https://liftarchive.com/test/cc-attribute-filters-added-to-collection-pages/).
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.