Product Listing Page Filters

Vans:

‘Off the Wall’ since ‘66 - the original cult Californian skate shoes and apparel brand.

For almost 60 years, Vans have been the go-to brand for all things skateboarding.

But it’s not only their technical gear that they’re known for: with a cult following of their own, customers come to their site to pick up shoes and apparel that simply looks good.

As part of the Biglight team, I worked on optimising their PLP filters to create a list of products that was refined but still offered variety.

The splits that were tested:

The original problem:

Learnings from previous tests proved how increased use of filters doesn’t necessarily result in positive impact on key metrics such as Add to Basket or Conversion Rate for Vans customers.

On mobile, users are presented with multiple filter options within the filters panel and this might encourage the filtering activity too much, leaving users with too few products to choose from.

The process:

Working with Biglight’s UX Researcher, I designed the four options based on loose wireframes.

There were various options for certain splits, such as having the colour name below or to the right side on Split B, and we worked collaboratively to refine these.

I then collaborated with the Developer to check quality assurance, before the splits went live.

The findings were then collated by Biglight’s Analyst before reporting back to the client.

The solution:

By enhancing access to key filters on mobile, users who could benefit from refinement could more frequently discover this benefit and see products that were relevant.

Additional UI/interaction-flow improvement also increased the successful use of filters, reduced frustration on PLP and improved chance of product finding, Add-to-Baskets, and ultimately - Conversions.

Testing the concept:

The four splits were tested against the Control (each at 20%) for 21 days on all PLP traffic to the UK website.

The success:

All splits resulted in an increase to Conversion and Revenue, with splits B and C being the most significant at around +3% Conversion and +5.5% Revenue.

When drilling down the traffic to focus only on the Shoes category, split C showed clear favourability, proving that encouraging users to filter shoes by size creates a more frictionless experience.