All Latest 550 A/B Tests

In this experiment, product listing were either opened in the same window (control) or opened in a new tab and focused on (variation). Impact on signups and sales was measured.

In this experiment, left column filters (control) were tested against top-aligned and sticky filters (variation). The hypothesis was to increase their visibility. Impact on their use and progression to next step (product/tour detail page) were measured.

Instead of only displaying sort and filters at the top of a listing page, the variation always had them visible with a sticky/floating interaction. Impact on sales was measured.

In this experiment, an inline panel was shown as a product tile. The panel informed customers about a variety of payment options (with detailed information being further presented after a button click). Impact on sales was measured.

In this experiment, some side column filters were made more visible by being automatically expanded. These included: brand, price and country of manufacturing.

In this experiment, the earliest availability dates were displayed underneath product tiles on listing pages. This was a/b tested on a car rental service website. Impact on product adds-to-cart as well as transactions was measured.

In this experiment, a static category theme image at the top of a listing page was tested against the same page but without the extra image. Impact on sales was measured.

In this experiment, infinite scrolling was a/b tested against a paginated one.

In this experiment, conversational filters were tested at the top of some listing pages. Instead of showing one set of product filters, customers were shown three sets of product questions. After selecting each answer, product results would narrow and update further down on the page. Impact on adds to cart and sales were measured.

In this experiment, the effect of having additional static category themed images was tested on category listing pages. Impact on sales was measured.

In this experiment, additional (discounted) products were shown at the top of category listing pages with a link to see more such products ("View All Price Drops"). Impact on overall sales was measured.

In this desktop experiment, 4 product tiles per page (control) were tested against 6. Impact on sales was measured.

In this experiment, a one large product photo (control) was tested against a two-column layout with two smaller images (variation). Impact on sales was measured.

In this experiment, the click area of job listing tiles was expanded to the size of the full job tile. In the control, the click area was smaller - mostly only the job headline, along with additional "view more" links on the right hand column. Clicking the tile or headline would open up a new job details page in both control and variation. Impact on progression and membership sales was measured.

In this experiment, product availabiltiy bars were shown on products with low stock. This was shown on listing pages. Impact on adds to cart and sales was measured.

In this experiment, a two column grid layout (control) was tested against single column layout (variation) with the product information shown to the right. Please note that the screenshot shows repeated products only because it's been sourced from a Figma design file. In reality, the products in the variation were equally diverse as in the control. 

(We've also flipped the A and B to match up with our grid pattern.)

Are more (popular) product results better than none at all? In this experiment, popular products were shown during an empty search result. Impact on sales was measured.

In this experiment, a floating top navigation was shown with a "Join" button. In the control, the navigation was only visible at the top of the page. Also keep in mind that signup starts were also triggered throughout multiple CTAs throughout the page and from particular job detail pages. The a/b test ran on a listing page of Backstage - a casting call job site. Impact on signups  and checkouts was measured.

In this listing page experiment, color sets of the same product were tested against individual products with unique colors (with additional product tiles). Essentially, the A version here contained fewer product items (with color sets), while the B version contained more results and tiles (with grouped products). Impact on total sales was measured.

(The original control and variation was inverted, but was flipped to match the fewer or more results pattern).