The Best A/B Testing Fail of the Week: When No News is Great News

April 19, 2018

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This week’s Best A/B Testing Fail of the Week celebrates the anticlimactic results. The A/B tests that you expect to make all the difference but turn up nothing. More often than you might think, big wins can come out of unimpressive results. Here’s one case where that was especially true.

Big Change Makes No Difference

A large women’s clothing retailer wanted to know what types of images led to more product purchases. They implemented an A/B test consisting of one variation with clothing shown on professional models against another variation with clothing shown against a plain backdrop. The brand hypothesized that the models would sell more clothing, because they would demonstrate how the items might be worn on a real person. Instead, they found no difference in purchase rates, average order values, or revenue between the two variations.

Glass Half Full

The brand saw these results as a huge win. Photographs of clothing without models cost much less to produce. While the product images without a model did not increase sales, they did save the company a large portion of its budget without hurting sales. The end result: the company saves much of its photography budget while maintaining the rate of revenue. That sounds like a win to us.

Read More Best Testing Fails                           Read More Case Studies

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Luke Hardwick is a Manager of Customer Success at SiteSpect, consulting for SiteSpect users on their optimization and personalization road maps and projects. Luke is based in London and has experience as an conversion rate optimization specialist across many softwares before landing at SiteSpect.

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