All Latest 552 A/B Tests

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Only Significant A/B Tests

Only show the highest quality tests with a p-value < 0.05

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Test #136 on Missetam.nl by Marlies Wilms Floet Dec 18, 2017 Desktop Product

Marlies Wilms Floet Tested Pattern #42: Countdown Timer In Test #136 On Missetam.nl

De Nieuwe Zaak (a Dutch ecommerce agency) tested a countdown timer on an ecommerce site. The variation showed how many hours and minutes were left in order to be eligible for next day delivery. The variation beat the control which did not have this element of urgency.

Test #134 on Kenhub.com by Niels Hapke Dec 14, 2017 Desktop Product

Niels Hapke Tested Pattern #41: Sticky Call To Action In Test #134 On Kenhub.com

In this beautiful test, the key change was the introduction of a larger call to action linking to a premium / upgrade screen. The call to action was placed on the left sidebar which was floating. This is a great example of providing visibility to important elements by making them persistent.

Test #133 on Bing.com by Ronny Kohavi Dec 13, 2017 Desktop Mobile Listing

Ronny Kohavi Tested Pattern #43: Long Titles In Test #133 On Bing.com

In 2012 a Microsoft employee working on Bing had an idea about changing the way the search engine displayed ad headlines. Developing it wouldn’t require much effort—just a few days of an engineer’s time—but it was one of hundreds of ideas proposed, and the program managers deemed it a low priority. So it languished for more than six months, until an engineer, who saw that the cost of writing the code for it would be small, launched a simple online controlled experiment—an A/B test—to assess its impact. Within hours the new headline variation was producing abnormally high revenue, triggering a “too good to be true” alert.

HBR, September–October 2017 Issue, https://hbr.org/2017/09/the-surprising-power-of-online-experiments

Note: This experiment was a solid success and replicated multiple times over a period of months. It worked at Bing and had a profound influence. The only reason why we atributed a 0.25 point (a "Maybe") was because we don't have the exact sample size and conversion data.

Test #132 on Sjvc.edu by Phillip Barnes Dec 12, 2017 Mobile Home & Landing