A/B testing removes guesswork from Web apps
June 22, 2012 —
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Continuous integration isn't only pushing developers to release more often, it’s enabling them to use A/B testing more effectively. Companies like Omniture, SitesSpect and Webtrends have all pushed out A/B testing software to help developers make better choices. And that's the promise of A/B testing: no more guesswork.
What exactly is A/B testing, and how can it be used in software? Simply put, it's the act of putting percentages for use on digital assets. In Farmville, for example, an A/B test could be set up to see how many users purchase an in-game pig when it is offered to them, versus how many purchase an in-game cow. A/B testing software would push out either a pig or a cow to Farmville players based on their profiles, or just based on a 50/50 chance, as determined by the developers.
Bob Garcia, optimization solution sales director for North America at Webtrends, has been working in the A/B and multivariable test market for many years now, and he said that proper use of such tests can have a dramatic impact on the bottom line.
He told the story of a recent test consulting engagement Webtrends had with a major motorcycle retailer. “We worked with them on tests for their checkout process. They started with little tests in their existing site, like changing button location, the size of the text, and adding content. They did this incrementally. Some of the tests didn't derive statistical differences, but then they went and built an entirely separate, parallel checkout process. When they did that, they saw an improvement, which has translated into US$2.5 million in extra revenue by reducing abandonment rates. That's a great use case where A/B testing is really most useful, in testing really big concepts.”
Thus, most of the work in A/B testing is designing the alternative layouts and deciding what to test. Garcia said A/B testing is much more effective on large changes rather than simple ones like button relocation and text adjustments.
Related Search Term(s): A/B testing, SaaS
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