Applitools Announces A/B Testing Support and Slack Integration to Help Teams Manage Quality More Effectively

Applitools, A/B Testing Support, Slack
Applitools Announces AB Testing Support and Slack Integration to Help Teams Manage Quality More Effectively

Applitools, the leading provider of Visual AI-powered test automation, announced enhancements to its flagship product, Applitools Eyes. Applitools Eyes now offers customers the ability to A/B test up to 20 variations of dynamic content and collaborate like never before via Slack or email.

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“A/B testing is a business imperative at GoodRx – it helps our product team deliver the absolute best user experience to our valued customers,” said Priyanka Halder, Sr. Manager, Quality Engineering at GoodRx. “Until now, our quality team struggled to automate tests for pages with A/B tests – we’d encounter false positives and by the time we wrote complex conditional test logic, the A/B test would be over. Applitools implementation of A/B testing is incredibly easy to set up and accurate. It has allowed our quality team to align and rally behind the business needs and guarantee the best experience for our end-users.”

A/B Testing to Validate Multiple Variations of an Application
In order to optimize engagement and increase customer conversion, online businesses offer multiple customized variations of web and mobile screens to their customers. This requirement creates a significant challenge for test engineers to automate the testing process.

A/B testing and more specifically, multivariate testing (MVT), is a technique used to compare multiple variations of the same application to determine which version is more effective with users. The problem is that many teams don’t automate tests to validate multiple variations because it’s expensive, “throwaway” code with endless conditional logic attempting to cover every variation.

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With Applitools Eyes and its new A/B Testing feature, developers and QA professionals can automatically test multiple variations with a single line of code instead of writing complicated testing scripts that cover all the potential options. If any of the variations come up and there are no bugs, the test will pass. By being able to quickly support A/B variations, QA teams are no longer a roadblock to business optimization.