The best success stories often come directly from the customer. We have some clients who work with us to conduct A/B test campaigns while others are self-sufficient and manage their entire A/B testing program without our involvement. For this latter group of customers, we don’t often hear about their success. So when we have the opportunity to meet up and talk with these folks about their experiences, we hear a lot of valuable insights we haven’t heard before.
At a recent breakfast meeting, we gathered some existing clients and prospects to discuss optimization success stories and provide real-world examples of A/B testing success. The meeting quickly evolved from a standard vendor presentation to an interactive, engaging conversation, and a central theme of being able to A/B test any site change emerged.
Imagine, being able to A/B test every single change to your site. The task seems daunting, but is achievable with a systematic approach to setting up and deploying A/B tests. The author in the Experimentation Culture blog post on the Harvard Business Review site states:
“At Shutterstock, where I work, we test everything: copy and link colors, relevance algorithms that rank our search results, language-detection functions, usability in downloading, pricing, video-playback design, and anything else you can see on our site (plus a lot you can’t see).”
The discussion at our breakfast truly echoed this mindset. For example, one of our clients, who deploys A/B tests for all front-end and back-end changes commented “Without testing, how can you know what is having a positive or negative effect on your conversions?”
As optimization programs advance, organizations are becoming more open to an all-encompassing approach to A/B testing. In order to do this, they need to be able to run more A/B tests in less time. These organizations not only A/B test all aspects of their site, but also set goals to run hundreds, if not thousands, of A/B tests in a year. And these A/B tests create measurable wins for marketers, product managers, and developers. This is the future of optimization, and it’s already started happening.
What is the optimization culture like at your organization? Have you seen it evolve as your A/B testing program matures? If so, in what way? We’d love to hear your thoughts!
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