The world of digital marketing is all about striking the right chord with the audience. If you know a little about digital marketing, you would know what A/B testing is and its importance in getting followers, subscribers and customers. But if you’re wondering what in the world that is, A/B testing is an experimental way of comparing two variations of a campaign or ad to see which works best. You divide your audience and show one half a certain campaign, the other half the other campaign and decide which performed better. The variations could be a different landing page, or ad text or ad headline etc. This way you decide what worked better and improve your campaign accordingly. Some advantages of using A/B testing on an e-commerce site:
Artificial Intelligence is changing the landscape of A/B testing The thing is, while you get quick results with A/B testing, they’re not quick enough when you want to test out hundreds of variations. Let us take a visual example.
In this case, a visitor could take two paths which would either “convert” or “not convert”. Here, a conversion means getting a better value of the metric you are measuring the performance against. eg. Time spent on site, sales.
What if you want to test more than just one page? Here, your visitor could either directly go from web page 1 to converting or not converting. But he could also go to web page 2 instead and vice versa. This adds complexity to the A/B testing routine. You will have to keep track of the transitions happening on your site. Enter, AI Using Artificial Intelligence, you could test all your hypotheses simultaneously, instead of a linear fashion. It follows the idea of evolution and does continuous optimisation by rejecting ideas that didn’t work. Based on the traffic that comes to the site, the AI software can start understanding what ideas help convert better and prune away ideas that failed. The concept of evolution — survival of the fittest with a dash of mutation
Ascend uses this technique to come up with evolving site designs to increase conversions and decrease customer acquisition costs. Large scale multivariate testing is done to test multiple variations at the same time. The winning variations are combined to achieve goals. The power of evolutionary algorithms is so strong that the best of 1 million designs can be selected by testing out just ~500 of them
End Notes There are several drawbacks to A/B testing that can easily be overcome with the help of AI technology. A/B testing requires a lot of manual effort and often, by the time the changes are implemented, the landscape has already changed. AI works excellently when scaling the process of continuous improvement. Cosabella, a leader in the lingerie space, got 38% more conversions by using Ascend’s technology.