Once you find the winner, usually you send 100% of your traffic to the winning variant which is exploitation. In a standard A/B test process, the traffic is split to the two variations equally and test till you reach the statistical significance (a measure of the confidence that the effect we measure is actually present) to determine the winning variant. Multi-Armed Bandit algorithms are machine learning algorithms used to optimize A/B testing.īefore we jump on to bandit algorithms for website optimization, let’s take a quick look at the standard A/B testing process and why you need Bandit algorithms. Here we will be discussing Bandit algorithms for website optimization which is nothing but a more advanced or complex form of A/B testing itself. No doubt, it is the best way to find which versions of your website work best and can bring more conversions. If both versions performed similarly, you may want to consider conducting further testing or seeking additional data to make a decision.For anyone thinking of optimizing your website for more conversions, A/B testing would be a default option. Implement the winning version: If one version outperformed the other, implement the winning version on your live site. View, side-by-side, the algorithmic scores for each version, and the overall query scores and how they ranked against the models. You can compare the results of the different versions (A and B) to see which performs better.Īnalyze the results: Use the data from the A/B test to determine which version performed better and why. Run the test: Use the search engine simulator to test your changes and see how they perform. Use your production environment calibrated search engine model: This will allow for a more accurate simulation of how your changes will perform in the real world. Implement your changes: Make the changes to your test site according to the auto-generated optimization tasks and their recommendations. This could include changes to your website's content, structure, or design. This can be a separate domain or a subdomain of your existing site.Ĭhoose your optimizations: Decide which auto-generated optimization tasks you want to test. Set up a test site: First, create a test site on which you can conduct your A/B test.
How to do A/B testing with search engine models:
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