A/B Testing and ABCDEFGHIJ...Z Testing

A/B testing is a method used in software and web development to compare two versions of a webpage, application, or any feature to determine which one performs better. The goal is to experiment with user interactions, engagement, and conversion rates by showing different versions (A and B) to random groups of users. The one that performs better, based on data metrics like clicks, conversions, or time spent, is chosen as the optimal version. Some companies, like Duolingo, have had tremendous success with A/B testing. For example, they tested multiple elements of their learning app to improve engagement and learning outcomes. You can read more about the basic technical details of A/B testing and an example here: <a href="https://www.optimizely.com/optimization-glossary/ab-testing/" target="_blank">A/B Testing Guide</a>.

I don't know how it works, and I wrote the code.

- Many programmers

Our platform now runs thousands and thousands of A/B tests, whether it was intended or not! Every creator who boosts their Bio Link page using our backend is essentially launching their own experiment. We can analyze the performance of every individual page and every advert on a page, using real-time data to determine what works best for each creator and their audience. This kind of experimentation was never our primary goal, but it organically became one of the most valuable aspects of our platform. By tracking the results of these bio link pages and analyzing trends, we’re able to gather insights that benefit not just one creator but the entire community. This is exactly how A/B testing started: small experiments designed to optimize outcomes. Our platform’s unique ecosystem of bio link pages has become a fertile ground for continuous experimentation and learning.

---