A Practical Tutorial for Using AI in A/B Testing

Traditional A/B testing is a method used to compare two versions of a digital experience, such as a landing page, headline, or call-to-action, to find out which one performs better. 

However, traditional A/B testing often struggles in fast-moving digital environments. It depends heavily on human intuition, manual setup, and slow feedback cycles, making it hard to keep up with rapidly shifting user expectations.

With the rise of AI-powered platforms, this process is undergoing significant evolution. Teams can now automate testing, personalize experiences in real time, and uncover deeper insights. Whether you're applying AI for UX design, conducting AI for UX research, or streamlining feedback with AI for user testing, intelligent experimentation helps you move faster and make better decisions.

In this guide, we’ll unpack the concept of AI-driven A/B testing, explore its business benefits, and offer a step-by-step tutorial on how to integrate it into your workflow effectively. Whether you're a product manager, marketer, or designer, this practical breakdown will help you unlock the full potential of intelligent experimentation.

Read more: https://lollypop.design/blog/2025/july/ai-in-a-b-testing/