Experimentation is central to making evidence-based decisions, and this is where A/B testing has always shined.
But with the advent of AI, we now have tools for AI A/B testing, making experimentation smarter, faster, and infinitely more manageable.
AI A/B testing gets you real-time reports and lets you test multiple hypotheses in a few clicks. To explore the magic that AI brings to A/B testing, I spoke with CRO experts who shared their unique insights.
On top of that, I’ll also take you through the benefits, limitations, and best practices for integrating AI into your A/B testing process.
In this article:
- Why use AI for A/B testing?
- Benefits of AI in A/B Testing
- Limitations of AI in A/B Testing
- How to Use AI for A/B Testing
Why use AI for A/B testing?
A/B testing is a research method used to analyze landing pages, user interfaces, or other marketing prototypes to determine the best version before full rollout.
You split your audience into two groups or …