A/B testing is a research method used to analyze landing pages and user interfaces by dividing the audience into groups to determine the best version.
With AI, we automate much of A/B testing's heavy lifting, delivering clear insights without the usual challenges of traditional testing methods.
AI systems, particularly those using machine learning, can sift through massive datasets, helping generate fresh test ideas and refining suggestions as data accumulates.
The integration of AI helps streamline data modeling and test customization, ensuring effective targeting and analysis in A/B testing processes.
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