A/B testing is essential for optimising websites, apps, and marketing campaigns. However, traditional A/B testing can be time-consuming, resource-intensive, and limited in scope. This course analyses the role of AI in overcoming these challenges, enabling marketers and product managers to conduct more sophisticated experiments, uncover hidden patterns, and personalise experiences at scale. Through real case studies, you will learn how to leverage AI to make data-driven decisions that drive actual business results.
Learning Goals
Understand the fundamentals of AI-driven A/B testing principles and methodologies and how they differ from traditional methods.
Explore how machine learning algorithms can analyse user behaviour, predict outcomes, and optimise test variations.
Explore various practical tools and techniques to design and implement AI-driven A/B testing experiments.
Learn how algorithms can dynamically allocate traffic to high-performing variations, maximising conversions and ROI.
Discover how AI can create personalised experiences for individual users, leading to higher engagement and conversion rates.
Gain insights into interpreting AI-generated results and making informed decisions based on data.