Description

A/B testing is one of the most effective techniques marketers can use to improve performance without increasing ad spend. This course teaches you how to confidently design, execute, and analyze A/B tests that lead to measurable improvements in conversions, engagement, and ROI. You’ll begin by learning the fundamentals of experimentation: setting goals, forming hypotheses, selecting variables, and defining success metrics. The course explains how to identify what to test — such as headlines, calls-to-action, images, layouts, subject lines, or offers — and how to prioritize high-impact tests. You’ll then explore how to segment audiences properly and distribute traffic fairly between test variants. Tools like Google Optimize, VWO, Optimizely, ConvertKit, and Meta A/B testing features are covered with real walkthroughs. You’ll also understand how to avoid common mistakes, such as overlapping experiments or drawing conclusions too early. Crucially, you’ll learn how to calculate statistical significance and confidence levels, interpret results correctly, and decide when a test is ready to stop or scale. Sample test reports and dashboards are provided so you can present your findings to stakeholders effectively. The course also explores multivariate testing, personalization experiments, and how to integrate learnings into your broader marketing strategy — across email, landing pages, paid ads, and content. By the end of the course, you’ll be able to use A/B testing as a consistent, scientific method for growth. Whether you’re optimizing your own campaigns or working for clients, you’ll stop relying on guesswork and start building data-backed strategies that drive continuous improvement.