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A/B Testing for Marketers

A/B Testing for Marketers
Marketing Analytics & Tools

A/B Testing for Marketers

Learn how to test marketing ideas properly so each change is judged on evidence. This e-learning material covers writing a hypothesis, choosing what to measure, deciding how long a test should run and reading results without fooling yourself. It suits marketers and business owners who want to improve pages, emails and ads step by step instead of changing everything at once.

Levels
4
Starting from
260 credits
Category
Marketing Analytics & Tools
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Beginner

  • What this level covers

    It covers what an A/B test is, writing a clear hypothesis, choosing one change to test, picking a primary metric and splitting traffic fairly. You also see simple examples on emails, landing pages and ads.

  • Who it suits

    Made for marketers who have heard of A/B testing but never run a test, or who have run one without a clear plan. It suits beginners who want a simple, reliable method to compare two options.

  • What you can apply afterwards

    You should be able to plan a basic A/B test from hypothesis to result, avoid changing too many things at once and describe clearly which version performed better and why that matters.

Level 1

260 credits

Inside this material

A/B testing sounds simple: show two versions and keep the winner. In practice, many tests end with unclear results because the question, the measure or the timing was not planned. This e-learning material builds the planning habits that make tests worth running.

Early levels explain hypotheses, control and variant groups, primary and supporting metrics, and why stopping a test too early leads to false conclusions. Later levels cover sample size, statistical confidence in plain language, testing on low-traffic sites, and keeping a record of results so your team learns from every experiment, including the ones that do not win.

You apply each idea by drafting a testing plan for your own website, email list or advertising, giving you a prioritised list of experiments and a simple template for documenting what you find.