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Original 2026-01-01

Modified 2026-02-28

1 <p>This course will teach you the fundamentals of A/B testing and optimization - from basic concepts, common pitfalls, and proven methods, all the way through evaluating and scaling your results. </p>

2 <p>15 Lessons</p>

3 <p>Lesson 1</p>

4 <h4><a>An introduction to A/B testing and optimization</a></h4>

5 <p>A comprehensive guide to A/B testing, explaining the differences between A/B and multivariate testing, how to conduct tests in a structured and progressive way, and the thought process behind choosing the right experiment.</p>

6 <a>Read Article</a><a></a><p>Professor David Steinberg of KPA Group</p>

7 <a></a><p>Professor Ron Kenett of KPA Group</p>

8 <p>Lesson 2</p>

9 <h4><a>A/A testing and decision making in experimentation</a></h4>

10 <p>A/A testing is meant to check that the underlying system is running properly. In this post, we’ll cover some of subtle issues to consider as you run them.</p>

11 <a>Read Article</a><a></a><p>Data Science and Predictive Modeling Expert</p>

12 <p>Lesson 3</p>

13 <h4><a>Why reaching and protecting statistical significance is so important in A/B tests</a></h4>

14 <p>Delve deeper into the mechanics of “classic” A/B testing, become familiar with the actual meaning of statistical significance, and discover the pitfalls threatening the validity of your test results.</p>

15 <a>Read Article</a><a></a><p>Lesson 4</p>

16 <h4><a>Choosing the right traffic allocation in A/B testing</a></h4>

17 <p>Learn how to choose the right traffic allocation method for your A/B tests and avoid common pitfalls, ensuring impactful, valid results.</p>

18 <a>Read Article</a><a></a><p>VP of Product, Dynamic Yield</p>

19 <p>Lesson 5</p>

20 <h4><a>Understanding conversion attribution scoping in A/B testing</a></h4>

21 <p>Understand the influence of different conversion attribution configurations on your personalization and A/B testing campaigns.</p>

22 <a>Read Article</a><a></a><p>VP of Product, Dynamic Yield</p>

23 <p>Lesson 6</p>

24 <h4><a>Choosing the right conversion optimization objective</a></h4>

25 <p>Conversion optimization can be a very powerful process, but it’s easy to get carried away by the methodology. Here’s how to choose the right optimization objective.</p>

26 <a>Read Article</a><a></a><p>Data Science and Predictive Modeling Expert</p>

27 <p>Lesson 7</p>

28 <h4><a>Frequentist vs. Bayesian approach in A/B testing</a></h4>

29 <p>The industry is moving toward the Bayesian framework as it is a simpler, less restrictive, more reliable, and more intuitive approach to A/B testing.</p>

30 <a>Read Article</a><a></a><p>Professor Ron Kenett of KPA Group</p>

31 <a></a><p>Professor David Steinberg of KPA Group</p>

32 <p>Lesson 8</p>

33 <h4><a>Guidelines for running effective Bayesian A/B tests</a></h4>

34 <p>In this post, we describe the basic ideas behind Bayesian statistics and how they feed into business decisions you will need to make at the end of a test.</p>

35 <a>Read Article</a><a></a><p>Lesson 9</p>

36 <h4><a>Beyond A/B testing: Multi-armed bandit experiments</a></h4>

37 <p>Learn how multi-armed bandit algorithms conclude experiments earlier than the classic A/B test while making fewer statistical errors on the way.</p>

38 <a>Read Article</a><a></a><p>Director of Enterprise Solution Engineering, Dynamic Yield</p>

39 <p>Lesson 10</p>

40 <h4><a>Client-side vs server-side A/B testing and personalization</a></h4>

41 <p>An in-depth analysis of the most important technical considerations when comparing client-side vs server-side rendering.</p>

42 <a>Read Article</a><a></a><p>Lesson 11</p>

43 <h4><a>Segmented A/B tests: Avoiding average experiences</a></h4>

44 <p>One of the biggest mistakes a company makes when A/B testing is selecting an average audience. Instead, they should be making segmentation an essential part of their test design - here’s how.</p>

45 <a>Read Article</a><a></a><p>Lesson 12</p>

46 <h4><a>The impact of A/B tests and personalization on SEO</a></h4>

47 <p>Read about Google’s official SEO advice on A/B or multivariate testing, and how to minimize the possible impact of A/B testing on SEO.</p>

48 <a>Read Article</a><a></a><p>Data Science and Marketing Analytics Expert</p>

49 <p>Lesson 13</p>

50 <h4><a>There are no failed A/B tests: How to ensure every experiment yields meaningful results</a></h4>

51 <p>With a comprehensive testing methodology and a renewed perspective toward experiment analysis, marketers can start gleaning meaningful insights from every A/B test, no matter the outcome.</p>

52 <a>Read Article</a><a></a><p>Senior Director of Marketing, Dynamic Yield</p>

53 <p>Lesson 14</p>

54 <h4><a>How to analyze and interpret A/B testing results</a></h4>

55 <p>Analyzing A/B testing results is one of the most important stages of an experiment. But it’s also the least talked about. Here’s how to do it right.</p>

56 <a>Read Article</a><a></a><p>Senior Director of Marketing, Dynamic Yield</p>

57 <p>Lesson 15</p>

58 <h4><a>Building an experimentation growth plan: A Kopari Beauty case study</a></h4>

59 <p>A conversation on personalization, conversion optimization and what makes the coconut the most kickass ingredient known to (wo)man with cosmetics retailer Kopari.</p>

60 <a>Read Article</a><p>Explore more learning paths</p>