A/B Testing definition

What is A/B Testing?

A/B Testing is a method of comparing two versions of a webpage or an app to determine which one performs better. It involves testing two different versions of a webpage or app with a small group of users to see which version performs better. The version that performs better is then rolled out to the rest of the users.

When did it start?

A/B Testing has been around for many years, but it became more popular in the early 2000s with the rise of e-commerce and online marketing. The first recorded A/B test was conducted by Google in 2000, but it wasn't until 2007 that A/B testing became more widespread.

What are the best practices?

There are several best practices to follow when conducting A/B testing, including defining clear goals, testing one variable at a time, and ensuring that the sample size is large enough to produce statistically significant results.

Who are the thought leaders?

Here are some of the top insights from Joanna Wiebe, Peep Laja, and Chris Goward in the field of A/B testing:

• Joanna Wiebe:
  • Use persuasive copywriting to increase conversions.
  • Test different headlines and value propositions to find the most effective messaging.
  • Focus on the customer's pain points and desires to create compelling copy.
• Peep Laja:
  • Use A/B testing to identify and fix user experience issues.
  • Test different variations of your website or app to determine which one performs best.
  • Use data to inform your decisions and continually optimize your site or app.
• Chris Goward:
  • Use a structured approach to A/B testing, including hypothesis development and test design.
  • Test one variable at a time to achieve accurate results.
  • Focus on long-term optimization to achieve sustainable growth.

These insights can help guide businesses in their A/B testing efforts and improve their overall performance.

How to get started in 3 steps

1. Define clear goals for your A/B test
2. Create two versions of your webpage or app
3. Test each version with a small group of users and measure the results

Most popular tools

Some of the most popular A/B testing tools include Optimizely, Google Optimize, and VWO.