Meaning of A/B test

Simple definition

An A/B test is a method used to compare two versions of a webpage, email, or ad to see which one performs better. It involves showing each version to a different group of users and measuring which version achieves a specific goal more effectively.

How to use A/B test in a professional context

In digital marketing and web development, A/B testing helps professionals optimize websites, ads, and emails by testing different elements (like headlines or button colors) to improve user engagement, click-through rates, and conversions.

Concrete example of A/B test

A company may test two email subject lines—one saying “20% Off Today” and another saying “Exclusive 20% Discount”—to see which one results in more people opening the email.

What is the purpose of an A/B test?

To make data-driven decisions that enhance performance by identifying which version achieves the desired outcome better.

How long should an A/B test run?

It depends on the traffic volume and goals but typically runs for several days to a few weeks to get reliable results.

Can I test more than two versions?

Yes, testing multiple versions is called multivariate testing, which compares more than two variations.
Related Blog articles
Stephan: From bootcamp student to campus director

Stephan: From bootcamp student to campus director

Stephan joined Le Wagon four years ago to build a tennis fantasy sports startup, found...

Arthur: An energy engineer pivots to data science

Arthur: An energy engineer pivots to data science

Rather than switching industries entirely, Arthur used Le Wagon's intensive Data Science bootcamp to add...

Antonin: A product leader goes data-driven

Antonin: A product leader goes data-driven

With two decades in product strategy and design, Antonin joined Le Wagon's Data Analytics bootcamp...

Suscribe to our newsletter

Receive a monthly newsletter with personalized tech tips.