A/B test

What is an A/B test?

An A/B test is a controlled experiment where you compare two versions of a page, ad or element to see which one performs better. Version A is the current control and version B is a variation with one deliberate change.

In digital marketing, an A/B test helps you move from gut feeling to data driven decisions. You show version A to part of your audience and version B to another similar group, then you compare results against a clear metric such as click through rate, conversion rate or revenue per session.

How an A/B test works in practice

An effective A/B test starts with a specific question, for example whether a shorter checkout form will increase completion rate. You create a hypothesis, design one variation that addresses it and split traffic between the original and the variant.

During the A/B test you keep all other factors constant, including targeting, traffic source and timing as much as possible. Once you reach a statistically reliable sample size, you analyse the data to see if version B truly outperforms version A, or if the difference is just noise.

For e commerce and B2B teams, an A/B test is ideal for optimising landing pages, pricing messages, lead forms and ad creatives. The same principle applies across paid media campaigns, email flows and website UX.

What you can test

An A/B test works best when you change one meaningful variable at a time. Typical test elements include headlines, calls to action, button colours, hero images, form length, pricing displays and trust elements like testimonials or guarantees.

In performance advertising, you might run an A/B test on different creatives in Meta ads to see which combination of visual and copy drives the lowest cost per acquisition. For SEO and growth marketing, you can test page layouts, content blocks or internal linking patterns to maximise engagement.

Why A/B testing matters for growth teams

• Removes guesswork An A/B test gives you evidence, not opinions, so you can defend decisions to stakeholders.
• Improves ROI Small conversion lifts from repeated A/B tests compound into significant revenue gains over time.
• Lowers risk You trial changes on a portion of traffic before rolling them out fully.
• Builds a learning culture Regular A/B tests create a habit of experimentation inside your marketing and product team.
• Aligns teams Product, design and marketing can rally around clear test results instead of subjective preferences.

Together, these benefits make the A/B test a core tool for ambitious teams that want predictable, scalable growth instead of one off wins.

Best practices for running an A/B test

Define a single primary metric before you start, such as sign ups, qualified leads or add to carts. Run your A/B test long enough to capture normal weekday and weekend patterns, and avoid stopping early just because one variant looks ahead after a day or two.

Make sure you test on meaningful traffic volumes and focus on changes that can realistically move revenue. Document every A/B test you run, including hypothesis, setup and learnings, so your team builds a reusable knowledge base instead of repeating the same ideas.

For growth minded B2B and e commerce leaders, mastering the A/B test is one of the fastest ways to squeeze more performance from existing channels and budgets without increasing ad spend.