How A/B testing works

A typical A/B test follows a straightforward process:

1. Choose one element to test, such as a headline or button.
2. Create two variations, known as version A and version B.
3. Split your audience so each version is shown to a similar number of people.
4. Measure the results using a clear metric such as conversion rate or click-through rate.
5. Keep the version that performs best.

Running tests this way helps reduce guesswork and improves performance over time.

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What can be tested

A/B testing can be applied to many parts of marketing and digital products, including:

• Landing page headlines
• Call-to-action buttons
• Page layouts
• Advertising creatives
• Email subject lines
• Website images
• Pricing or offers

Small changes can sometimes lead to meaningful improvements in results.

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Why A/B testing matters

A/B testing helps businesses improve performance without relying on opinion or internal debate. Instead of guessing what people prefer, you can test ideas and let the data show what works.

Over time, this leads to better conversion rates, clearer messaging, and more effective marketing.

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A/B testing and conversion optimisation

A/B testing is closely linked to conversion rate optimisation. While conversion optimisation focuses on improving how many visitors take action, A/B testing is one of the main tools used to find the best way to do that.

For example, a business might test different page layouts to see which one generates more sign-ups or sales.

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Simple example

Imagine a landing page with a call-to-action button that says “Start now”.

A business might test a second version that says “Get started today”. If the second version leads to more clicks or sign-ups, it becomes the new default.

This small change can lead to measurable improvements in performance.

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When to use A/B testing

A/B testing works best when there is enough traffic to produce reliable results. It is commonly used when improving:

• Website conversion rates
• Advertising performance
• Email marketing campaigns
• Product onboarding experiences

Rather than making large changes all at once, teams often run a series of smaller tests that gradually improve performance over time.

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