Definition
An A/B test is an experiment that shows two versions of something, such as an ad, an email subject line or a landing page, to similar groups of people at the same time to see which one gets better results. Version A is usually the current one, and version B changes one thing, so you know what caused any difference.
How it works
You start with a hypothesis, such as 'showing the price in the headline will bring more bookings'. Then you change only that one element, split the audience randomly between the two versions, and decide in advance which metric picks the winner, for example bookings rather than clicks. The test must run long enough to collect enough data, often at least a full week so that weekday and weekend behaviour are both covered. Meta Ads Manager has a built-in A/B test feature, Google Ads offers experiments, and most email tools can test subject lines. Once a clear winner emerges, it becomes the new version A.
Example
Say a gym in Chandigarh tests two subject lines on its newsletter list of 4,000 people who signed up for updates. Half get 'Diwali offer inside' and half get '3 months for ₹4,999, this week only'. The gym measures clicks to the offer page, not just opens. If version B gets clearly more clicks, the gym uses the specific, price-led style for its next campaign and moves on to test something new, such as the time of day it sends emails.
An illustration: the business and the rupee figures are made up to show how the idea works.
Common mistake
Changing several things at once, such as the headline, image and price, so you cannot tell which change made the difference. Another mistake is declaring a winner after one day or a handful of conversions. Small samples swing by chance, so wait until each version has enough results before deciding.
Where you learn it
- Module 2: Website & Landing Pages
- Class: Conversion Rate Optimisation (CRO) Basics
- Module 6: Meta Ads (Facebook & Instagram)
- Class: Budgeting & A/B Testing
Related terms
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