A/B Testing
Define
Testing two targeted variations of a single page to analyse which one performs better
A/B testing is also known as 'split testing". Experimenters aim to discover whether changing specific elements can influence the performance of a website app. advert or email campaign against a goal. From studying user behaviour (for example, website data), experimenters devise a hypothesis to test. They then produce a variation of a targeted element. Users are split between the 'control (or original) and variant simultaneously, and left to interact with the product aver n sel period of time. Almost anything on your website, app or campaign can be tested, but some example include:
- Headlines
- Subheadings
- Paragraph Text
- CTA's
- Images
Following close examination of how the user engages with the new design, experimenters use statistical analysis to determine which version (the control or the now) performs best against the pre-sel goal. They usually focus on the overall conversion rate. For instance, experimenters could change the colour or layout of a certain element and Lest whether this has a positive negative or no effect on visitor behaviour and conversion rates.
If a user's engagement with a variant is high. and the change boasts an excellent or improved conversion rate, experimenters select the version with higher performance They use it for future iterations of a campaign (for example, emails) or implement it on a web page or app. A/P lasting lools often have calculators to help experimenters ensure results are statistically significant and test are not being conc uced too early.
Through close, data-driven analysis, A/B testing removes the guesswork from website optimisation and ensures that changes yield positive results.