What you need to know about AB Testing

You might have heard some talk recently about AB testing. So what’s it all about and what relevance does it have for your business?

AB testing (also known as Split Testing) is a method of comparing two versions of digital content. It might relate to a website, email marketing call to action or app against each other to determine which one performs better. If you are not sure, perhaps hiring a good marketing manager to guide you through this process would be useful.

AB testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal.

Testing takes the guesswork out of the picture and enables data-informed decisions that shift business conversations from ‘we think’ to ‘we know’. By measuring the impact that changes have on your metrics, you can ensure that every change produces positive results. If you don’t have time to analyse such data, perhaps outsourcing your marketing would be a good strategy to consider.

AB testing often involves subtle content variations which can drive significant conversion results by using testing with colour, copy, video content, images, layout and price offers.

A/B testing allows companies to make careful changes to their user experiences while collecting data on the results. This allows them to construct hypotheses, and to learn better why certain elements of their experiences impact user behaviour.

More than just answering a one-off question or settling a disagreement, AB testing can be used consistently to continually improve a given experience, improving a single goal like conversion rate and return on investment over time.

Whatever your experiment’s outcome, use your experience to inform future tests and continually iterate on optimising your digital user experience. The following is an AB testing framework you can use to start running tests:

  • Collect data
  • Identify goals
  • Generate hypothesis
  • Create variations
  • Run experiment
  • Analyse data

Are you ready to introduce AB testing into your marketing strategy?

 

[Source: Optimizely – abridged]