What is an A/B Test?

A/B testing (also known as split test) is a technique used to test the impact of different design/content combination on customers. The main idea is to present different formats to different customers (chosen randomly), to see which one performs better. It’s a concept widely used for landing pages, email marketing or to improve eCommerce funnels.

Why A/B Testing is Important for your business

Performing an A/B test allows to choose the right design/workflow to get more conversions: instead of trying different solutions in different moments, A/B tests are able to validate single assumptions, thus creating a constantly improving environment.

A practical example: say an eCommerce website has two different ideas on how to design the checkout page, so the manager creates an A/B test to choose the best one. Both pages are created and each customers see a random one. After a while, seeing which is the better performing page, the other page is closed and the “best” page remains online.

About Vivocha’s A/B Testing

It’s possible to do the same with Vivocha’s services: create an A/B test to see which service design/engagement rule performs better and evaluate customers’ reactions.

Design: setting up different services with different designs will allow to understand which design is more appealing to customers and/or which one generates more conversions.

Engagement: the A/B test functionality built-in in Vivocha’s services can be used to test which engagement rule (or combination of rules) works better.

A practical example: will a delayed popup generate more interactions or would a sidetab be more effective? Creating two similar services and assigning them to the same A/B test group will generate detailed statistics about which one performs best.

How does it work?

Once two (or more) services are assigned to an A/B testing group, they will be shown randomly to different users (the same user will always see the same service, for consistency reasons). The system is calibrated to show each service the same number of times, to create a reliable data set, useful for decision making.


Follow our step-by-step guide to set up the A/B testing for services and start experimenting or request a demo to learn more.