What is A/B Testing?
A/B testing, also known as slipt testing, is a user experience methodology that compares two versions of a single variable by testing the performance of variant A against variant B. This test helps determine which of the two variants is more effective.
A/B testing allows for an organization to be more strategic and data-driven about its digital communication and business decisions. Ultimately, this helps the company embrace a digital transformation effort.
Why is A/B Testing Important?
Data-driven guidance removes the guesswork from decision-making and lets the data decide the best path forward. When we review results based on A vs B or “split” testing, it helps facilitate a conversation with a focus on the data, rather than opinion, or emotion, and can improve operational efficiency with decisions supported by customer data.
Testing, rather than guessing, yields time back to an organization for marketing and operational teams to work on other priorities.
How Can Razorvision Help?
Razorvision supports A/B testing and data-driven decisions. We recently had a client who added steps to a customer data intake/application process. The initial hypothesis was that increasing points of contact with the customer would not help completion rates because it is taking longer to finish the overall data intake process.
We introduced a multi-step application running as a “Challenger” and compared the completion rates against the “Champion” or single application process. In three separate tests, the Challenger maintained a 9+% better performance than the original application completion rate. The client can now run additional A/B tests as they refine the user journey and let customers tell them what they prefer along the way.