Iterative A/B Testing – A Must If You Lack a Crystal Ball

Iterative A/B Testing – A Must If You Lack a Crystal Ball

You have a hypothesis, and run a test. Result – no difference (or even drop in results). What should you do now? Test a different hypothesis?

Not so fast.

A fairly common scenario

Let’s imagine that you conducted a qualitative survey, and a large number of respondents voiced concerns about your credit card payment page – they didn’t feel it was secure enough (even though it actually was secure). It caused anxiety in people, made them …read more

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