Hypothesis

Definition:

In website optimisation a hypothesis is a change and effect statement that is based upon qualitative (e.g. customer complaints) and/or quantitative data (e.g. web analytics). This should be measurable and ideally provide a rationale for why a change to the customer experience will influence the success metrics. Creating an hypothesis is a critical step in the test and learn process outlined below.

Image of test and learn process for conversion rate optimization

Without a strong hypothesis for each A/B test the optimisation process is likely to become random and not reach its full potential to improve the bottom line. Without a hypothesis there is also little, if any, learning from tests as there needs to be a logical reason to believe a new experience is better than the default.  Failure is how we learn, but it is also important to try and understand why something didn’t work.

Resources:

Conversion marketing – Glossary of Conversion Marketing.

Over 300 tools reviewed – Digital Marketing Toolbox.

A/B testing software – Which A/B testing tools should you choose?

Optimisation process – 8 steps guaranteed to boost your conversion rate.

Prioritise tests – How should you prioritise your A/B test ideas?