When thinking about site tests, there are two approaches you could take.

The first is to just chose something to test. This is appealing; it would fun and easy. Whatever caught your eye, you could change and run as an A/B test against the original version. Sometimes you would be lucky. More often, though, you would be wrong. The changes would be coming from you rather than from what the audience wants. A site change’s success is entirely dependent upon the audience’s reaction. If the audience isn’t happy, your site change will not work.

The second approach is to think about the details of the test and form a hypothesis. When you set up a hypothesis you consider your audience’s point of view.

A hypothesis can be thought of as a testable short story that describes user behavior when a change is introduced. For instance, a hypothesis might be, “Changing the hero image copy to focus on the design benefit rather than technical benefits will increase revenue by 10%”. It states what’s changing (the copy) and the predicted audience behavior (10% increase in revenue).

While it doesn’t appear in the hypothesis statement, the most important part of constructing a hypothesis is why you think it will work. If you can’t convincingly answer that, then your hypothesis is very unlikely to be successful.

You can answer why a hypothesis will work because you are knowledgeable about your audience. Testing with a hypothesis is a great way to increase that knowledge. If you test new copy and it works, it enriches your existing ideas about your audience. If it doesn’t work, it adds to your knowledge of your audience. You had an idea as to why it should work but that idea was wrong. So now you need to reconsider what you know about your audience. You can use this information to make your future tests stronger.

Without a hypothesis, a winning or failing test lacks context. It’s hard to interpret because the test wasn’t created with the audience and site in mind. Instead of enriching already known information, the test results are isolated data points.

Hypotheses are also useful because you can use them to prioritize site changes. If you have many changes you want to make to a site, look at what hypotheses are most worthwhile and run those tests first. You get the most impact for your testing efforts.

Finally creating hypotheses is a good way to get support from the people you work with. A series of hypotheses that ties into your site strategy will give people confidence that you know what you’re testing, why you’re testing it and what outcome you anticipate.