When is a test hypothesis successful or not?

[arzina221]

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But of course you can also test more drastic adjustments on your website. For example your navigation items. I believe very much in 'reciprocity'. That is why I added the menu item 'video tutorials'. My test hypothesis here is: 'by offering video tutorials about Google Analytics, visitors will be more inclined to book a training with me'. I have not A/B tested this yet, but I will definitely do so.


A hypothesis is already successful if you extract learnings from it. Not every hypothesis will result in an increase in conversion. Example: I set up a test with the call-to-action 'Google Analytics whitepaper' on the homepage. This test did not result in more registrations. I did extract learnings from it. Visitors clicked significantly more on the iceland phone data call-to-actions 'training for beginners' and 'training for advanced users'. That is why I removed the call-to-action 'Google Analytics whitepaper' from the homepage.

In short: don't be put off by a test that doesn't yield a conversion increase. In my experience, only 1 in 6 A/B tests yields a conversion increase.

In summary
A/B testing is more than just trying out button sizes and colors. The pre-analysis and your test hypothesis determine the success of your test. That is why it is so important to first analyze your website based on your conversion factors. You can do this based on your own expertise, but that is of course quite one-sided.

Your visitors determine the success of your website. That is why it is better to include the feedback of the visitor when setting up A/B tests. With this input you can then formulate a substantiated hypothesis. In short: a critical success factor to take your site results to a higher level. Finally, I am very curious about how you approach formulating a hypothesis. I would like to read your vision on this in the comments!

er the customer a positive experience of your product and he will come back more often and buy more. Easier said than done. In this article I will discuss how you can improve the customer experience with the 'peak-end rule' and give you practical tips to apply this rule.