I am running a series of surveys with single variant A/B tests aimed at gathering information about how different groups of users perceive a series of website designs with different distortions applied. Each participant will be able to rate the various design/distortion combinations using a single metric using a slider rating system (-100 to +100). The aim being to identify which elements/features of a design, when removed or distorted, have a greater or lesser effect on the different groups of users and what is the comparable level of effect on them.
The Null Hypothesis is that there is no perceived difference. The alternative is therefore that there is a perceived difference.
The second stage of my research will involve creating different designs based on this information which I will test using the same apparatus. The aim being to see if I can evoke a specific response among particular user groups to particular designs based on the information gleaned from the first series of experiments. My problem is that I don't know the correct terminology to describe this second stage.
What is the correct name for this type of 'confirmation' experiment?
Essentially I'm running a 'rigged' experiment which I hope will provide a particular response. I have been using variances of "alternative Hypothesis confirmation experiment" but that really does not seem right.
Any help is much appreciated.