Most experimentation programs start with prioritizing ideas based on a model like ICE or PIE. If you want to improve your prioritization you move on to PXL Model. It is much more detailed and tailored to A/B-tests ideas and hypotheses.
ICE and PIE models are subjective, based on who’s calling the shots about the changes. But the PXL model is more nuanced, with added questions like—Is the change above the fold? Changes above the fold are noticed by more people, thus increasing the likelihood of the test having an impact. Is the change noticeable in under 5 seconds? If not, it’s likely to have less impact.
How you prioritize your experiments matters. A lot. Prioritization models help you base your experiments and changes on valid foundations like user research, other data, the change’s impact, and a lot more. They are also great when you have a big backlog of ideas, to sort and prioritize them right. Prioritization models will help you get out, start things right, and dig gold from the dirt.
- Prioritize your experiments based on objective standards.
- Help someone who’s only starting experimentation.