A/B testing | Notion

A/B testing is a user experience research methodology. A/B testing is a way to compare multiple versions of a single variable, for example by testing a subject's response to variant A against variant B, and determining which of the variants is more effective (from Wikipedia).
A/B testing is especially relevant for optimization of an existing solution.

Collect data (in order to understand what are possible places for conversion optimization)
Set goals (define metrics in order to be able to determine which variation is more successful)
Generate test hypothesis (brainstorm and think of ideas that might improve current metrics, then prioritize them based on impact and cost of implementation and select the best one)
Create different variations (use an A/B testing tool to create the variation in your website/app, or orchestrate the variant in case some development is needed)
Run experiment (start the A/B testing experiment in the A/B testing tool to test the variant against the control)
Wait for results (wait for enough traffic in order to verify the results are conclusive)
Analyze results (check the results in the A/B testing tool to see if there is a significant difference between the variant and the control with regards to the defined metrics in order to choose which one is better)