Prioritize growth experiments with a structured scorecard.
Use a tool like VWO, which has an in-built hypothesis repository.
Impact: how much the experiment is likely to positively affect the key metric.
Confidence: the probability that the hypothesis is true.
Ease: the amount of effort, in terms of time utilization, required to run an experiment.
Grade each hypothesis on a scale of 1 to 5 for impact, confidence, and ease, with 1 being the lowest and 5 being the highest chance of success.
Consult and discuss with various stakeholders, including experiment creators, product managers, developers, designers, etc. while grading impact, confidence, and ease.
Add up the impact, confidence, and ease scores for each of the listed hypotheses and divide the total by 3 to calculate an average prioritization score.
Add the score in the Total ICE score column.