Prioritize Your Experiments
When you've accumulated a number of experiment ideas, it can be challenging to decide which to start with. Your first inclination might be to start with something small and easy to implement, but that may not always be the best route; there may be something on your list that would be better to try first. Knowing how to prioritize your experiments will help you create an efficient backlog or roadmap that will give you the best experience with optimization.
In this course, you'll answer the following three questions:
- What are the deciding factors that influence which hypotheses should be tested first?
- How can you reduce the guesswork for prioritizing experiments?
- What resources can help or hinder your capacity to experiment on a particular hypothesis?
When all of the course elements are marked Completed, return to the learning path by clicking the path name in the breadcrumb at the top of the page.
This course will teach you the various ways an experimentation program structure can be set up, as well as which individuals should be involved and what various teams might look like.
In this course, you'll learn how to use Program Management to more effectively analyze the results of your experiments and iterate out into new experiment ideas.
In this course, you will learn how to set up and manage your team in Program Management.
In this course, you'll learn how to use Optimizely's Program Management to help you with ideation and planning for your experiments.