As an executive sponsor or leader on a team, you want to see the business impact and ROI Optimizely experimentation is having on your business, though you don’t expect to be hands-on with the tool.
As the experimentation lead you need an understanding of working with strategy, experimentation implementation and results to run an optimization program that meets business needs.
For software developers and engineers working in Full Stack, this path focuses on setting up and running experiments, feature rollouts, and QA testing.
UX designers or front end developers focused on developing customer experiences using our WYSIWYG editor in Optimizely X Web. This path helps you learn how to develop, run and QA experiments.
Now that you've got the basics down, let's dive a little deeper into the fundamentals learned in Level 1, including more in-depth lessons on experimentation strategy, developing and managing experimentation teams, and more.
Data analysts will learn to review and use results from experiments as part of the decision-making process.
For those who contribute experimentation ideas, such as marketing managers, we help you focus on building a good hypothesis.
Designed for those using Optimizely's free Rollouts to ideate, design and build feature flags.