Experiment configuration
Test Optimizely Web Experimentation
Before launching your Web Experimentation experiment, you should test (QA) your variation code, targeting, activation, and metrics. For more information about testing at Optimizely, see the following documentation Test Optimizely Experimentation a basic experiment plan an advanced experiment plan and QA checklist Does your variation look the way it should?
Control the timing of Optimizely Web Experimentation Event dispatch with holdEvents and sendEvents
Optimizely Web Experimentation Optimizely Web Experimentation snippets that use the /events endpoint log batches of events, rather than generate one network request per event. It sends these batches once per second for the first ten seconds after snippet activation and immediately thereafter.
Change the statistical significance setting in Optimizely Experimentation
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack When you run experiments, Optimizely Experimentation's Stats Engine constantly analyzes your results to determine whether your results are statistically significant how unusual your experiment results would be if there was no difference between your variation and baseline, and the difference in lift was due to random chance alone. With the statistical significance setting, you can set a project-wide significance level at which you would like Optimizely Experimentation to declare significant results (winners and losers) on the Results page .
Configure projects for development and production environments
Optimizely Web Experimentation Optimizely Personalization Many organizations have separate development and production environments so they can build and test new features without disturbing production traffic. You can create separate projects for each environment to help with governance.