Stage 3 – Organize your experiments
Common metrics by revenue model
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) Setting the right primary, secondary, and monitoring goals helps you design a successful experiment that aligns with business goals. Mature testing programs often diversify their secondary and monitoring goals to gather different kinds of data at different funnel stages.
Create a basic prioritization framework
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) Use a prioritization framework to evaluate your ideas and decide which experiments and campaigns to run first. A basic prioritization framework uses consistent criteria to order the experiments and campaigns to run from first to last.
Create an experimentation roadmap
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) Create a testing roadmap to determine which experiments and campaigns to run first and what impact to expect. A full testing roadmap moves past a basic prioritization framework by including an implementation schedule and a breakdown of the experiment workflow.
Use minimum detectable effect when you design an experiment
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) Once you decide on a hypothesis, you can design an experiment. Experiment design is a key part of the cost calculation of experimentation.
Use minimum detectable effect to prioritize experiments
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) Many optimization programs prioritize their roadmaps by estimating the effort versus the impact of an experiment. Use the minimum detectable effect (MDE) to gauge an experiment's potential effort and impact.
Create a basic experiment plan
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) After prioritizing a list of optimization ideas , your next step is to implement them. A basic experiment plan can help you scope and launch individual experiments.
Create an advanced experiment plan and QA checklist
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) A full experiment plan gathers decisions from stakeholders into a single, collaborative document. It provides a detailed summary of the motivations and mechanics of your experiment or campaign.
Primary metrics, secondary metrics, and monitoring goals
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge Optimizely Feature Experimentation Optimizely Full Stack (Legacy) The right metrics can validate or disprove your hypothesis and help you progress toward your business goals. In experience optimization, metrics have different roles depending on where you set them and what you want to know.