By conducting experiments on a small group of users (artificial intervention), estimate the causal effect of X intervention on business metric Y, to guide future company strategies.
- In tech industry, X can be new feature in web/app, new product or new promotion strategy etc. Y can be conversion, user engagement etc.
- In clinical industry, X can be a new drug, new dose or new treatment strategy etc. Y can be side effects, event rates, health condition etc.
- For the success of experimental study, in addition to mastering the statistical foundation of experimental research, it is also necessary to have specific domain knowledge in specific industries and projects, such as understanding of variables and characteristics of user behavior. Because these are the key factors in experimental design and post-test analysis.