Experimental Study in Tech: A/B Testing Structure

<p>By conducting experiments on a small group of users (artificial intervention), estimate the&nbsp;<strong>causal effect of X</strong>&nbsp;intervention on business metric Y, to guide future company strategies.</p> <ul> <li>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.</li> <li>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.</li> <li>For the success of experimental study, in addition to mastering the statistical foundation of experimental research, it is also necessary to have&nbsp;<strong>specific domain knowledge</strong>&nbsp;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.</li> </ul> <p><a href="https://medium.com/@LobsterTing/experimental-study-in-tech-a-b-testing-structure-fbc741cd2cdf"><strong>Visit Now</strong></a></p>