Controlled Experiments

Controlled experiments, often called A/B tests or split tests, are a scientific methodology used to compare two or more versions of a product, feature, or process to determine which performs better based on predefined metrics. They involve randomly assigning users to different groups (e.g., control and treatment) and measuring outcomes to establish causal relationships between changes and effects. This approach is widely applied in software development, marketing, and user experience design to make data-driven decisions.

Also known as: A/B Testing, Split Testing, Randomized Controlled Trials, RCT, Bucket Testing

Why learn Controlled Experiments?

Developers should learn controlled experiments to optimize product features, improve user engagement, and reduce risks by testing changes on a small scale before full deployment. They are essential in agile and data-driven environments, such as web applications, mobile apps, and SaaS platforms, where iterative improvements rely on empirical evidence rather than assumptions. For example, using A/B testing to compare different UI designs or algorithm tweaks helps ensure that updates lead to desired outcomes like increased conversions or reduced load times.

Learning Resources

• docs: A/B Testing Guide by Optimizely
• course: Controlled Experiments on Coursera
• tutorial: A/B Testing: The Complete Guide by VWO
• book: Trustworthy Online Controlled Experiments by Kohavi et al.
• video: Introduction to A/B Testing on YouTube