More feature flags related terms

Multivariate testing


Multivariate testing is a method used in software and web development to test multiple variables simultaneously to determine the best combination of elements. It's an advanced form of A/B testing that provides deeper insights into how different elements interact and affect user behavior.



  1. Identify Variables: Select multiple elements (like layout, images, text) for testing.
  2. Create Variations: Develop different combinations of these elements.
  3. Run Tests: Expose these variations to users, tracking their interaction and responses.
  4. Analyze Results: Use statistical analysis to determine which combination performs the best.

Key Features

Best Practices


Multivariate testing is a powerful tool in the optimization arsenal, offering detailed insights into how various elements of a user interface interact with each other. By enabling data-driven decisions, it plays a crucial role in enhancing the user experience and improving the effectiveness of software and websites. Learn more about multivariate testing and A/B tests.

A/A testing

A/A testing validates A/B testing methods by comparing identical content versions to uncover anomalies, establish a benchmark for future tests, and enhance confidence in testing processes and tools.

Learn about A/A testing


CUPED is a technique that uses pre-experiment data to reduce variance in A/B testing, improving result sensitivity and reliability by focusing on the true effects of the experimental changes.

Learn about CUPED

User segmentation

Dividing users into groups based on behavior or attributes for targeted feature releases.

Learn about User segmentation

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