A/B Testing
The idea of A/B testing is to present different content to different user groups, gather their reactions and use the results to build strategies in the future.
To conduct A/B testing you need two versions of an design or element (A and B) and a metric that defines success. To determine which version is better, you subject both versions to experimentation simultaneously. In the end, you measure which version was more successful and select that version for real-world use or continued testing.
Research Details (Optional - only for a research method)
| Research Type | Sample Size | Suggested Time |
|---|---|---|
| Quantitative, Behavioral, Summative | Large (as many as possible) | 1 to 2 hours set up |
When to Use
- When making incremental refinements and changes to a design.
- When you have a hypothesis that a design change will change user behavior and want to test it.
Steps
- It’s best to start the A/B testing process by forming a hypothesis. What impact do you think your proposed design changes will have on user behavior.
- Then determine a way to quantify and measure that behavioral change. A commonly used metric is conversion rate. But the metric will depend on your hypothesis, designs, and user goals. Other potential metrics include
References
- The Ultimate Guide to A/B Testing
- A/B Testing and UX Research
- User Experience and Funnel Optimization
- How Netflix does A/B Testing
Created by: Joe Steinkamp | Last updated by: Joe Steinkamp