A/B testing
š A/B Testing
A/B testing, also called split testing, involves comparing two different versions of a product or feature to see which one yields better results. By randomly assigning users to different experiences and measuring specific metrics (e.g., click-through rates, conversions), teams gain direct insight into what resonates most with their audience.
š Notable Insights:
š Notable Insights:
- āļø Experimentation: Rapidly test hypotheses about user behavior using controlled, data-driven experiments.
- āļø Reduced Bias: Randomized sampling helps eliminate subjective guesswork and personal preferences.
- āļø Real-Time Feedback: Gain immediate metrics on key performance indicators (KPIs) to assess impact.
- āļø Broader Application: Use in UX, marketing, product features, and even pricing strategy decisions.
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