How does A/B testing contribute to data-driven decision making?
- It analyzes historical data to make predictions about future trends.
- It focuses on creating visual representations of data for better understanding.
- It helps in comparing two versions of a webpage or app to determine which performs better.
- It involves analyzing data in real-time.
A/B testing is a method for comparing two versions of a webpage or app to determine which performs better. It contributes to data-driven decision making by providing empirical evidence on the effectiveness of changes, enabling informed decisions based on actual user responses.
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