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AB Testing

A/B testing is a method for comparing two or more variants—such as website layouts or marketing messages—to determine which one performs better based on real user data. It relies on statistical analysis to provide objective evidence for making business decisions.

Stats & ScoringAnalytics
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Workflow
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AB Testing with KNIME

How This Workflow Works

This workflow brings together customer interaction data, transforms it for analysis, applies statistical tests to compare variant performance, and presents the results visually. The process helps you identify which option leads to better outcomes, supporting data-driven decision-making.

Key Features:

  • Quantitatively compare the performance of different variants
  • Apply robust statistical tests to detect significant differences
  • Visualize results for clearer interpretation and communication
  • Support evidence-based optimization of marketing or product strategies

Step-by-step:

1. Transform and Encode Variant Data:

The workflow converts categorical information about each variant (such as which landing page a user saw) into a numerical format. This step ensures the data is ready for statistical analysis and comparison.

2. Apply Statistical Testing:

Statistical tests, including ANOVA and post-hoc analyses, are used to determine if there are significant differences in performance between the variants. This step provides the core evidence for deciding which variant is more effective.

3. Visualize and Share Insights:

The results are presented using bar plots and scatterplots, making it easier to interpret differences between variants. These visualizations help stakeholders quickly grasp the findings and support informed decision-making.

How to Get Started