A method determining the best marketing strategy, with the champion being the current approach and the challenger being a new proposed method.

Core Idea:

The Champion/Challenger Test involves comparing the performance of two or more competing decision-making approaches in a live production environment.

  • Champion: This represents the current strategy or decision-making process being used by the organization. It serves as the benchmark for comparison.
  • Challenger: This is an alternative approach or decision logic that you hypothesize might be more effective than the current champion.


  1. Define the Champion and Challenger: Clearly identify the existing strategy (champion) and the alternative approach (challenger) you want to test.
  2. Random Sampling: Select a representative sample of your target population. This could be a subset of your customers, website visitors, or loan applicants depending on the context.
  3. Apply Strategies: Randomly assign the champion strategy to one portion of the sample population and the challenger strategy to another portion. This ensures a fair and unbiased comparison.
  4. Monitor & Analyze Results: Track and measure relevant performance metrics (e.g., sales conversion rate, customer satisfaction score, loan approval rate) for both groups over a predetermined period.
  5. Make Decisions: Based on the collected data and statistical analysis, determine if the challenger strategy outperforms the champion.

Benefits of Champion/Challenger Testing:

  • Data-Driven Decisions: By testing different approaches in a controlled environment, businesses can make informed decisions based on concrete data rather than intuition or guesswork.
  • Improved Performance: The challenger strategy might identify areas for improvement in the existing decision-making process, leading to better outcomes and potentially increased revenue, customer satisfaction, or other key metrics.
  • Continuous Improvement: The Champion/Challenger Test fosters a culture of experimentation and continuous improvement, allowing businesses to refine their strategies over time based on real-world results.


  • Sample Size: The sample size for each group needs to be statistically significant to ensure reliable results.
  • Testing Duration: The testing period should be long enough to capture meaningful data and account for potential fluctuations.
  • Metrics Selection: Choose the appropriate performance metrics that accurately reflect the goals of the test.
  • Fair Comparison: Ensure a fair comparison by controlling for external factors that might influence the results.