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Assessing the statistical significance of repeated A/B tests with meta-analysis

Author

Listed:
  • Harman, David

    (Assistant Professor, University of St. Thomas, USA)

Abstract

This paper presents the steps to conduct a meta-analysis of a set of repeated A/B tests. Repeated A/B testing is common in professional marketing practice. Each test, however, can only be individually evaluated for statistical significance when using basic statistical analysis. A meta-analysis of the same A/B tests provides three useful analytics outputs: an overall treatment effect across all tests, a confidence interval for that effect to assess statistical significance, and a measure of heterogeneity between tests to assess the context variation between campaigns. Meta-analysis is a useful addition to marketing analytics practice.

Suggested Citation

  • Harman, David, 2022. "Assessing the statistical significance of repeated A/B tests with meta-analysis," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 7(4), pages 374-385, March.
    • Handle: RePEc:aza:ama000:y:2022:v:7:i:4:p:374-385
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    More about this item

    Keywords

    meta-analysis; A/B testing; significance testing; marketing campaign analytics;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

    Statistics

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