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  • March–April 2020
  • Article
  • Harvard Business Review

Avoid the Pitfalls of A/B Testing

By: Iavor I. Bojinov, Guillaume Sait-Jacques and Martin Tingley
  • Format:Print
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Abstract

Online experiments measuring whether “A,” usually the current approach, is inferior to “B,” a proposed improvement, have become integral to the product-development cycle, especially at digital enterprises. But often firms make serious mistakes in conducting these tests: They focus on the average, instead of looking at how a change impacts different customer segments. They forget that customers are connected and that their interactions can affect test outcomes. And they run tests for too short a period, failing to recognize that customers’ reactions can change over time. This article describes how to avoid all those traps by applying techniques that LinkedIn and Netflix have used to produce better insights.

Keywords

A/B Testing; Experiment Design; Social Networks; Product Development; Performance Improvement; Measurement and Metrics; Social Media

Citation

Bojinov, Iavor I., Guillaume Sait-Jacques, and Martin Tingley. "Avoid the Pitfalls of A/B Testing." Harvard Business Review 98, no. 2 (March–April 2020): 48–53.
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About The Author

Iavor I. Bojinov

Technology and Operations Management
→More Publications

More from the Authors

    • 2022
    • Faculty Research

    Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

    By: Daniel Yue, Paul Hamilton and Iavor Bojinov
    • October 2022
    • Faculty Research

    On Ramp to Crypto

    By: Iavor Bojinov, Michael Parzen and Paul Hamilton
    • September 16, 2022
    • Science

    A Causal Test of the Strength of Weak Ties

    By: Karthik Rajkumar, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson and Sinan Aral
More from the Authors
  • Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development By: Daniel Yue, Paul Hamilton and Iavor Bojinov
  • On Ramp to Crypto By: Iavor Bojinov, Michael Parzen and Paul Hamilton
  • A Causal Test of the Strength of Weak Ties By: Karthik Rajkumar, Guillaume Saint-Jacques, Iavor I. Bojinov, Erik Brynjolfsson and Sinan Aral
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