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Interference Produces False-Positive Pricing Experiments

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  • Lars Roemheld
  • Justin Rao
Abstract
It is standard practice in online retail to run pricing experiments by randomizing at the article-level, i.e. by changing prices of different products to identify treatment effects. Due to customers' cross-price substitution behavior, such experiments suffer from interference bias: the observed difference between treatment groups in the experiment is typically significantly larger than the global effect that could be expected after a roll-out decision of the tested pricing policy. We show in simulations that such bias can be as large as 100%, and report experimental data implying bias of similar magnitude. Finally, we discuss approaches for de-biased pricing experiments, suggesting observational methods as a potentially attractive alternative to clustering.

Suggested Citation

  • Lars Roemheld & Justin Rao, 2024. "Interference Produces False-Positive Pricing Experiments," Papers 2402.14538, arXiv.org.
    • Handle: RePEc:arx:papers:2402.14538
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    References listed on IDEAS

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    1. Joe Cooprider & Shima Nassiri, 2023. "Science of price experimentation at Amazon," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 58(1), pages 34-41, January.
    2. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
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