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Protecting customer privacy when marketing with second-party data


  • Schneider, Matthew J.
  • Jagpal, Sharan
  • Gupta, Sachin
  • Li, Shaobo
  • Yu, Yan


Data sharing is a strategically important marketing initiative in many industries. Increasingly, companies seek to enhance the value of their customer data by supplementing this information with customer-level information from another company. However, this arrangement requires one company to reveal its customer-level data to another and face privacy risks which may result in substantial losses in brand value, customer trust, and competitive advantage, or legal penalties from not conforming to regulations. To overcome this problem, we propose a decision-theoretic approach for use by companies to protect their customer segmentation data prior to entering into collaborative arrangements. Our approach extends the literature because it allows the data provider to protect all customer segmentation data at the individual customer level instead of only at the aggregate level. We show that the optimal data protection strategy depends on a risk-return tradeoff based on the probabilities of misclassification of customers into segments, the opportunity costs of erroneously assigning segment membership, and the anticipated cost of a data breach.

Suggested Citation

  • Schneider, Matthew J. & Jagpal, Sharan & Gupta, Sachin & Li, Shaobo & Yu, Yan, 2017. "Protecting customer privacy when marketing with second-party data," International Journal of Research in Marketing, Elsevier, vol. 34(3), pages 593-603.
  • Handle: RePEc:eee:ijrema:v:34:y:2017:i:3:p:593-603
    DOI: 10.1016/j.ijresmar.2017.02.003

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    References listed on IDEAS

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    4. Thomas J. Steenburgh & Andrew Ainslie & Peder Hans Engebretson, 2003. "Massively Categorical Variables: Revealing the Information in Zip Codes," Marketing Science, INFORMS, vol. 22(1), pages 40-57, August.
    5. Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
    6. Drechsler, Jörg & Reiter, Jerome P., 2010. "Sampling With Synthesis: A New Approach for Releasing Public Use Census Microdata," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1347-1357.
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    Blog mentions

    As found by, the blog aggregator for Economics research:
    1. Protecting Customers’ Privacy Requires More than Anonymizing Their Data
      by Sachin Gupta in HBR Blog Network on 2018-06-01 14:00:49


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