Bargaining over Data and Analytics: Sellers, Buyers and Consultants

The rapid growth of digital platforms and online commerce has generated vast amounts of proprietary data that firms increasingly seek to monetize. Sellers face two fundamental choices: whether to provide access exclusively to a single buyer or nonexclusively to multiple buyers, and whether to sell stand-alone data or offer a data product that integrates data with analytics services. Buyers, in turn, must decide how to structure negotiations—separately with the seller and the consultant, or with both simultaneously. We develop a Nash bargaining framework to analyze these strategic decisions. Our results show that sellers may profit from offering stand-alone data even when they possess analytics capabilities, and offering integrated data products can be optimal even if the seller’s analytics services are inferior to those of external consultants. We further demonstrate that simultaneous three-way negotiations allow buyers to capture more of the consultant’s contribution, but at the risk of ceding part of the intrinsic value of the data to the consultant. We identify conditions under which sellers prefer exclusive contracts over nonexclusive arrangements, even when exclusivity reduces total value. Our analysis highlights the role of bargaining power in shaping these outcomes. Strong sellers are more likely to benefit from stand-alone data sales, whereas weaker sellers gain from offering data products or pursuing nonexclusive contracts. By contrasting our bargaining model with auctions, mechanism design, and query-based pricing, we show how cooperative bargaining yields distinct insights for data monetization strategies across industries such as healthcare, retail, financial services, and travel.

History: Ram Gopal, Senior Editor; Heng Xu, Associate Editor.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.0404.