Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising

Raghav Singal (), Omar Besbes (), Antoine Desir (), Vineet Goyal () and Garud Iyengar ()
Additional contact information
Raghav Singal: Tuck School of Business, Dartmouth College, Hanover, New Hampshire 03755
Omar Besbes: Graduate School of Business, Columbia University, New York, New York 10027
Antoine Desir: Technology and Operations Management, INSEAD, 77305 Fontainebleau, France
Vineet Goyal: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027
Garud Iyengar: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027

Management Science, 2022, vol. 68, issue 10, 7457-7479

Abstract: One of the central challenges in online advertising is attribution, namely, assessing the contribution of individual advertiser actions such as emails, display ads, and search ads to eventual conversion. Several heuristics are used for attribution in practice; however, most do not have any formal justification. The main contribution in this work is to propose an axiomatic framework for attribution in online advertising. We show that the most common heuristics can be cast under the framework and illustrate how these may fail. We propose a novel attribution metric, which we refer to as counterfactual adjusted Shapley value (CASV), which inherits the desirable properties of the traditional Shapley value while overcoming its shortcomings in the online advertising context. We also propose a Markovian model for the user journey through the conversion funnel, in which ad actions may have disparate impacts at different stages. We use the Markovian model to compare our metric with commonly used metrics. Furthermore, under the Markovian model, we establish that the CASV metric coincides with an adjusted “unique-uniform” attribution scheme. This scheme is efficiently implementable and can be interpreted as a correction to the commonly used uniform attribution scheme. We supplement our theoretical developments with numerical experiments using a real-world large-scale data set.

Keywords: digital economy; online advertising; attribution; Markov chain; Shapley value; causality (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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