Big Data and Marketing Analytics in Gaming: Combining Empirical Models and Field Experimentation

47 Pages Posted: 27 Feb 2014 Last revised: 28 Jun 2017

See all articles by Harikesh Nair

Harikesh Nair

Stanford University - Graduate School of Business

Sanjog Misra

University of Chicago - Booth School of Business

William Hornbuckle

MGM Resorts International

Ranjan Mishra

ESS Analysis

Anand Acharya

ESS Analysis

Date Written: February 22, 2017

Abstract

Efforts on developing, implementing and evaluating a marketing analytics framework at a real-world company are described. The framework uses individual-level transaction data to fit empirical models of consumer response to marketing efforts, and uses these estimates to optimize segmentation and targeting. The models feature themes emphasized in the academic marketing science literature, including incorporation of consumer heterogeneity and state-dependence into choice, and controls for the endogeneity of the firm's historical targeting rule in estimation. To control for the endogeneity, we present an approach that involves conducting estimation separately across fixed partitions of the score variable that targeting is based on, which may be useful in other behavioral targeting settings. The models are customized to facilitate casino operations and are implemented at the MGM Resorts International's group of companies. The framework is evaluated using a randomized trial implemented at MGM involving about 1.5M consumers. Using the new model produces about $1M to $5M incremental profits per campaign, translating to about 20cent incremental profit per dollar spent relative to the status quo. At current levels of marketing spending, this implies between $10M and $15M in incremental annual profit for the firm. The case-study underscores the value of using empirically-relevant marketing analytics solutions for improving outcomes for firms in real-world settings.

Keywords: marketing, promotions, casinos, behavioral targeting, nonrandom targeting, endogeneity, field experiments

Suggested Citation

Nair, Harikesh and Misra, Sanjog and Hornbuckle, William and Mishra, Ranjan and Acharya, Anand, Big Data and Marketing Analytics in Gaming: Combining Empirical Models and Field Experimentation (February 22, 2017). Stanford University Graduate School of Business Research Paper No. 14-07; Simon Business School Working Paper No. FR 14-04. Available at SSRN: https://ssrn.com/abstract=2399676 or http://dx.doi.org/10.2139/ssrn.2399676

Harikesh Nair (Contact Author)

Stanford University - Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States
650-736-4256 (Phone)

HOME PAGE: http://faculty-gsb.stanford.edu/nair/index.html

Sanjog Misra

University of Chicago - Booth School of Business ( email )

5807 South Woodlawn Avenue
Chicago, IL 60637
United States

William Hornbuckle

MGM Resorts International ( email )

3799 Las Vegas Boulevard South
Las Vegas, NV 89109
United States

Ranjan Mishra

ESS Analysis

Cambridge, MA
United States

Anand Acharya

ESS Analysis

Cambridge, MA
United States

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