User-Based Cannibalization Mitigation in an Online Marketplace
Online marketplaces are not only digital places where consumers buy and sell merchandise, and they are also destinations for brands to connect with real consumers at the moment when customers are in the shopping mindset. For many marketplaces, brands have been important partners through advertising. There can be, however, a risk of advertising impacting a consumer’s shopping journey if it hurts the use experience or takes the user away from the site. Both could lead to the loss of transaction revenue for the marketplace. In this paper, we present user-based methods for cannibalization control by selectively turning off ads to users who are likely to be cannibalized by ads subject to business objectives. We present ways of measuring cannibalization of advertising in the context of an online marketplace and propose novel ways of measuring cannibalization through purchase propensity and uplift modeling. A/B testing has shown that our methods can significantly improve user purchase and engagement metrics while operating within business objectives. To our knowledge, this is the first paper that addresses cannibalization mitigation at the user-level in the context of advertising.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1340603Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 363
 G. Brajnik and S. Gabrielli. A Review of Online Advertising Effects on the User Experience. Intl. Journal Of Human–Computer Interaction, 26(10), 971–997, 2010
 P. Manchanda, J. Dubé, K. Goh and P. Chintagunta. The Effect of Banner Advertising on Internet Purchasing. Journal of Marketing Research, February 2006.
 T. Powers, D. Advincula, M. Austin, S. Graiko and J.Snyder. Digital and Social Media in the Purchase Decision Process. Journal of Advertising Research, December 2012.
 R. Gopal, X. Li, and R. Sankaranarayanan, Online keyword based advertising: Impact of ad impressions on own-channel and cross-channel click-through rates. Decision Support Systems December 2011 pages 1-8.
 L. Teng, M. Laroche, and H Zhu. The effects of multiple‐ads and multiple‐brands on consumer attitude and purchase behavior. Journal of Consumer Marketing 2007.
 P. Hoban and R. Bucklin. Effects of Internet Display Advertising in the Purchase Funnel: Model-Based Insights from a Randomized Field Experiment. Journal of Marketing Research, June 2015, Vol. 52, No. 3, pages 375-393.
 J. Zhang and E. Mao. From Online Motivations to Ad Clicks and to Behavioral Intentions: An Empirical Study of Consumer Response to Social Media Advertising. Psychology & Marketing, Feburary 2016.
 W. Havlena, R. Cardarelli and M. Montigny. Quantifying the Isolated and Synergistic Effects of Exposure Frequency for TV, Print, and Internet Advertising. Journal of Advertising Research, September 2007.
 E. Rahbar and N. Wahid. Investigation of green marketing tools' effect on consumers' purchase behavior. Business Strategy Series, 2007.
 A. Goldfarb and C. Tucker. Online Display Advertising: Targeting and Obtrusiveness. Marketing Science, April 2010.
 C. Mason. An approach for identifying cannibalization within product line extensions and multi-brand strategies. Journal of Business Research, Volume 31, Issues 2–3 react-text: 63 , /react-text react-text: 64 October–November 1994 /react-text react-text: 65 , Pages 163-170.
 V. Guide, Jr and J Li. The Potential for Cannibalization of New Products Sales by Remanufactured Products. Decision Sciences, August 2010.
 G Taylor. Search Quality and Revenue Cannibalization by Competing Search Engines. Journal of Economics & Management Strategy, July 2013.
 W. Copulsky. Cannibalism in the Marketplace. Journal of Marketing, Vol. 40, No. 4, October 1976, pages 103-105.
 S Balseiro, J. Feldman. V. Mirrokni and S. Muthukrishnan. Yield Optimization of Display Advertising with Ad Exchange. Management Science, October 2014 pages 2886-2907.
 R. Yeung, W. Yee. Logistic Regression: An advancement of predicting consumer purchase propensity. The Marketing Review, Volume 11, Number 2011, pages 71-81.
 E. Kim, W. Kim and Y. Lee. Combination of multiple classifiers for the customer's purchase behavior prediction. Decision Support Systems, Volume 34, Issue 2, January 2003, Pages 167–175.
 G. Andreeva, J. Ansell and J. Crook. Modeling the purchase propensity: analysis of a revolving store card. Journal of the Operational Research Society, September 2005, Volume 56, Issue 9, pp 1041–1050.
 B. Milles and J. Schleich. What's driving energy efficient appliance label awareness and purchase propensity? Energy Policy, Volume 38, Issue 2, February 2010, Pages 814–825.
 M. Walley and D. Fortin. Behavioral outcomes from online auctions: reserve price, reserve disclosure, and initial bidding influences in the decision process. Journal of Business Research, Volume 58, Issue 10, October 2005, Pages 1409-1418.
 D. Vincent. Bidding Off the Wall: Why Reserve Prices May Be Kept Secret. Journal of Economic Theory, Volume 65, Issue 2, April 1995, Pages 575-584.
 O. Hinz and M. Spann. The Impact of Information Diffusion on Bidding Behavior in Secret Reserve Price Auctions. Information Systems Research, September 2008.
 P. Rzepakowski and S. Jaroszewicz. Uplift Modeling in Direct Marketing. Journal of Telecommunications and Information Technology, 2012.
 P. Rzepakowski and S. Jaroszewicz. Decision Trees for Uplift Modeling with Single and Multiple Treatments. Knowledge and Information Systems, August 2012, Volume 32, Issue 2, pp303-327.
 P. Farris, Bendle, N., Pfeifer, P., and E. Reibstein. Marketing Metrics: The Definitive Guid to Measuring Marketing Performance. Pearson FT Press. 2010.
 W. Lomax, R. East and M. Clemente. The measurement of cannibalization. Marketing Intelligence and Planning, December 1996, pages 26-39.