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Monetizing Online Marketplaces

Author

Listed:
  • Hana Choi

    (Simon School of Business, University of Rochester, Rochester, New York 14627)

  • Carl F. Mela

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

Abstract

This paper considers the monetization of online marketplaces. These platforms trade off fees from advertising with commissions from product sales. Although featuring advertised products can make search less efficient (lowering transaction commissions), it incentivizes sellers to compete for better placements via advertising (increasing advertising fees). We consider this trade-off by modeling both sides of the platform. On the demand side, we develop a joint model of browsing (impressions), clicking, and purchase. On the supply side, we consider sellers’ valuations and advertising competition under various fee structures (cost-per-mille, cost-per-click (CPC), and cost-per-action) and ranking algorithms. Using buyer, seller, and platform data from an online marketplace where advertising dollars affect the order of seller items listed, we explore various product-ranking and ad-pricing mechanisms. We find that sorting items below the fifth position by expected sales revenue while conducting a CPC auction in the top 5 positions yields the greatest improvement in profits (181%) because this approach balances the highest valuations from advertising in the top positions with the transaction revenues in the lower positions.

Suggested Citation

  • Hana Choi & Carl F. Mela, 2019. "Monetizing Online Marketplaces," Marketing Science, INFORMS, vol. 38(6), pages 948-972, November.
  • Handle: RePEc:inm:ormksc:v:38:y:2019:i:6:p:948-972
    DOI: 10.1287/mksc.2019.1197
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    References listed on IDEAS

    as
    1. Yuxin Chen & Song Yao, 2017. "Sequential Search with Refinement: Model and Application with Click-Stream Data," Management Science, INFORMS, vol. 63(12), pages 4345-4365, December.
    2. Susan Athey & Glenn Ellison, 2011. "Position Auctions with Consumer Search," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(3), pages 1213-1270.
    3. Raluca M. Ursu, 2018. "The Power of Rankings: Quantifying the Effect of Rankings on Online Consumer Search and Purchase Decisions," Marketing Science, INFORMS, vol. 37(4), pages 530-552, August.
    4. Yongmin Chen & Chuan He, 2011. "Paid Placement: Advertising and Search on the Internet," Economic Journal, Royal Economic Society, vol. 121(556), pages 309-328, November.
    5. Mark Armstrong & John Vickers & Jidong Zhou, 2009. "Prominence and consumer search," RAND Journal of Economics, RAND Corporation, vol. 40(2), pages 209-233, June.
    6. Jun B. Kim & Paulo Albuquerque & Bart J. Bronnenberg, 2010. "Online Demand Under Limited Consumer Search," Marketing Science, INFORMS, vol. 29(6), pages 1001-1023, 11-12.
    7. Babur De los Santos & Sergei Koulayev, 2017. "Optimizing Click-Through in Online Rankings with Endogenous Search Refinement," Marketing Science, INFORMS, vol. 36(4), pages 542-564, July.
    8. Thomas Blake & Chris Nosko & Steven Tadelis, 2015. "Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment," Econometrica, Econometric Society, vol. 83, pages 155-174, January.
    9. Zhou, Jidong, 2011. "Ordered search in differentiated markets," International Journal of Industrial Organization, Elsevier, vol. 29(2), pages 253-262, March.
    10. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2015. "Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design," Management Science, INFORMS, vol. 61(4), pages 864-884, April.
    11. Andrey Simonov & Chris Nosko & Justin M. Rao, 2018. "Competition and Crowd-Out for Brand Keywords in Sponsored Search," Marketing Science, INFORMS, vol. 37(2), pages 200-215, March.
    12. Tat Y. Chan & Young-Hoon Park, 2015. "Consumer Search Activities and the Value of Ad Positions in Sponsored Search Advertising," Marketing Science, INFORMS, vol. 34(4), pages 606-623, July.
    13. Hal R. Varian, 2010. "Computer Mediated Transactions," American Economic Review, American Economic Association, vol. 100(2), pages 1-10, May.
    14. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    15. Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
    16. Elisabeth Honka, 2014. "Quantifying search and switching costs in the US auto insurance industry," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 847-884, December.
    17. Krishnamurthy Iyer & Ramesh Johari & Mukund Sundararajan, 2014. "Mean Field Equilibria of Dynamic Auctions with Learning," Management Science, INFORMS, vol. 60(12), pages 2949-2970, December.
    18. Wilson, Chris M., 2010. "Ordered search and equilibrium obfuscation," International Journal of Industrial Organization, Elsevier, vol. 28(5), pages 496-506, September.
    19. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    20. Navid Mojir & K. Sudhir, 2014. "Price Search Across Time and Across Stores," Cowles Foundation Discussion Papers 1942R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2019.
    21. Elisabeth Honka & Ali Hortaçsu & Maria Ana Vitorino, 2017. "Advertising, consumer awareness, and choice: evidence from the U.S. banking industry," RAND Journal of Economics, RAND Corporation, vol. 48(3), pages 611-646, August.
    22. Song Yao & Carl F. Mela, 2011. "A Dynamic Model of Sponsored Search Advertising," Marketing Science, INFORMS, vol. 30(3), pages 447-468, 05-06.
    23. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-654, May.
    24. Michael Dinerstein & Liran Einav & Jonathan Levin & Neel Sundaresan, 2018. "Consumer Price Search and Platform Design in Internet Commerce," American Economic Review, American Economic Association, vol. 108(7), pages 1820-1859, July.
    25. Sergei Koulayev, 2014. "Search for differentiated products: identification and estimation," RAND Journal of Economics, RAND Corporation, vol. 45(3), pages 553-575, September.
    26. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2003. "Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation," Marketing Science, INFORMS, vol. 22(1), pages 58-84, June.
    27. Mark Armstrong & Jidong Zhou, 2011. "Paying for Prominence," Economic Journal, Royal Economic Society, vol. 121(556), pages 368-395, November.
    28. John J. Horton, 2017. "The Effects of Algorithmic Labor Market Recommendations: Evidence from a Field Experiment," Journal of Labor Economics, University of Chicago Press, vol. 35(2), pages 345-385.
    29. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    30. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    31. Bart J. Bronnenberg & Jun B. Kim & Carl F. Mela, 2016. "Zooming In on Choice: How Do Consumers Search for Cameras Online?," Marketing Science, INFORMS, vol. 35(5), pages 693-712, September.
    32. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    33. Ettore Damiano & Hao Li, 2007. "Price discrimination and efficient matching," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 30(2), pages 243-263, February.
    34. Przemyslaw Jeziorski & Ilya Segal, 2015. "What Makes Them Click: Empirical Analysis of Consumer Demand for Search Advertising," American Economic Journal: Microeconomics, American Economic Association, vol. 7(3), pages 24-53, August.
    35. Per Krusell & Anthony A. Smith & Jr., 1998. "Income and Wealth Heterogeneity in the Macroeconomy," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 867-896, October.
    36. Han Hong & Matthew Shum, 2006. "Using price distributions to estimate search costs," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 257-275, June.
    37. Andrei Hagiu & Bruno Jullien, 2011. "Why do intermediaries divert search?," RAND Journal of Economics, RAND Corporation, vol. 42(2), pages 337-362, June.
    38. Donghoon Lee & Kenneth I. Wolpin, 2006. "Intersectoral Labor Mobility and the Growth of the Service Sector," Econometrica, Econometric Society, vol. 74(1), pages 1-46, January.
    39. George J. Stigler, 1961. "The Economics of Information," Journal of Political Economy, University of Chicago Press, vol. 69(3), pages 213-213.
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