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First Degree Price Discrimination Using Big Data

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  • Benjamin Reed Shiller

    ()
    (Economics Department, Brandeis University)

Abstract

Second and 3rd degree price discrimination (PD) receive far more attention than 1st degree PD, i.e. person-specific pricing, because the latter requires previously unobtainable information on individuals’ willingness to pay. I show modern web behavior data reasonably predict Netflix subscription, far outperforming data available in the past. I then present a model to estimate demand and simulate outcomes had 1st degree PD been implemented. The model is structural, derived from canonical theory models, but resembles an ordered Probit, allowing methods for handling massive datasets. Simulations show using demographics alone to tailor prices raises profits by 0.14%. Including web browsing data increases profits by much more, 1.4%, increasingly the appeal of tailored pricing, and resulting in some consumers paying twice as much as others do for the exact same product.

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File URL: http://www.brandeis.edu/departments/economics/RePEc/brd/doc/Brandeis_WP58R2.pdf
File Function: Revised version, 2014
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File URL: http://www.brandeis.edu/departments/economics/RePEc/brd/doc/Brandeis_WP58R.pdf
File Function: Revised version, 2013
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File URL: http://www.brandeis.edu/departments/economics/RePEc/brd/doc/Brandeis_WP58.pdf
File Function: First version, 2013
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Bibliographic Info

Paper provided by Brandeis University, Department of Economics and International Businesss School in its series Working Papers with number 58.

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Length: 31 pages
Date of creation: Aug 2013
Date of revision: Sep 2013
Handle: RePEc:brd:wpaper:58

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Postal: MS032, P.O. Box 9110, Waltham, MA 02454-9110
Web page: http://www.brandeis.edu/departments/economics/
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  1. Alan L. Montgomery & Shibo Li & Kannan Srinivasan & John C. Liechty, 2004. "Modeling Online Browsing and Path Analysis Using Clickstream Data," Marketing Science, INFORMS, vol. 23(4), pages 579-595, November.
  2. Mussa, Michael & Rosen, Sherwin, 1978. "Monopoly and product quality," Journal of Economic Theory, Elsevier, vol. 18(2), pages 301-317, August.
  3. Ben Shiller & Joel Waldfogel, 2011. "Music for a Song: An Empirical Look at Uniform Pricing and Its Alternatives," Journal of Industrial Economics, Wiley Blackwell, vol. 59(4), pages 630-660, December.
  4. Alessandro Acquisti & Hal R. Varian, 2002. "Contidioning Prices on Purchase History," Microeconomics 0210001, EconWPA.
  5. Chenghuan Sean Chu & Phillip Leslie & Alan Sorensen, 2011. "Bundle-Size Pricing as an Approximation to Mixed Bundling," American Economic Review, American Economic Association, vol. 101(1), pages 263-303, February.
  6. Crawford, Gregory S & Shum, Matthew, 2007. "Monopoly Quality Degradation and Regulation in Cable Television," Journal of Law and Economics, University of Chicago Press, vol. 50(1), pages 181-219, February.
  7. Graddy, Kathryn & Hall, George, 2011. "A dynamic model of price discrimination and inventory management at the Fulton Fish Market," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 6-19.
  8. Martin Feldstein, 1992. "College Scholarship Rules and Private Saving," NBER Working Papers 4032, National Bureau of Economic Research, Inc.
  9. Harikesh Nair, 2007. "Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games," Quantitative Marketing and Economics, Springer, vol. 5(3), pages 239-292, September.
  10. Wendy W. Moe & Peter S. Fader, 2004. "Dynamic Conversion Behavior at E-Commerce Sites," Management Science, INFORMS, vol. 50(3), pages 326-335, March.
  11. Coase, Ronald H, 1972. "Durability and Monopoly," Journal of Law and Economics, University of Chicago Press, vol. 15(1), pages 143-49, April.
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Cited by:
  1. Baye, Irina & Sapi, Geza, 2014. "Targeted pricing, consumer myopia and investment in customer-tracking technology," DICE Discussion Papers 131, Heinrich‐Heine‐Universität Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).

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