IDEAS home Printed from https://ideas.repec.org/p/zrh/wpaper/329.html
   My bibliography  Save this paper

Digital Content Strategies

Author

Listed:
  • Daniel Halbheer

    () (Department of Business Administration (IBW), University of Zurich)

  • Florian Stahl

    () (Department of Business Administration (IBW), University of Zurich)

  • Oded Koenigsberg

    () (Department of Marketing, London Business School)

  • Donald R. Lehmann

    () (Marketing, Columbia Business School)

Abstract

This paper studies content strategies for online publishers of digital information goods. It examines sampling strategies and compares their performance to paid content and free content strategies. A sampling strategy, where some of the content is offered for free and consumers are charged for access to the rest, is known as a metered model in the newspaper industry. We analyze optimal decisions concerning the size of the sample and the price of the paid content when sampling serves the dual purpose of disclosing content quality and generating advertising revenue. We show in a reduced-form model how the publishers optimal ratio of advertising revenue to sales revenue is linked to characteristics of both the content market and the advertising market. We assume that consumers learn about content quality from the free samples in a Bayesian fashion. Surprisingly, we find that it can be optimal for the publisher to generate advertising revenue by offering free samples even when sampling reduces both prior quality expectations and content demand. In addition, we show that it can be optimal for the publisher to refrain from revealing quality through free samples when advertising effectiveness is low and content quality is high.

Suggested Citation

  • Daniel Halbheer & Florian Stahl & Oded Koenigsberg & Donald R. Lehmann, 2013. "Digital Content Strategies," Working Papers 329, University of Zurich, Department of Business Administration (IBW).
  • Handle: RePEc:zrh:wpaper:329
    as

    Download full text from publisher

    File URL: http://repec.business.uzh.ch/RePEc/zrh/wpaper/329_IBW_full.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Kapil Bawa & Robert Shoemaker, 2004. "The Effects of Free Sample Promotions on Incremental Brand Sales," Marketing Science, INFORMS, vol. 23(3), pages 345-363, November.
    2. Monic Sun, 2011. "Disclosing Multiple Product Attributes," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 20(1), pages 195-224, March.
    3. Simon P. Anderson & Régis Renault, 2006. "Advertising Content," American Economic Review, American Economic Association, vol. 96(1), pages 93-113, March.
    4. Marc Rysman, 2009. "The Economics of Two-Sided Markets," Journal of Economic Perspectives, American Economic Association, vol. 23(3), pages 125-143, Summer.
    5. Milgrom, Paul & Roberts, John, 1986. "Price and Advertising Signals of Product Quality," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 796-821, August.
    6. Ramnath K. Chellappa & Shivendu Shivendu, 2005. "Managing Piracy: Pricing and Sampling Strategies for Digital Experience Goods in Vertically Segmented Markets," Information Systems Research, INFORMS, vol. 16(4), pages 400-417, December.
    7. Hans Jarle Kind & Tore Nilssen & Lars Sørgard, 2009. "Business Models for Media Firms: Does Competition Matter for How They Raise Revenue?," Marketing Science, INFORMS, vol. 28(6), pages 1112-1128, 11-12.
    8. Yi Xiang & David A. Soberman, 2011. "Preview Provision Under Competition," Marketing Science, INFORMS, vol. 30(1), pages 149-169, 01-02.
    9. Amir Heiman & Bruce McWilliams & Zhihua Shen & David Zilberman, 2001. "Learning and Forgetting: Modeling Optimal Product Sampling Over Time," Management Science, INFORMS, vol. 47(4), pages 532-546, April.
    10. Boom, Anette, 2004. ""Download for Free": When do providers of digital goods offer free samples?," Discussion Papers 2004/28, Free University Berlin, School of Business & Economics.
    11. V. Joseph Hotz & Mo Xiao, 2013. "Strategic Information Disclosure: The Case Of Multiattribute Products With Heterogeneous Consumers," Economic Inquiry, Western Economic Association International, vol. 51(1), pages 865-881, January.
    12. Tülin Erdem & Michael P. Keane & Baohong Sun, 2008. "A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality," Marketing Science, INFORMS, vol. 27(6), pages 1111-1125, 11-12.
    13. Drew Fudenberg & Jean Tirole, 1991. "Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061414, January.
    14. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    15. Cheng, Hsing Kenneth & Tang, Qian Candy, 2010. "Free trial or no free trial: Optimal software product design with network effects," European Journal of Operational Research, Elsevier, vol. 205(2), pages 437-447, September.
    16. David Godes & Elie Ofek & Miklos Sarvary, 2009. "Content vs. Advertising: The Impact of Competition on Media Firm Strategy," Marketing Science, INFORMS, vol. 28(1), pages 20-35, 01-02.
    17. Hemant K. Bhargava & Vidyanand Choudhary, 2008. "Research Note--When Is Versioning Optimal for Information Goods?," Management Science, INFORMS, vol. 54(5), pages 1029-1035, May.
    18. Wilson, Robert, 1985. "Multi-dimensional signalling," Economics Letters, Elsevier, vol. 19(1), pages 17-21.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kretschmer, Tobias & Peukert, Christian, 2014. "Video killed the radio star? Online music videos and digital music sales," LSE Research Online Documents on Economics 60276, London School of Economics and Political Science, LSE Library.
    2. Anja Lambrecht & Avi Goldfarb & Alessandro Bonatti & Anindya Ghose & Daniel Goldstein & Randall Lewis & Anita Rao & Navdeep Sahni & Song Yao, 2014. "How do firms make money selling digital goods online?," Marketing Letters, Springer, vol. 25(3), pages 331-341, September.

    More about this item

    Keywords

    Information Goods; Sampling; Content Pricing; Advertising; Dorfman-Steiner Condition; Pricing; Product Quality; Bayesian Learning; News Websites;

    JEL classification:

    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zrh:wpaper:329. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Daniela Koller). General contact details of provider: http://edirc.repec.org/data/ibuzhch.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.