IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v68y2022i12p8933-8962.html
   My bibliography  Save this article

Social Referral Programs for Freemium Platforms

Author

Listed:
  • Rodrigo Belo

    (Nova School of Business and Economics, Universidade Nova de Lisboa, Campus de Carcavelos, 2775-405 Carcavelos, Portugal; Rotterdam School of Management, Erasmus University, 3062 PA Rotterdam, Netherlands)

  • Ting Li

    (Rotterdam School of Management, Erasmus University, 3062 PA Rotterdam, Netherlands)

Abstract

We examine how freemium platforms can design social referral programs to encourage growth and engagement without sacrificing revenue. On the one hand, social referral programs generate new referrals from users who would not have paid for the premium features. On the other hand, they also attract new referrals from users who would have paid but prefer to invite others, resulting in more referrals but fewer paying users. We use data from a large-scale randomized field experiment in an online dating platform to assess the effects of adding referrals programs to freemium platforms and changing the referral requirements on users’ behavior, namely, on their decisions to invite, pay, and engage with the platform. We find that introducing referral programs in freemium platforms can significantly contribute to increasing the number of referrals at the expense of revenue. Platforms can avoid the loss in revenue by reserving some premium features exclusively for paying users. We also find that increasing referral requirements in social referral programs can work as a double-edged sword. Increasing the referral threshold results in more referrals and higher total revenue. Yet these benefits appear to come at a cost. Users become less engaged, decreasing the value of the platform for all users. We explore two mechanisms that help to explain the differences in users’ social engagement. Finally, and contrary to prior findings, we find that the quality of the referrals is not affected by the referral requirements. We discuss the theoretical and practical implications of our research.

Suggested Citation

  • Rodrigo Belo & Ting Li, 2022. "Social Referral Programs for Freemium Platforms," Management Science, INFORMS, vol. 68(12), pages 8933-8962, December.
  • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:12:p:8933-8962
    DOI: 10.1287/mnsc.2022.4301
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2022.4301
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2022.4301?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Zijun (June) Shi & Kaifu Zhang & Kannan Srinivasan, 2019. "Freemium as an Optimal Strategy for Market Dominant Firms," Marketing Science, INFORMS, vol. 38(1), pages 150-169, January.
    2. Raghuram Iyengar & Christophe Van den Bulte & Jae Young Lee, 2015. "Social Contagion in New Product Trial and Repeat," Marketing Science, INFORMS, vol. 34(3), pages 408-429, May.
    3. Eyal Biyalogorsky & Eitan Gerstner & Barak Libai, 2001. "Customer Referral Management: Optimal Reward Programs," Marketing Science, INFORMS, vol. 20(1), pages 82-95, August.
    4. Laura J. Kornish & Qiuping Li, 2010. "Optimal Referral Bonuses with Asymmetric Information: Firm-Offered and Interpersonal Incentives," Marketing Science, INFORMS, vol. 29(1), pages 108-121, 01-02.
    5. Marius F. Niculescu & D. J. Wu, 2014. "Economics of Free Under Perpetual Licensing: Implications for the Software Industry," Information Systems Research, INFORMS, vol. 25(1), pages 173-199, March.
    6. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Michael R. Galbreth & Bikram Ghosh & Mikhael Shor, 2012. "Social Sharing of Information Goods: Implications for Pricing and Profits," Marketing Science, INFORMS, vol. 31(4), pages 603-620, July.
    8. Duncan Sheppard Gilchrist & Emily Glassberg Sands, 2016. "Something to Talk About: Social Spillovers in Movie Consumption," Journal of Political Economy, University of Chicago Press, vol. 124(5), pages 1339-1382.
    9. David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
    10. Jaehwuen Jung & Ravi Bapna & Joseph M. Golden & Tianshu Sun, 2020. "Words Matter! Toward a Prosocial Call-to-Action for Online Referral: Evidence from Two Field Experiments," Information Systems Research, INFORMS, vol. 31(1), pages 16-36, March.
    11. Sinan Aral & Dylan Walker, 2011. "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks," Management Science, INFORMS, vol. 57(9), pages 1623-1639, February.
    12. Sara Hanson & Hong Yuan, 2018. "Friends with benefits: social coupons as a strategy to enhance customers’ social empowerment," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 768-787, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuichiro Kamada & Aniko Öry, 2020. "Contracting with Word-of-Mouth Management," Management Science, INFORMS, vol. 66(11), pages 5094-5107, November.
    2. Tianshu Sun & Siva Viswanathan & Elena Zheleva, 2021. "Creating Social Contagion Through Firm-Mediated Message Design: Evidence from a Randomized Field Experiment," Management Science, INFORMS, vol. 67(2), pages 808-827, February.
    3. Inyoung Chae & Andrew T. Stephen & Yakov Bart & Dai Yao, 2017. "Spillover Effects in Seeded Word-of-Mouth Marketing Campaigns," Marketing Science, INFORMS, vol. 36(1), pages 89-104, January.
    4. Lili Wang & Zoey Chen, 2022. "The effect of incentive structure on referral: the determining role of self-construal," Journal of the Academy of Marketing Science, Springer, vol. 50(5), pages 1091-1110, September.
    5. Meyners, Jannik & Barrot, Christian & Becker, Jan U. & Bodapati, Anand V., 2017. "Reward-scrounging in customer referral programs," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 382-398.
    6. Liangfei Qiu & Zhan (Michael) Shi & Andrew B. Whinston, 2018. "Learning from Your Friends’ Check-Ins: An Empirical Study of Location-Based Social Networks," Information Systems Research, INFORMS, vol. 29(4), pages 1044-1061, December.
    7. Shan Huang & Sinan Aral & Yu Jeffrey Hu & Erik Brynjolfsson, 2020. "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment," Marketing Science, INFORMS, vol. 39(6), pages 1142-1165, November.
    8. Stephen, Andrew T. & Lehmann, Donald R., 2016. "How word-of-mouth transmission encouragement affects consumers' transmission decisions, receiver selection, and diffusion speed," International Journal of Research in Marketing, Elsevier, vol. 33(4), pages 755-766.
    9. Heike M. Wolters & Christian Schulze & Karen Gedenk, 2020. "Referral Reward Size and New Customer Profitability," Marketing Science, INFORMS, vol. 39(6), pages 1166-1180, November.
    10. Jin, Liyin & Huang, Yunhui, 2014. "When giving money does not work: The differential effects of monetary versus in-kind rewards in referral reward programs," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 107-116.
    11. Walsh, Gianfranco & Elsner, Ralf, 2012. "Improving referral management by quantifying market mavens’ word of mouth value," European Management Journal, Elsevier, vol. 30(1), pages 74-81.
    12. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    13. Yifan Dou & Marius F. Niculescu & D. J. Wu, 2013. "Engineering Optimal Network Effects via Social Media Features and Seeding in Markets for Digital Goods and Services," Information Systems Research, INFORMS, vol. 24(1), pages 164-185, March.
    14. Irina Heimbach & Oliver Hinz, 2018. "The Impact of Sharing Mechanism Design on Content Sharing in Online Social Networks," Information Systems Research, INFORMS, vol. 29(3), pages 592-611, September.
    15. Ariel BenYishay & A. Mushfiq Mobarak, 2014. "Social Learning and Communication," NBER Working Papers 20139, National Bureau of Economic Research, Inc.
    16. Tingting Song & Jinghua Huang & Yong Tan & Yifan Yu, 2019. "Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms," Service Science, INFORMS, vol. 30(1), pages 191-203, March.
    17. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    18. Tavasoli, Ali & Shakeri, Heman & Ardjmand, Ehsan & Young, William A., 2021. "Incentive rate determination in viral marketing," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1169-1187.
    19. Yanhao Wei & Pinar Yildirim & Christophe Van den Bulte & Chrysanthos Dellarocas, 2016. "Credit Scoring with Social Network Data," Marketing Science, INFORMS, vol. 35(2), pages 234-258, March.
    20. Jaehwuen Jung & Ravi Bapna & Joseph M. Golden & Tianshu Sun, 2020. "Words Matter! Toward a Prosocial Call-to-Action for Online Referral: Evidence from Two Field Experiments," Information Systems Research, INFORMS, vol. 31(1), pages 16-36, March.

    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:inm:ormnsc:v:68:y:2022:i:12:p:8933-8962. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.