Converting freemium customers from free to premium—the role of the perceived premium fit in the case of music as a service

Abstract

Freemium seems to be a promising solution for content providers to earn money now that Web 2.0 users feel entitled to free services and content services like Spotify generally accept this concept. Providers using freemium offer their service in free basic and paid premium versions. To prompt users to pay, a free version has fewer functions. However, no studies have yet investigated whether limiting features is the best strategy for converting users into paying customers, and, if so, how many functional differences there should be between free and premium versions. Therefore, our study aims to measure whether a free service’s limitations impact the evaluation of free and premium versions. Drawing on the Dual Mediation Hypothesis and the Elaboration Likelihood Model, we examined 317 freemium users’ survey responses. Our results indicate that companies providing freemium services can increase the probability of user conversion by providing a strong functional fit between their free and premium services.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

References

  1. Anderson, C. (2009). Free—the future of a radical price. London: Random House.

    Google Scholar 

  2. Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402.

    Article  Google Scholar 

  3. Bourreau, M., & Lethiais, V. (2007). Pricing information goods: Free vs. Pay content. In E. Brousseau & N. Curien (Eds.), Internet and digital economics (pp. 345–367). Cambridge: Cambridge University Press.

    Google Scholar 

  4. Brown, S. P., & Stayman, D. M. (1992). Antecedents and consequences of attitude toward the ad: a meta-analysis. The Journal of Consumer Research, 19(1), 34–51.

    Article  Google Scholar 

  5. Buxmann, P., Strube, J., & Pohl, G. (2007). Cooperative pricing in digital value chains—the case of online music. Journal of Electronic Commerce Research, 8(1), 32–40.

    Google Scholar 

  6. Cheng, H. K., & Tang, Q. C. (2010). Free trial or no free trial: optimal software product design with network effects. European Journal of Operational Research, 205(2), 437–447.

    Article  Google Scholar 

  7. Chin, W. W. (1998). The partial least squares approach to structural equation modelling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  8. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  9. Coulter, K. S., & Punj, G. (1999). Influence of viewing context on the determinants of attitude toward the ad and the brand. Journal of Business Research, 45(1), 47–58.

    Article  Google Scholar 

  10. d’Astous, A., & Landreville, V. (2003). An experimental investigation of factors affecting consumers’ perceptions of sales promotions. European Journal of Marketing, 37(11–12), 1746–1761.

    Article  Google Scholar 

  11. Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 28(3), 307–319.

    Article  Google Scholar 

  12. Dörr, J., Benlian, A., Vetter, J., & Hess, T. (2010, August 12–15). Pricing of content services - an empirical investigation of music as a service. Paper presented at the Proceedings of the sixteenth Americas Conference on Information Systems, Lima, Peru.

  13. Dörr, J., Wagner, T. M., Benlian, A., & Hess, T. (2013). Music as a service: an alternative to music piracy? An empirical investigation of the intention to use music streaming services. Business & Information Systems Engineering, 5(6), 383–396.

    Article  Google Scholar 

  14. Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: Lisrel and pls applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440–452.

    Article  Google Scholar 

  15. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  16. Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analyses with readings. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  17. Helm, R., Mark, A., & Bley, S. (2009). The effect of free product premiums on attitudes and buying intention for durable goods: moderating effects of value and product premium fit in the dual mediation model. European Retail Research, 23(1), 21–45.

    Article  Google Scholar 

  18. Homer, P. M. (1990). The mediating role of attitude toward the ad: some additional evidence. Journal of Marketing Research, 27(1), 78–86.

    Article  Google Scholar 

  19. Hung, J. (2010). Economic essentials of online publishing with associated trends and patterns. Publishing Research Quarterly, 26(2), 79–95.

    Article  Google Scholar 

  20. IFPI. (2012). Digital music report 2012—expanding choice. Going global. London: IFPI Communications.

  21. Karson, E. J., & Fisher, R. J. (2005a). Predicting intentions to return to the web site: extending the dual mediation hypothesis. Journal of Interactive Marketing, 19(3), 2–14.

    Article  Google Scholar 

  22. Karson, E. J., & Fisher, R. J. (2005b). Reexamining and extending the dual mediation hypothesis in an on-line advertising context. Psychology & Marketing, 22(4), 333–351.

    Article  Google Scholar 

  23. Lambert, D. M., & Harrington, T. C. (1990). Measuring nonresponse bias in customer service mail surveys. Journal of Business Logistics, 11(2), 5–25.

    Google Scholar 

  24. Liu, C. Z., Au, Y. A., & Choi, H. S. (2012, December 16–19). An empirical study of the freemium strategy for mobile apps: Evidence from the google play market. Paper presented at the Proceedings of the thirty third International Conference on Information Systems, Orlando, FL, USA.

  25. Locander, W. B., & Hermann, P. W. (1979). The effect of self-confidence and anxiety on information seeking in consumer risk reduction. Journal of Marketing Research, 16(2), 268–274.

    Article  Google Scholar 

  26. López, I., & Ruiz, S. (2011). Explaining website effectiveness: the hedonic-utilitarian dual mediation hypothesis. Electronic Commerce Research and Applications, 10(1), 49–58.

    Article  Google Scholar 

  27. Lyons, K., Messinger, P., Niu, R., & Stroulia, E. (2012). A tale of two pricing systems for services. Information Systems and e-Business Management, 10(1), 19–42.

    Article  Google Scholar 

  28. MacKenzie, S. B., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: a test of competing explanations. Journal of Marketing Research, 23(2), 130–143.

    Article  Google Scholar 

  29. Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies. Journal of Marketing, 69(2), 61–83.

    Article  Google Scholar 

  30. Murray, K. B. (1991). A test of services marketing theory: consumer information acquisition activities. Journal of Marketing, 55(1), 10–25.

    Article  Google Scholar 

  31. Oestreicher-Singer, G., & Zalmanson, L. (2013). Content or community? A digital business strategy for content providers in the social age. MIS Quarterly, 37(2), 591–616.

    Google Scholar 

  32. Pavlou, P. A., & Fygenson, M. (2006). Understanding and prediction electronic commerce adoption: an extension of the theory of planned behavior. MIS Quarterly, 30(1), 115–143.

    Google Scholar 

  33. Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: Classic and contemporary approaches. Dubuque: Wm. C. Brown.

  34. Pujol, N. (2010). Freemium: Attributes of an emerging business model (working paper). Available at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1718663.

  35. Ringle, C. M., Wende, S., & Will, S. (2005). Hamburg. http://www.smartpls.de.

  36. Rogers, E. M. (1995). Diffusion of innovations. New York: Free Press.

    Google Scholar 

  37. Semenzin, D., Meulendijks, E., Seele, W., Wagner, C., & Brinkkemper, S. (2012). Differentiation in freemium: Where does the line lie? Paper presented at the Proceedings of the third International Conference on Software Business, Cambridge, MA, USA.

  38. Shapiro, C., & Varian, H. R. (1998a). Information rules: A strategic guide to the network economy. Boston: Harvard Business School Press.

    Google Scholar 

  39. Shapiro, C., & Varian, H. R. (1998b). Versioning: the smart way to sell information. Harvard Business Review, 76(6), 106–115.

    Google Scholar 

  40. Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society. Series B (Methodological), 36(2), 111–147.

    Google Scholar 

  41. Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2–3), 172–194.

    Article  Google Scholar 

  42. Tellis, G. J. (1997). Advertising and sales promotion strategy. Reading: Addison-Wesley.

    Google Scholar 

  43. Teng, L., & Laroche, M. (2007). Building and testing models of consumer purchase intention in competitive and multicultural environments. Journal of Business Research, 60(3), 260–268.

    Article  Google Scholar 

  44. Veit, D., Clemons, E., Benlian, A., Buxmann, P., Hess, T., Kundisch, D., Leimeister, J., Loos, P., & Spann, M. (2014). Business models. Business & Information Systems Engineering, 6(1), 45–53.

    Article  Google Scholar 

  45. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

    Google Scholar 

  46. Wagner, T. M., Benlian, A., & Hess, T. (2013). The Advertising Effect of Free – Do Free Basic Versions Promote Premium Versions within the Freemium Business Model of Music Services? Proceedings of the forty sixth Hawaii International Conference on System Sciences, Maui, HI, USA, pp. 1–10.

  47. Wilson, F. (2006, 03-24-2012). A freemium business model. Retrieved from http://www.avc.com/a_vc/2006/03/the_freemium_bu.html

  48. Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Thomas M. Wagner.

Additional information

Responsible Editors: Jan Marco Leimeister and Hubert Österle

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wagner, T.M., Benlian, A. & Hess, T. Converting freemium customers from free to premium—the role of the perceived premium fit in the case of music as a service. Electron Markets 24, 259–268 (2014). https://doi.org/10.1007/s12525-014-0168-4

Download citation

Keywords

  • Freemium
  • Feature limitations
  • Conversion
  • Dual mediation hypothesis

JEL classification

  • L11
  • L82