Predicting Season Ticket Holder Retention Using Rich Behavioral Data

in Journal of Sport Management
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  • 1 Swinburne University of Technology
  • | 2 Deakin University
  • | 3 RMIT University
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Season ticket holders are a vital source of revenue for professional teams, but retention remains a perennial issue. Prior research has focused on broad variables, such as relationship tenure, game attendance frequency, and renewal intention, and has generally been limited to survey data with its attenuate problems. To advance this important research agenda, the present study analyzes team-supplied behavioral data to investigate and predict retention as a loyalty outcome for a single professional team over a 3-year period. Specifically, the authors embrace a broad range of loyalty measures and team performance to predict retention and employ novel data mining techniques to improve predictive accuracy.

Karg is with Swineburne University of Technology, Hawthorn, Victoria, Australia. Tamaddoni and Ewing are with  Deakin University, Burwood, Victoria, Australia. McDonald is with RMIT University, Melbourne, Victoria, Australia.

Karg (akarg@swin.edu.au) is corresponding author.
  • Ainslie, A., & Pitt, L. (1992). Customer retention analyses: An application of descriptive and inferential statistics in database marketing. Journal of Direct Marketing, 6(3), 3143. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baade, R.A., & Tiehen, L.J. (1990). An analysis of major league baseball attendance. Journal of Sport and Social Issues, 14(1), 1432. doi:

  • Baker, B.J., Jordan, J.S., & Funk, D.C. (2018). Run again another day: The role of consumer characteristics and satisfaction in repeat consumption of a sport-related experience product. Journal of Sport Management, 32(1), 3852 . doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bauer, H.N., Stokburger-Sauer, N.E., & Exler, S. (2008). Brand image and fan loyalty in professional team sport: A refined model and empirical assessment. Journal of Sport Management, 22(2), 205226. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bejou, D., Wray, B., & Ingram, T. (1996). Determinants of relationship quality: An artificial neutral network analysis. Journal of Business Research, 36(2), 137143. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berry, M.J.A., & Linoff, G.S. (2004). Machine learning techniques for marketing, sales, and customer relationship management (2nd ed.). Indianapolis, IN: Wiley Publishing.

    • Search Google Scholar
    • Export Citation
  • Bloemer, J., & de Ruyter, K. ( 1998). On the relationship between store image, store satisfaction and store loyalty. European Journal of Marketing, 32(5/6), 499513. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bolton, R, Kannan, P., & Bramlett M. (2000). Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science, 28(1), 95108. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buckinx, W., & Van den Poel, D. (2005). Customer base analysis: Partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting. European Journal of Operational Research, 164(1), 252268. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burez, J., & Van den Poel, D. (2007). CRM at a pay-TV company: Using analytical models to reduce customer attrition by targeted marketing for subscription services. Expert Systems with Applications, 32(2), 277. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burez, J., & Van den Poel, D. (2009). Handling class imbalance in customer churn prediction. Expert Systems with Applications, 36(3), 46264636. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cialdini, R.B., Borden, R.J., Thorne, A., Walker, M.R., Freeman, S., & Sloan, L.R. (1976). Basking in reflected glory: Three (football) field studies. Journal of Personality and Social Psychology, 34(3), 366375. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coussement, K. (2014). Improving customer retention management through cost-sensitive learning. European Journal of Marketing, 48(3/4), 477495. doi:.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coussement, K., & De Bock, K.W. (2013). Customer churn prediction in the online gambling industry: The beneficial effect of ensemble learning. Journal of Business Research, 66(9), 16291636. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coussement, K., & Van den Poel, D. ( 2008). Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques. Expert Systems with Applications, 34(1), 313327. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dawes, J. (2009). The effect of service price increases on customer retention: The moderating role of customer tenure and relationship breadth. Journal of Service Research, 11(3), 232245. doi:.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • De Bock, K.W., & Van den Poel, D. (2011). An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction. Expert Systems with Applications, 38(10), 1229312301. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • De Caigny, A., Coussement, K., & De Bock, K.W. (2018). A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees. European Journal of Operational Research, 269(2), 760772. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeSchriver, T.D., & Jensen, P.E. ( 2002). Determinants of spectator attendance at NCAA Division II football contests. Journal of Sport Management, 16(4), 311. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dick, A.S., & Basu, K. (1994). Customer loyalty: Towards an integrated framework. Journal of The Academy of Marketing Science, 22(2), 99113. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doyle, J.P., Filo, K., Lock, D., Funk, D.C., & McDonald, H. (2016). Exploring PERMA in spectator sport: Applying positive psychology to examine the individual-level benefits of sport consumption. Sport Management Review, 19(5), 506519. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doyle, J.P., Kunkel, T., & Funk, D. (2013). Sports spectator segmentation: Examining the differing psychological connections among spectators of leagues and teams. International Journal of Sports Marketing and Sponsorship, 14(2), 2036. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • East, R., Gendall, P., Hammond, K., & Lomax, W. (2005). Consumer loyalty: Singular, additive or interactive? Australasian Marketing Journal, 13(2), 1026. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • East, R., Hammond, K., & Gendall, P. (2006). Fact and fallacy in retention marketing. Journal of Marketing Management, 22(1/2), 523. doi:

  • Fader, P.S., & Hardie, B.G.S. (2009). Probability models for customer-base analysis. Journal of Interactive Marketing, 23(1), 6169. doi:

  • Funk, D., Alexandris, K., & McDonald, H. (2016). Sport consumer behaviour: Marketing strategies (2nd ed.). London, UK: Routledge.

  • Funk, D.C., & James, J.D. (2001). The psychological continuum model: A conceptual framework for understanding an individual’s psychological connection to sport. Sport Management Review, 4(2), 119150. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • George, M., & Wakefield, K. (2018). Modeling the consumer journey for membership services. Journal of Services Marketing, 32(2), 113125. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gladden, J.M., & Funk, D.C. (2001). Understanding brand loyalty in professional sport: Examining the link between brand associations and brand loyalty. International Journal of Sports Marketing & Sponsorship, 3, 6791. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gladden, J.M., Milne, G.R., & Sutton, W.A. (1998). A conceptual framework for assessing brand equity in Division I college athletics. Journal of Sport Management, 12(1), 119. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gupta, S., Hanssens, D., Hardie, B., Kahn, W., Kumar, V., Lin, N., … Sriram, S. (2006). Modeling customer lifetime value. Journal of Service Research, 9(2), 139. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gupta, A., Su, B., & Walter, Z. (2004). Risk profile and consumer shopping behavior in electronic and traditional channels. Decision Support Systems, 38(3), 347367. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hastie, T., Tibshirani, R., & Friedman, J.H. (2008). The elements of statistical learning (2nd ed.). New York, NY: Springer.

  • Hill, B., & Green, B.C. (2000). Repeat attendance as a function of involvement, loyalty, and the sportscape across three football contexts. Sport Management Review, 3 (2), 145162. doi:.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Homburg, C., & Giering, A. (1999). Personal characteristics as moderators of the relationship between customer satisfaction and loyalty—An empirical analysis. Psychology and Marketing, 18(1), 4366. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iwasaki, Y., & Havitz, M. (2004). Examining relationships between leisure involvement, psychological commitment and loyalty to a recreation agency. Journal of Leisure Research, 36(1), 4572. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jacoby, J., & Chestnut, R.W. (1978). Brand loyalty measurement and management. New York, NY: Wiley.

  • Jensen, J.A., Turner, B.A., James, J., McEvoy, C., Seifried, C., Delia, E., … Walsh, P. (2016). Forty years of BIRGing: New perspectives on Cialdini’s seminal studies. Journal of Sport Management, 30(2), 149. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263291. doi:

  • Kamakura, W., Mela, C., Ansari, A., Bodapati, A., Fader, P., Iyengar, R., … Wilcox, R. (2005). Choice models and customer relationship management. Marketing Letters, 16(3), 279291. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kamakura, W., Ramaswami, S.N., & Srivastava, R.K. (1991). Applying latent trait analysis in the evaluation of prospects for cross-selling of financial services. International Journal of Research in Marketing, 8(4), 329349. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Katz, M., Heere, B., & Melton, E.N. (2020). Predicting fan behavior through egocentric network analysis: Examining season-ticket holder renewal. Journal of Sport Management, 34(3), 217228. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Katz, M., Ward, R.M., & Heere, B. (2018). Explaining attendance through the brand community triad: Integrating network theory and team identification. Sport Management Review, 21(2), 176188. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kotler, P. (1994). Marketing management, analysis, planning, implementation, and control. London, UK: Prentice-Hall International.

  • Lally, P., & Gardner, B. (2013). Promoting habit formation. Health Psychology Review, 7(Suppl. 1), S137S158. doi:

  • Lapidus, R., & Schibrowsky, J. (1996). Do the hot dogs taste better when the home team’ wins? Journal of Consumer Satisfaction Dissatisfaction and Complaining Behavior, 9, 111. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Larivière, B., & Van den Poel, D. (2005). Predicting customer retention and profitability by using random forests and regression forests techniques. Expert Systems with Applications, 29(2), 472484. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lawrence, H.J., Contorno, R.T., & Steffek, B. (2013). Selling premium seating in today’s sport marketplace. Sport Marketing Quarterly, 22(1), 919.

    • Search Google Scholar
    • Export Citation
  • Lemmens, A., & Croux, C. (2006). Bagging and boosting classification trees to predict churn. Journal of Marketing Research, 43(2), 276286. doi:

  • Lemmens, A., & Gupta, S. (2013). Managing churn to maximize profits [Working paper]. Retrieved from http://www.hbs.edu/ faculty/Publication%20Files/14-020_3553a2f4-8c7b-44e6-9711-f75dd56f624e.pdf

    • Search Google Scholar
    • Export Citation
  • Lock, D., & Heere, B. (2017). Identity crisis: A theoretical analysis of ‘team identification’ research. European Sport Management Quarterly, 17(4), 413435. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahony, D.F., Madrigal, R., & Howard, D. (2000). Using the psychological commitment to a team (PCT) scale to segment sport consumer based on loyalty. Sport Marketing Quarterly, 9, 1525.

    • Search Google Scholar
    • Export Citation
  • McDonald, H. (2010). The factors influencing churn rates among season ticket holders: An empirical analysis. Journal of Sport Management, 24(6), 676701. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McDonald, H., & Karg, A. (2014). Managing co-creation in professional sports: The antecedents and consequences of ritualized spectator behavior. Sport Management Review, 17(3), 292309. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McDonald, H., Karg, A.J., & Leckie, C. (2014). Predicting which season ticket holders will renew and which will not. European Sport Management Quarterly, 14(5), 503520. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McDonald, H., Karg, A.J., & Vocino, A. (2013). Measuring season ticket holder satisfaction: Rationale, scale development and longitudinal validation. Sport Management Review, 16(1), 4153. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McDonald, H., & Shaw, R.N. (2005). Satisfaction as a predictor of football club members’ intentions. International Journal of Sports Marketing and Sponsorship, 7(1), 7581. doi:.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McDonald, H., & Stavros, C. (2007). A defection analysis of lapsed season ticket holders: A consumer and organizational study. Sport Marketing Quarterly, 16(4), 218229. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miguéis, V.L., Camanho, A., & Falcão e Cunha, J. (2013). Customer attrition in retailing: An application of multivariate adaptive regression splines. Expert Systems with Applications, 40(16), 62256232. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morgan, R., & Hunt S. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 2038. doi:

  • Mullin, B., Hardy, S., & Sutton, W. (2014). Sport marketing (4th ed.). New York, NY: Human Kinetics.

  • Oliver, R.L. (1999). Whence consumer loyalty? Journal of Marketing, 63(4, Suppl. 1), 3344. doi:

  • Olsen, L.L., & Johnson, M.D. (2003). Service equity, satisfaction, and loyalty: From transaction-specific to cumulative evaluations. Journal of Service Research, 5(3), 184195. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ostrom, A., Parasuraman, A., Bowen, D.E., Patrício, L., & Voss, C.A. (2015). Service research priorities in a rapidly changing context. Journal of Service Research, 18(2), 127159. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ouellette, J.A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 5474. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pan, D.W., Gabert, T.E., McGaugh, E.C., & Branvold, S.E. (1997). Factors and differential demographic effects on purchases of season tickets for intercollegiate basketball games. Journal of Sport Behavior, 20(4), 447. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pritchard, M.P., Havitz, M.E., & Howard, D.R. (1999). Analyzing the commitment-loyalty link in service contexts. Journal of the Academy of Marketing Science, 27(3), 333348. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pritchard, M.P., & Stinson, J.L. ( 2014). Leveraging brands in sport business. New York, NY: Routledge.

  • Provost, F., & Fawcett, T. (2013). Data Science for Business: What you need to know about machine learning and data-analytic thinking. London, UK: O’ Reilly Media.

    • Search Google Scholar
    • Export Citation
  • Reichheld, F. (1996). Learning from customer defection. Harvard Business Review, 74(2), 5669.

  • R Core Team. (2016). R: A language and environment for statistical computing. R: A language and environment for statistical computing. Retrieved from http://www.R-project.org/

    • Search Google Scholar
    • Export Citation
  • Reichheld, F.F., & Sasser, W. (1990). Zero defections: Quality comes to services. Harvard Business Review, 68(5), 105111. PubMed ID: 10107082

    • Search Google Scholar
    • Export Citation
  • Reichheld F., & Teal, T. (1996). The loyalty effect: The hidden force behind growth, profits, and lasting value. Boston, MA: Harvard Business School Press.

    • Search Google Scholar
    • Export Citation
  • Reinartz, W.J., & Kumar, V. (2000). On the profitability of long-life customers in a noncontractual setting: An empirical investigation and implications for marketing. Journal of Marketing, 64(4), 1735. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sandström, S., Edvardsson, B., Kristensson, P., & Magnusson, P. (2008). Value in use through service experience. Managing Service Quality: An International Journal, 18(2), 112126. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schreyer, D., & Dauper, D. (2018). Determinants of spectator no-show behaviour: First empirical evidence from the German Bundesliga. Applied Economic Letters, 25(21), 14751480. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schreyer, D., Schmidt, S., & Torgler, B. (2016). Against all odds? Exploring the role of game outcome uncertainty in season ticket holders’ stadium attendance demand. Journal of Economic Psychology, 56, 192217.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schreyer, D., Schmidt, S., & Torgler, B. (2019). Football spectator no-show behavior. Journal of Sport Economics, 20(4), 580602 . doi:

  • Shapiro, S.L., Dwyer, B., & Drayer, J. (2016). Examining the role of price fairness in sport consumer ticket purchase decisions. Sport Marketing Quarterly, 25(4), 167187.

    • Search Google Scholar
    • Export Citation
  • Shilbury, D., Westerbeek, H., Quick, S., Funk, D., & Karg, A. (2014). Strategic sport marketing. Sydney, NSW: Allen & Unwin.

  • Sloan, L.R. (1989). The motives of sports fans. In J.H. Goldstein (Ed.) Sports, games, and play: Social & psychological viewpoints (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.

    • Search Google Scholar
    • Export Citation
  • Smith, A.C.T., & Stewart, B. (2010). The special features of sport: A critical revisit. Sport Management Review, 13(1), 113. doi:

  • Snyder, C.R., Lassegard, M., & Ford, C.E. (1986). Distancing after group success and failure: Basking in reflected glory and cutting off reflected failure. Journal of Personality and Social Psychology, 51(2), 382388. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tamaddoni, A., Stakhovych, S., & Ewing, M. (2016). Comparing churn prediction techniques and assessing their performance: A contingent perspective. Journal of Service Research, 19(2), 123141. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tamaddoni, A., Stakhovych, S., & Ewing, M. (2017). The impact of personalised incentives on the profitability of customer retention campaigns. Journal of Marketing Management, 33(5–6), 327347. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tamaddoni Jahromi, A., Stakhovych, S., & Ewing, M. (2014). Managing B2B customer churn, retention and profitability. Industrial Marketing Management, 43(7), 12581268. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wann, D.L., & Schrader, M.P. ( 1996). An analysis of the stability of sport team identification. Perceptual and Motor Skills, 82(1), 322322. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wharton Business School. (2015). The other moneyball: Using analytics to sell season tickets. Retrieved from http://knowledge.wharton.upenn.edu/article/the-other-moneyball-using-analytics-to-sell-season-tickets/

    • Search Google Scholar
    • Export Citation
  • Wood, W., & Neal, D.T. (2009). The habitual consumer. Journal of Consumer Psychology, 19(4), 579592. doi:

  • Wu, C., & Chen, H.-L. (2000). Counting your customers: Compounding customer’s in-store decisions, interpurchase time and repurchasing behavior. European Journal of Operational Research, 127(1), 109119. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yu, X., Guo, S., Guo, J., & Huang, X. (2011). An extended support vector machine forecasting framework for customer churn in e-commerce. Expert Systems with Applications, 38(3), 14251430. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zaharia, N., Bascaia, R., Gray, D., & Stotlar, D. (2016). No more ‘good’ intentions: Purchase behaviors in sponsorship. Journal of Sport Management, 30(2), 162175. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zahavi, J., & Levin, N. (1997). Applying neural computing to target marketing. Journal of Direct Marketing, 11(1), 522. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zeithaml, V., Berry, L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 3146. doi:

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