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Is my cross-promotion profitable? Evaluation of game-to-game cannibalization in free-to-play mobile games

Author

Listed:
  • Jean-Baptiste Débordès

    (HEC Montréal)

  • Gilles Caporossi

    (HEC Montréal)

  • Denis Larocque

    (HEC Montréal)

Abstract

Advertisements are a central source of revenue for free-to-play games. However, they could decrease in-app purchases (IAP) by reducing the quality of user experience or by causing early churn. We analyzed more than 50 million advertisements viewed in eight Gameloft games, and found that more than 139 thousand of them led to an install in another Gameloft game. Propensity score matching was used to account for selection bias in the decision to install the advertised game. This method allowed us to correct observational data to mimic a randomized experiment. Results reveal an overall 20.66% decrease in expected IAP revenues in the current game after the user installs the advertised game. This variation was found to be greater in higher revenue-generating games, but it did not appear to vary depending on the amount the user spent before seeing the advertisement. In the Gameloft context, the decrease in future expected IAP revenues in the current game was lower than the gains in the newly installed game, resulting in an overall 17.69% increase in future expected revenues. The results of this paper suggest companies should carefully select which game is promoted, in order to fully benefit from cross-promotion.

Suggested Citation

  • Jean-Baptiste Débordès & Gilles Caporossi & Denis Larocque, 2021. "Is my cross-promotion profitable? Evaluation of game-to-game cannibalization in free-to-play mobile games," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 173-184, September.
  • Handle: RePEc:pal:jmarka:v:9:y:2021:i:3:d:10.1057_s41270-021-00122-x
    DOI: 10.1057/s41270-021-00122-x
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    1. Tsung-Chi Liu & Li-Wei Wu, 2009. "Cross-buying evaluations in the retail banking industry," The Service Industries Journal, Taylor & Francis Journals, vol. 29(7), pages 903-922, July.
    2. Jalan, Jyotsna & Ravallion, Martin, 2003. "Does piped water reduce diarrhea for children in rural India?," Journal of Econometrics, Elsevier, vol. 112(1), pages 153-173, January.
    3. Dawes, John G., 2012. "Brand-Pack Size Cannibalization Arising from Temporary Price Promotions," Journal of Retailing, Elsevier, vol. 88(3), pages 343-355.
    4. Kollmann, Tobias & Kuckertz, Andreas & Kayser, Ina, 2012. "Cannibalization or synergy? Consumers' channel selection in online–offline multichannel systems," Journal of Retailing and Consumer Services, Elsevier, vol. 19(2), pages 186-194.
    5. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    6. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    7. Mendola, Mariapia, 2007. "Agricultural technology adoption and poverty reduction: A propensity-score matching analysis for rural Bangladesh," Food Policy, Elsevier, vol. 32(3), pages 372-393, June.
    8. Chiung-Ju Liang & Hui-Ju Chen & Wen-Hung Wang, 2008. "Does online relationship marketing enhance customer retention and cross-buying?," The Service Industries Journal, Taylor & Francis Journals, vol. 28(6), pages 769-787, July.
    9. Shih-Ping Jeng, 2008. "Effects of corporate reputations, relationships and competing suppliers' marketing programmes on customers' cross-buying intentions," The Service Industries Journal, Taylor & Francis Journals, vol. 28(1), pages 15-26, January.
    10. Skallerud, Kåre & Korneliussen, Tor & Olsen, Svein Ottar, 2009. "An examination of consumers’ cross-shopping behaviour," Journal of Retailing and Consumer Services, Elsevier, vol. 16(3), pages 181-189.
    11. McColl, Rod & Macgilchrist, Renaud & Rafiq, Shuddhasattwa, 2020. "Estimating cannibalizing effects of sales promotions: The impact of price cuts and store type," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    12. Nicholas Ross, 2018. "Customer retention in freemium applications," Journal of Marketing Analytics, Palgrave Macmillan, vol. 6(4), pages 127-137, December.
    13. Mason, Charlotte H. & Milne, George R., 1994. "An approach for identifying cannibalization within product line extensions and multi-brand strategies," Journal of Business Research, Elsevier, vol. 31(2-3), pages 163-170.
    14. Becerril, Javier & Abdulai, Awudu, 2010. "The Impact of Improved Maize Varieties on Poverty in Mexico: A Propensity Score-Matching Approach," World Development, Elsevier, vol. 38(7), pages 1024-1035, July.
    15. Evanschitzky, Heiner & Malhotra, Neeru & Wangenheim, Florian v. & Lemon, Katherine N., 2017. "Antecedents of peripheral services cross-buying behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 218-224.
    16. Appel, Gil & Libai, Barak & Muller, Eitan & Shachar, Ron, 2020. "On the monetization of mobile apps," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 93-107.
    17. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    18. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    19. Reinartz, Werner & Thomas, Jacquelyn S. & Bascoul, Ganaël, 2008. "Investigating cross-buying and customer loyalty," Journal of Interactive Marketing, Elsevier, vol. 22(1), pages 5-20.
    20. David I. Levine & Gary Painter, 2003. "The Schooling Costs of Teenage Out-of-Wedlock Childbearing: Analysis with a Within-School Propensity-Score-Matching Estimator," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 884-900, November.
    21. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
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