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Personalized mobile marketing strategies

  • Siliang Tong
  • Xueming Luo
  • Bo XuEmail author
CONCEPTUAL/THEORETICAL PAPER

Abstract

The prevalence of mobile usage data has provided unprecedented insights into customer hyper-context information and brings ample opportunities for practitioners to design more pertinent marketing strategies and timely targeted campaigns. Granular unstructured mobile data also stimulate new research frontiers. This paper integrates the traditional marketing mix model to develop a framework of personalized mobile marketing strategies. The framework incorporates personalization into the center of mobile product, mobile place, mobile price, mobile promotion, and mobile prediction. Extant studies in mobile marketing are reviewed under the proposed framework, and promising topics about personalized mobile marketing are discussed for future research.

Keywords

Mobile marketing Mobile personalization Mobile marketing mix Artificial intelligence 

Notes

References

  1. Adweek. (2018). Why Mobile and Consumers Are the Focal Points of This Year’s NewFronts. Retrieved July 2, 2018, from adweek.com website: https://www.adweek.com/digital/why-mobile-and-consumers-are-the-focal-points-of-this-years-newfronts/.
  2. Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34–49.CrossRefGoogle Scholar
  3. Andrews, M., Luo, X., Fang, Z., & Ghose, A. (2016). Mobile ad effectiveness: Hyper-contextual targeting with crowdedness. Marketing Science, 35(2), 218–233.CrossRefGoogle Scholar
  4. Arora, S., Hofstede, F., & Mahajan, V. (2017). The implications of offering free versions for the performance of paid Mobile apps. Journal of Marketing, 81(6), 62–78.CrossRefGoogle Scholar
  5. Balasubramanian, S., Peterson, R. A., & Jarvenpaa, S. L. (2002). Exploring the implications of M-commerce for markets and marketing. Journal of the Academy of Marketing Science, 30, 348–361.CrossRefGoogle Scholar
  6. Bart, Y., Stephen, A. T., & Sarvary, M. (2014). Which products are best suited to Mobile advertising? A field study of Mobile display advertising effects on consumer attitudes and intentions. Journal of Marketing Research, 51(3), 270–285.CrossRefGoogle Scholar
  7. Barwise, P., & Strong, C. (2002). Permission-based Mobile advertising. Journal of Interactive Marketing, 16(1), 14–24.CrossRefGoogle Scholar
  8. Bluecorona. (2018). 61 Mobile Marketing Statistics for 2018 and Beyond | Mobile Usage Statistics. Retrieved July 2, 2018, from bluecororna.com website: https://www.bluecorona.com/blog/mobile-marketing-statistics.
  9. Businessofapps. (2018). App Download and Usage Statistics - Business of Apps. Retrieved July 2, 2018, from businessofapps.com website: http://www.businessofapps.com/data/app-statistics/.
  10. BusinessWire. (2019). Global Mobile Marketing Market to Reach $183.5 Billion by 2024, with a CAGR of 23.4% - Analysis Segmented by Solution Type, Organization Size, End-user and Geography. Retrieved May 3, 2019, from businesswire.com website: https://www.businesswire.com/news/home/20190325005436/en/Global-Mobile-Marketing-Market-Reach-183.5-Billion.
  11. Castelo, N., & Thalmann, N. (2019). Robot or human? Consumer Perceptions of Human-Like Robots. Working Paper.Google Scholar
  12. Ciechanowski, L., Przegalinska, A., Magnuski, M., & Gloor, P. (2019). In the shades of the Uncanny Valley: An experimental study of human--Chatbot interaction. Future Generation Computer Systems, 92, 539–548.CrossRefGoogle Scholar
  13. Danaher, P. J., Smith, M. S., Ranasinghe, K. & Danaher, T. S. (2015). Where, when and how long: Factors that influence the redemption of mobile phone coupons. Journal of Marketing Research, 52, 710–725.Google Scholar
  14. De Haan, E., Kannan, P. K., Verhoef, P. C., & Wiesel, T. (2018). Device switching in online purchasing: Examining the strategic contingencies. Journal of Marketing, 82(5), 1–19.CrossRefGoogle Scholar
  15. Dickinger, A., & Kleijnen, M. (2008). Coupons going wireless: Determinants of consumer intentions to redeem mobile coupon. Journal of Interactive Marketing, 22(3), 23–39.Google Scholar
  16. Digital Trends. (2018). Streaming TV consumption more than doubles in 12 months. Retrieved May 3, 2019, from digitaltrends.com website: https://www.digitaltrends.com/home-theater/streaming-tv-consumption-doubles/.
  17. Digitalnewsdaily. (2018). Nielsen Catalina Solutions To Launch Tool To Measure In-Store Sales Based On Video Ads. Retrieved June 27, 2018, from mediapost.com website: https://www.mediapost.com/publications/article/321104/nielsen-catalina-solutions-to-launch-tool-to-measu.html.
  18. Dubé, J.-P., Fang, Z., Fong, N., & Luo, X. (2017). Competitive Price targeting with smartphone coupons. Marketing Science, 36(6), 944–975.CrossRefGoogle Scholar
  19. Economides, N., & Jeziorski, P. (2017). Mobile Money in Tanzania. Marketing Science, 36(6), 815–837.CrossRefGoogle Scholar
  20. Einav, L., Levin, J., Popov, I., & Sundaresan, N. (2014). Growth, adoption, and use of Mobile E-commerce. American Economic Review, 104(5), 489–494.CrossRefGoogle Scholar
  21. eMarketer. (2019). What’s Behind the Sudden Growth of TikTok? Retrieved May 3, 2019, from emarketer.com website: https://www.emarketer.com/content/what-s-behind-the-sudden-growth-of-tiktok.
  22. Fast Company. (2018). Why Nike ditched a proven winning strategy for the 2018 world cup. Retrieved May 6, 2019, from fastcompany.com website: https://www.fastcompany.com/90179193/why-nike-ditched-a-proven-winning-strategy-for-the-2018-world-cup.
  23. Fong, N. M., Fang, Z., & Luo, X. (2015). Geo-Conquesting: Competitive locational targeting of Mobile promotions. Journal of Marketing Research, 52(5), 726–735.CrossRefGoogle Scholar
  24. Fong, N., Zhang, Y., Luo, X., & Wang, X. (2019). Targeted promotions on an E-book platform: Crowding out, heterogeneity, and opportunity costs. Journal of Marketing Research, 56(2), 310–323.CrossRefGoogle Scholar
  25. Ghose, A., & Pil Han, S. (2011). An empirical analysis of user content generation and usage behavior on the Mobile internet. Management Science, 57(9), 1671–1691.CrossRefGoogle Scholar
  26. Ghose, A., & Pil Han, S. (2014). Estimating demand for Mobile applications in the new economy. Management Science, 60(6), 1470–1488.CrossRefGoogle Scholar
  27. Ghose, A., Goldfarb, A., & Han, S. P. (2013). How is the Mobile internet different? Search costs and local activities. Information Systems Research, 24(3), 613–631.CrossRefGoogle Scholar
  28. Ghose, A., Kwon, H. E., Lee, D., & Oh, W. (2019a). Seizing the commuting moment: Contextual targeting based on mobile transportation apps. Information Systems Research, 30(1), 154–174.CrossRefGoogle Scholar
  29. Ghose, A., Li, B., & Liu, S. (2019b). Mobile targeting using customer trajectory patterns. Management Science, Articles in Advance.Google Scholar
  30. Gill, M., Sridhar, S., & Grewal, R. (2017). Return on engagement initiatives: A study of a business-to-business Mobile app. Journal of Marketing, 81(4), 45–66.CrossRefGoogle Scholar
  31. Grewal, L., & Stephen, A. T. (2019). In Mobile we trust: The effects of Mobile versus nonmobile reviews on consumer purchase intentions. Journal of Marketing Research, 002224371983451.Google Scholar
  32. Grewal, D., Bart, Y., Spann, M., & Zubcsek, P. P. (2016). Mobile advertising: A framework and research agenda. Journal of Interactive Marketing, 34, 3–14.CrossRefGoogle Scholar
  33. Grewal, D., Roggeveen, A. L., & Nordfält, J. (2017). The future of retailing. Journal of Retailing, 93(1), 1–6.CrossRefGoogle Scholar
  34. Grewal, D., Ahlbom, C.-P., Beitelspacher, L., Noble, S. M., & Nordfält, J. (2018). In-store Mobile phone use and customer shopping behavior: Evidence from the field. Journal of Marketing, 82(4), 102–126.CrossRefGoogle Scholar
  35. Gurău, C., & Ranchhod, A. (2009). Consumer privacy issues in Mobile commerce: A comparative study of British, French and Romanian consumers. Journal of Consumer Marketing, 26(7), 496–507.CrossRefGoogle Scholar
  36. Harvard Business Review. (2017). Your Mobile Strategy Can’t Just Be About Phones. Retrieved May 4, 2019, from hbr.org website: https://hbr.org/2017/07/your-mobile-strategy-cant-just-be-about-phones.
  37. Ho, S. Y., & Lim, K. H. (2018). Nudging moods to induce unplanned purchases in imperfect Mobile personalization contexts. MIS Quarterly, 42(3), 757–778.CrossRefGoogle Scholar
  38. Hofacker, C. F., de Ruyter, K., Lurie, N. H., Manchanda, P., & Donaldson, J. (2016). Gamification and Mobile marketing effectiveness. Journal of Interactive Marketing, 34, 25–36.CrossRefGoogle Scholar
  39. Huang, M.-H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 109467051775245.CrossRefGoogle Scholar
  40. Hubspot. (2018). 12 Examples of Brands With Brilliant Omni-Channel Experiences. Retrieved May 4, 2019, from hubspot.com website: https://blog.hubspot.com/service/omni-channel-experience.
  41. Hui, S. K., Inman, J. J., Huang, Y., & Suher, J. (2013). The effect of in-store travel distance on unplanned spending: Applications to Mobile promotion strategies. Journal of Marketing, 77(2), 1–16.CrossRefGoogle Scholar
  42. Hui, S., Thornswood, L., Goehring, J., Andrews, M., & Pancras, J. (2016). Mobile promotions: A framework and research priorities. Journal of Interactive Marketing, 34, 15–24.CrossRefGoogle Scholar
  43. Investopedia. (2018). Mobile Advertising Definition. Retrieved June 22, 2018, from Investopedia website: https://www.investopedia.com/terms/m/mobile-advertising.asp.
  44. Kannan, P. K., & Li, H. “. A.”. (2017). Digital marketing: A framework, review and research agenda. International Journal of Research in Marketing, 34(1), 22–45.Google Scholar
  45. Kim, S. J., Wang, R. J. H., & Malthouse, E. C. (2015). The effects of adopting and using a Brand’s Mobile application on customers’ subsequent purchase behavior. Journal of Interactive Marketing, 31, 28–41.CrossRefGoogle Scholar
  46. Kübler, R., Pauwels, K., Yildirim, G., & Fandrich, T. (2018). App popularity: Where in the world are consumers Most sensitive to Price and user ratings? Journal of Marketing, 82(5), 20–44.CrossRefGoogle Scholar
  47. Kumar, V., Nim, N., & Sharma, A. (2018). Driving growth of Mwallets in emerging markets: A Retailer’s perspective. Journal of the Academy of Marketing Science, pp. 1–23.Google Scholar
  48. Lamberton, C., & Stephen, A. T. (2016). A thematic exploration of digital, social media, and Mobile marketing: Research evolution from 2000 to 2015 and an agenda for future inquiry. Journal of Marketing, 80(6), 146–172.CrossRefGoogle Scholar
  49. Leung, E., Paolacci, G., & Puntoni, S. (2018). Man versus machine: Resisting automation in identity-based consumer behavior. Journal of Marketing Research, 55(6), 818–831.CrossRefGoogle Scholar
  50. Li, C., Luo, X., Zhang, C., & Wang, X. (2017). Sunny, rainy, and cloudy with a chance of Mobile promotion effectiveness. Marketing Science, 36(5), 762–779.CrossRefGoogle Scholar
  51. Luo, X., Andrews, M., Fang, Z., & Phang, C. W. (2014). Mobile Targeting. Management Science, 60(7), 1738–1756.CrossRefGoogle Scholar
  52. McCarthy, E. (1960). Basic marketing, a managerial approach. Retrieved from http://www.worldcat.org/title/basic-marketing-a-managerial-approach/oclc/242332.
  53. Melumad, S., Inman, J. J., & Pham, M. T. (2019). Selectively emotional: How smartphone use changes user-generated content. Journal of Marketing Research, 56(2), 259–275.CrossRefGoogle Scholar
  54. Mobile Marketer. (2019). Spider-man swings by world landmarks in Snapchat’s AR lenses | Mobile Marketer. Retrieved July 2, 2019, from mobilemarketer.com website: https://www.mobilemarketer.com/news/spider-man-swings-by-world-landmarks-in-snapchats-ar-lenses/557946/.
  55. Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005). Intentions to use Mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330–346.CrossRefGoogle Scholar
  56. Provost, F., Martens, D., & Murray, A. (2015). Finding similar Mobile consumers with a privacy-friendly geosocial design. Information Systems Research, 26(2), 243–265.CrossRefGoogle Scholar
  57. Quartz. (2018). Nigeria’s World Cup kit has sold out - Nike. Retrieved May 6, 2019, from qz.com website: https://qz.com/africa/1294652/nigerias-world-cup-kit-has-sold-out-nike/.
  58. Ransbotham, S., Lurie, N. H., & Liu, H. (2019). Creation and consumption of Mobile word of mouth: How are Mobile reviews different? Marketing Science.Google Scholar
  59. Retaildive. (2018). Zara to Offer Mobile AR Experience in Stores. Retrieved June 27, 2018, from retaildive.com website: https://www.retaildive.com/news/zara-to-offer-mobile-ar-experience-in-stores/519286/.
  60. Shankar, V., & Balasubramanian, S. (2009). Mobile marketing: A synthesis and prognosis. Journal of Interactive Marketing, 23(2), 118–129.CrossRefGoogle Scholar
  61. Shankar, V., Venkatesh, A., Hofacker, C., & Naik, P. (2010). Mobile Marketing in the Retailing Environment: Current insights and future research avenues. Journal of Interactive Marketing, 24(2), 111–120.CrossRefGoogle Scholar
  62. Shankar, V., Kleijnen, M., Ramanathan, S., Rizley, R., Holland, S., & Morrissey, S. (2016). Mobile shopper marketing: Key issues, current insights, and future research avenues. Journal of Interactive Marketing, 34, 37–48.CrossRefGoogle Scholar
  63. Shen, H., Zhang, M., & Krishna, A. (2016). Computer interfaces and the “direct-touch” effect: Can iPads increase the choice of hedonic food? Journal of Marketing Research, 53(5), 745–758.CrossRefGoogle Scholar
  64. Spaid, B. I., & Flint, D. J. (2014). The meaning of shopping experiences augmented by Mobile internet devices. Journal of Marketing Theory and Practice, 22(1), 73–90.CrossRefGoogle Scholar
  65. Statista. (2018). Chart: Mobile E-commerce is up and Poised for Further Growth. Retrieved July 1, 2018, from statista.com website: https://www.statista.com/chart/13139/estimated-worldwide-mobile-e-commerce-sales/.
  66. Statista. (2019). Number of Mobile Phone Users Worldwide 2015–2020. Retrieved May 3, 2019, from statista.com website: https://www.statista.com/statistics/274774/forecast-of-mobile-phone-users-worldwide/.
  67. The Verge. (2019). Netflix tests a Mobile-only plan in select countries that costs $4. Retrieved May 4, 2019, from theverge.com website: https://www.theverge.com/2019/3/22/18277547/netflix-mobile-only-plan-countries-price.
  68. Themanifest. (2018). Mobile App Usage Statistics 2018. Retrieved July 2, 2018, from themanifest.com website: https://themanifest.com/app-development/mobile-app-usage-statistics-2018.
  69. Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Source Journal of Marketing, 68(1), 1–17 Retrieved from http://www.jstor.org/stable/30161971.CrossRefGoogle Scholar
  70. Vlachos, P. A., & Vrechopoulos, A. P. (2008). Determinants of behavioral intentions in the Mobile internet services market. Journal of Services Marketing, 22(4), 280–291.CrossRefGoogle Scholar
  71. Wang, R. J.-H., Malthouse, E. C., & Krishnamurthi, L. (2015). On the go: How Mobile shopping affects customer purchase behavior. Journal of Retailing, 91(2), 217–234.CrossRefGoogle Scholar
  72. Wang, Q., Li, B., & Singh, P. V. (2018). Copycats vs. original Mobile apps: A machine learning copycat-detection method and empirical analysis. Information Systems Research, 29(2), 273–291.CrossRefGoogle Scholar
  73. Wang, F., Zuo, L., Yang, Z., & Wu, Y. (2019). Mobile searching versus online searching: Differential effects of paid search keywords on direct and indirect sales. Journal of the Academy of Marketing Science.Google Scholar
  74. Xu, H., Teo, H. H., Tan, B. C. Y., & Agarwal, R. (2012). Effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: A study of location-based services. Information Systems Research, 23(4), 1342–1363.CrossRefGoogle Scholar
  75. Xu, J., Forman, C., Kim, J. B., & Van Ittersum, K. (2014). News media channels: Complements or substitutes? Evidence from Mobile phone usage. Journal of Marketing, 78(4), 97–112.CrossRefGoogle Scholar
  76. Xu, K., Chan, J., Ghose, A., & Han, S. P. (2017). Battle of the channels: The impact of tablets on digital commerce. Management Science, 63(5), 1469–1492.CrossRefGoogle Scholar
  77. Zinrelo. (2018). Tiered Loyalty Programs- What Makes the Sephora’s Loyalty Rewards Program Successful? Retrieved May 4, 2019, from zinrelo.com website: https://zinrelo.com/tiered-loyalty-programs-what-makes-the-sephoras-loyalty-rewards-program-successful.html.
  78. Zubcsek, P. P., Katona, Z., & Sarvary, M. (2017). Predicting Mobile advertising response using consumer colocation networks. Journal of Marketing, 81(4), 109–126.CrossRefGoogle Scholar

Copyright information

© Academy of Marketing Science 2019

Authors and Affiliations

  1. 1.Fox School of BusinessTemple UniversityPhiladelphiaUSA
  2. 2.Global Center for Big Data and Mobile Analytics, Fox School of BusinessTemple UniversityPhiladelphiaUSA
  3. 3.School of ManagementFudan UniversityShanghaiChina

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