Which touchpoints matter most? A data-driven model for understanding student journey
DOI:
https://doi.org/10.18568/internext.v20i03.866Keywords:
Attribution Models, Consumer Behavior, Decision Making, Higher Education, MarketingAbstract
Objective: This research aimed to develop an attribution model using data from individual customer journeys to assess marketing channels and allocate value to various touchpoints throughout those journeys. Method: Through a comprehensive case study, the research developed and applied an attribution model using data from individual customer journeys to assess marketing channels and allocate value to various touchpoints throughout those journeys. The model analyzed 662,838 online and offline touchpoints across 185,631 customer journeys from a Brazilian higher education institution database. Main Results: The research on a student's journey shows that email, live chat, call center, sales, and inbound interactions were responsible for over 70% of enrollments. It also emphasizes the significance of customer-initiated contacts over firm-initiated contacts, with brand-owned touchpoints making up over 80% of registered contacts. Relevance / Originality: This article offers a dual contribution to the literature on student journey by evaluating the effectiveness of marketing touchpoints and exploring robust measurement methodologies. Theoretical / Methodological Contributions: The primary contribution of this research to the field lies in demonstrating that models based on data collected throughout the customer journey—and which account for all marketing touchpoints—achieve superior performance in identifying the specific contribution of each channel. Social contributions for management: This study offers three key managerial insights: it underscores the strategic value of integrating the customer journey into planning, the importance of mapping and monitoring touchpoints through data systems, and the need for continuous, iterative improvements to enhance conversion and customer experience.
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References
Abhishek, V., Fader, P., & Hosanagar, K. (2012). Media exposure through the funnel: a model of multi-stage attribution. SSRN. https://doi.org/10.2139/ssrn.2158421
Abreu, W. F., Araújo, R. S., & Lima, J. P. C. (2019). Políticas de financiamento e expansão no Ensino Superior do Brasil. Quaestio - Revista de Estudos em Educação, 21(2), 583-609. https://doi.org/10.22483/2177-5796.2019v21n2p583-609
Alblas, R. (2018). Attribution modeling customer journey online. Retrieved from https://research.tue.nl/en/studentTheses/attribution-modeling
Altomare, D., & Loris, D. (2016). Python Package “ChannelAttribution. Retrieved from https://pypi.org/project/ChannelAttribution/
Anderl, E., Becker, I., von Wangenheim, F., & Schumann, J. H. (2013). Putting attribution to work: a graph-based framework for attribution modeling in managerial practice. SSRN Electronic Journal, 1-36. https://doi.org/10.2139/ssrn.2343077
Anderl, E., Becker, I., von Wangenheim, F., & Schumann, J. H. (2016). Mapping the customer journey: Lessons learned from graph-based online attribution modeling. International Journal of Research in Marketing, 33(3), 457-474. https://doi.org/10.1016/j.ijresmar.2016.03.001
Archak, N., Mirrokni, V. S., & Muthukrishnan, S. (2010). Mining Advertiser-specific User Behavior Using Adfactors Categories and Subject Descriptors. In Proceedings of the 19th International Conference on World Wide Web (pp. 31-40). Association for Computing Machinery, Raleigh.
Bergamo, F., Ponchio, M., Zambaldi, F., Giuliani, A. C., & Spers, E. (2010). De prospect a aluno: fatores influenciadores da escolha de uma instituição de ensino superior. Base – Revista de Administração e Contabilidade da Unisinos, 7(3), 182-193. https://doi.org/10.4013/base.2010.73.01
Berman, R. (2018). Beyond the last touch: Attribution in online advertising. Marketing Science, 37(5), 771-792. https://doi.org/10.1287/mksc.2018.1104
Bolat, E., & O’Sullivan, H. (2017). Radicalising the marketing of higher education: learning from student-generated social media data. Journal of Marketing Management, 33(9-10), 742-763. https://doi.org/10.1080/0267257X.2017.1328458
Buhalis, D., & Volchek, K. (2021). Bridging marketing theory and big data analytics: The taxonomy of marketing attribution. International Journal of Information Management, 56, 102253. https://doi.org/10.1016/j.ijinfomgt.2020.102253
Chapman, D. W. (1981). A model of student college choice. The Journal of Higher Education, 52(5), 490. https://doi.org/10.2307/1981837
Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C, & Wirth, R. (2000). Crisp-Dm 1.0. CRISP-DM Consortium (Vol. 76).
Conselho Administrativo de Defesa Econômica (CADE) (2016). Atos de concentração no mercado de prestação de serviços de ensino superior. CADE. Retrieved from https://cdn.cade.gov.br/Portal/centrais-de-conteudo/publicacoes/estudos-economicos/cadernos-do-cade/atos-de-concentracao-no-mercado-de-prestacao-de-servicos-de-ensino-superior-2016.pdf
de Haan, E., Wiesel, T., & Pauwels, K. (2016). The effectiveness of different forms of online advertising for purchase conversion in a multiple-channel attribution framework. International Journal of Research in Marketing, 33(3), 491-507. https://doi.org/10.1016/j.ijresmar.2015.12.001
Følstad, A., & Kvale, K. (2018). Customer journeys: a systematic literature review. Journal of Service Theory and Practice, 28(2), 196-227. https://doi.org/10.1108/JSTP-11-2014-0261
Gai, L., Xu, C., & Pelton, L. E. (2016). A netnographic analysis of prospective international students’ decision-making process: implications for institutional branding of American universities in the emerging markets. Journal of Marketing for Higher Education, 26(2), 181-198. https://doi.org/10.1080/08841241.2016.1245233
Galan, M., Lawley, M., & Clements, M. (2015). Social media’s use in postgraduate students’ decision-making journey: an exploratory study. Journal of Marketing for Higher Education, 25(2), 287-312. https://doi.org/10.1080/08841241.2015.1083512
Hanson, K. H., & Litten, L. H. (1982). Mapping the road to academe: a review of research on women, men, and the college selection process. In P. J. Perun (Ed.), The undergraduate woman: Issues in education equity (pp. 73-98). Lexington Books.
Hossler, D., & Gallagher, K. S. (1987). Studying student college choice: a three-phase model and the implications for policymakers. College and University, 62(3), 207-221.
James-MacEachern, M. (2018). A comparative study of international recruitment–tensions and opportunities in institutional recruitment practice. Journal of Marketing for Higher Education, 28(2), 247-265. https://doi.org/10.1080/08841241.2018.1471014
James-MacEachern, M., & Yun, D. (2017). Exploring factors influencing international students’ decision to choose a higher education institution: A comparison between Chinese and other students. International Journal of Educational Management, 31(3), 343-363. https://doi.org/10.1108/IJEM-11-2015-0158
Kakalejč, L., Bucko, J., Resende, P., & Ferencova, M. (2018). Multichannel marketing attribution using Markov chains. Journal of Applied Management and Investments, 7(1), 49-60.
Kannan, P. K., & Kulkarni, G. (2022). The impact of Covid-19 on customer journeys: implications for interactive marketing. Journal of Research in Interactive Marketing, 16(1), 22-36. https://doi.org/10.1108/JRIM-03-2021-0078
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. https://doi.org/10.1016/j.ijresmar.2016.11.006
Kannan, P. K., Reinartz, W., & Verhoef, P. C. (2016). The path to purchase and attribution modeling: Introduction to special section. International Journal of Research in Marketing, 33(3), 449-456. https://doi.org/10.1016/j.ijresmar.2016.07.001
Kireyev, P., Pauwels, K., & Gupta, S. (2016). Do display ads influence search? Attribution and dynamics in online advertising. International Journal of Research in Marketing, 33(3), 475-490. https://doi.org/10.1016/j.ijresmar.2015.09.007
Kotler, P. (1976). A role for marketing in college admissions. In Applying marketing theory to college admissions (pp. 54-72). College Entrance Examination Board.
Kumar, A., Bezawada, R., Rishika, R., Janakiraman, R., & Kannan, P. K. (2018). The effects of firm generated content (FGC) in social media on customer behavior. Journal of Marketing, 53(9), 1689-1699.
Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96. https://doi.org/10.1509/jm.15.0420
Li, H., & Kannan, P. K. (2014). Attributing conversions in a multichannel online marketing environment: an empirical model and a field experiment. Journal of Marketing Research, 51(1), 40-56. https://doi.org/10.1509/jmr.13.0050
Li, N., Arava, S. K., Dong, C., Yan, Z., & Pani, A. (2018). Deep neural net with attention for multi-channel multi-touch attribution. AdKDD. https://doi.org/10.48550/arXiv.1809.02230
Mahboobi, S. H., Usta, M., & Bagheri, S. R. (2018). Coalition game theory in attribution modeling: Measuring what matters at scale. Journal of Advertising Research, 58(4), 414-422. https://doi.org/10.2501/JAR-2018-014
Maringe, F. (2006). University and course choice: Implications for positioning, recruitment and marketing. International Journal of Educational Management, 20(6), 466-479. https://doi.org/10.1108/09513540610683711
McColl-Kennedy, J. R., Zaki, M., Lemon, K. N., Urmetzer, F., & Neely, A. (2019). Gaining customer experience insights that matter. Journal of Service Research, 22(1), 8-26. https://doi.org/10.1177/1094670518812182
Nascimento, R. L. S., Cruz Junior, G. G., & Fagundes, R. A. A. (2018). Mineração de dados educacionais: um estudo sobre indicadores da educação em bases de dados do INEP. RENOTE, 16(1), 1-11. https://doi.org/10.22456/1679-1916.85989
Nichols, W. (2013). Advertising Analytics 2.0. Harvard Business Review, 91(3), 60-68.
Ordenes, F. V., Theodoulidis, B., Burton, J., Gruber, T., & Zaki, M. (2014). Analyzing customer experience feedback using text mining: a linguistics-based approach. Journal of Service Research, 17(3), 278-295. https://doi.org/10.1177/1094670514524625
Pattanayak, S., Pati, P. B., & Singh, T. (2022). Performance analysis of machine learning algorithms on multi-touch attribution model. In 3rd International Conference for Emerging Technology (pp. 1-7). IEEE, Belgaum. https://doi.org/10.1109/INCET54531.2022.9824865
Piurcosky, F. P., Calegário, C. L. L., Silva, G., Frogeri, R. F., & Portugal, N. S. (2019). Fusões e aquisições no mercado de ensino superior: uma revisão sistemática. Brazilian Journal of Development, 5(9), 15738-15751. https://doi.org/10.34117/bjdv5n9-146
Rosenbaum, M. S., Otalora, M. L., & Ramírez, G. C. (2017). How to create a realistic customer journey map. Business Horizons, 60(1), 143-150. https://doi.org/10.1016/j.bushor.2016.09.010
Schuhbauer, H., Brockmann, P., & Mustafayev, T. (2020). Mapping the students’ journey to develop student-centered tools. In IEEE Global Engineering Education Conference (pp. 56-60). https://doi.org/10.1109/EDUCON45650.2020.9125139
Senhoras, E. M., Takeuchi, K. P., & Takeuchi, K. P. (2012). A análise estrutural do ensino superior privado sob perspectiva. In Simpósio de Excelência em Gestão e Tecnologia (pp. 1-12). Universidade Federal Fluminense.
Shao, X., & Li, L. (2011). Data-driven multi-touch attribution models. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 258-264). Association for Computing Machinery. https://doi.org/10.1145/2020408.2020453
Shearer, C., Watson, H. J., Grecich, D. G., Moss, L., Adelman, S., Hammer, K., & Herdlein, S. A. (2000). The CRISP-DM model: the new blueprint for data mining. Journal of Data Warehousing, 5(4), 13-22. Retrieved from https://www.scirp.org/(S(vtj3fa45qm1ean45vvffcz55))/reference/ReferencesPapers.aspx?ReferenceID=1592780
Tankovska, H. (2020). Share of social media users in the United States who believe they will use select social media more if confined at home due to the coronavirus as of March 2020. Statista. Retrieved from https://www.statista.com/statistics/1106343/social-usage-increase-due-to-coronavirus-home-usa/
Tueanrat, Y., Papagiannidis, S., & Alamanos, E. (2021). Going on a journey: A review of the customer journey literature. Journal of Business Research, 125, 336-353. https://doi.org/10.1016/j.jbusres.2020.12.028
Vescovi, P. V. S. (2020). Análise preditiva na detecção de evasão de alunos no ensino superior privado brasileiro: abordagem de algoritmos de aprendizado de máquina, com base nas perspectivas acadêmicas, financeiras, geográficas e socioeconômicas [dissertation, Fundação Getúlio Vargas]. Retrieved from https://bibliotecadigital.fgv.br/dspace/handle/10438/28907
Wiesel, T., Pauwels, K., & Arts, J. (2010). Marketing’s profit impact: Quantifying online and off-line funnel progression. Marketing Science, 30(4), 604-611. https://doi.org/10.1287/mksc.1100.0612
Yin, R. K. (2018). Case study research and applications: Design and methods. SAGE Publications.
Zhao, K., Mahboobi, S. H., & Bagheri, S. R. (2019). Revenue-based attribution modeling for online advertising. International Journal of Market Research, 61(2), 195-209. https://doi.org/10.1177/1470785318774447
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