Modelado de la efectividad en el e-mail marketing – Una aproximación basada en la teoría de jerarquía de efectos

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Publicado 13-01-2021
Ángel José Lorente Páramo
Ángel Hernández García
Julián Chaparro Peláez

Resumen

Pese a la importancia y difusión del e-mail marketing, la mejora de su efectividad continúa siendo una prioridad para la mayoría de anunciantes dado su potencial para la generación de ingresos. Sin embargo, el estudio del e-mail marketing ha sido en gran parte ignorado por la comunidad científica. En concreto, la ausencia de enfoques holísticos y marcos conceptuales de estudio impiden a las compañías mejorar la planificación y ejecución de estrategias de e-mail marketing. Este estudio responde a este problema mediante la propuesta de un modelo general de efectividad de e-mail marketing basado en la teoría de jerarquía de efectos. Así, cada una de las fases del modelo AIDA (Atención, Interés, Deseo, Acción) se vincula a las diversas etapas del proceso secuencial experimentado por los consumidores en su interacción con los correos electrónicos promocionales. Esto permite identificar diferentes métricas parciales de efectividad asociadas a las etapas cognitiva, afectiva y conativa, que a su vez pueden ser operacionalizadas a través de tasas habitualmente utilizadas por la industria (apertura, clic, retención y conversión). En concreto, la etapa de atención queda vinculada a la efectividad de apertura, la etapa de interés a la efectividad de clic y de retención de suscriptores, y la etapa de acción a la efectividad de conversión. El modelo no asocia ninguna métrica a la etapa de deseo dado que ésta ocurre habitualmente fuera del proceso del e-mail marketing. El estudio incluye un ejemplo de la adecuación del modelo conceptual a partir de datos y resultados de estudios previos.

Cómo citar

Lorente Páramo, Ángel J., Hernández García, Ángel, & Chaparro Peláez, J. (2021). Modelado de la efectividad en el e-mail marketing – Una aproximación basada en la teoría de jerarquía de efectos. Cuadernos De Gestión, 21(1), 19–27. https://doi.org/10.5295/cdg.191094ah
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Keywords

Marketing Digital, E-mail Marketing, Correo Electrónico, Jerarquía de Efectos, MarketingInteractivo, Efectividad, AIDA

References
AMA, Deloitte and Duke University, 2017. The CMO Survey. Available at: https://cmosurvey.org/wp-content/uploads/sites/15/2017/08/The_CMO_Survey-Highlights_and_Insights-Aug-2017.pdf (Accessed: 22 January 2018).
Andersson, M., Fredriksson, M. and Berndt, A., 2014. Open or delete: decision-makers attitudes towards e-mail marketing messages. Advances in Social Sciences Research Journal, 1(3), 133-144. doi: 10.14738/assrj.13.201.
Arnold, J., 2008. Email marketing for dummies. 2nd ed. Hoboken, NJ: Wiley Publishing, Inc.
Ashcroft, L. and Hoey, C., 2001. PR, marketing and the Internet: implications for information professionals. Library Management. MCB UP Ltd, 22(1/2), 68-74. doi: 10.1108/01435120110358952.
Balakrishnan, R. and Parekh, R., 2015. Learning to predict subject-line opens for large-scale email marketing. Proceedings of the 2014 IEEE International Conference on Big Data, IEEE Big Data 2014. Washington, DC: IEEE, 57-584. doi: 10.1109/BigData.2014.7004277.
Barnham, C., 2008. Instantiation - Reframing brand communication. International Journal of Market Research, 50(2), 203-220. doi: 10.1177/147078530805000205.
Barry, T.E. and Howard, D.J., 1990. A review and critique of the hierarchy of effects in advertising. International Journal of Advertising, 9(2), 121-135. doi: 10.1080/02650487.1990.11107138.
Bauman, A., Bowles, H.R., Huhman, M., Heitzler, C.D., Owen, N., Smith, B.J. and Reger-Nash, B., 2008. Testing a Hierarchy-of-Effects Model. Pathways from Awareness to Outcomes in the VERB Campaign 2002-2003. American Journal of Preventive Medicine. Elsevier, 34(6 SUPPL.), S249-S256. doi: 10.1016/j.amepre.2008.03.015.
Bawm, Z.L. and Nath, R.P.D., 2014. A Conceptual Model for effective email marketing. in 2014 17th International Conference on Computer and Information Technology (ICCIT). Dhaka: IEEE, 250-256. doi: 10.1109/ICCITechn.2014.7073103.
Bonfrer, A. and Drèze, X., 2009. Real-Time Evaluation of E-mail Campaign Performance. Marketing Science, 28(2), 251-263. doi: 10.1287/mksc.1080.0393.
Bruner, G.C. and Kumar, A., 2000. Web commercials and advertising hierarchy-of-effects. Journal of Advertising Research, 40(1-2), 35-42. doi: 10.2501/JAR-40-1-2-35-42.
Candent CG, 2017. 2017 Marketing Spend Study. Available at: http://cadentcg.com/wp-content/uploads/2017-Marketing-Spending-Study.pdf (Accessed: 22 January 2018).
Cases, A.S., Fournier, C., Dubois, P.L. and Tanner, J.F., 2010. Web Site spill over to email campaigns: The role of privacy, trust and shoppers’ attitudes. Journal of Business Research, 63(9-10), 993-999. doi: 10.1016/j.jbusres.2009.02.028.
Cramphorn, S., 2006. How to use advertising to build brands-In search of the philosopher’s stone. International Journal of Market Research, 48(3), 255-276. doi: 10.1177/147078530604800303.
Diehl, D., and Terlutter, R., 2003. The Role of Lifestyle and Personality in Explaining Attitude to the Ad. In: Flemming Hansen, Lars Bech Christensen (eds), Branding and Advertising, 306-331. Copenhagen: Copenhagen Business School Press.
eMarketer, 2017. Email Marketing Benchmarks 2017. Available at: https://www.emarketer.com/Report/Email-Marketing-Benchmarks-2017-Metrics-Steady-Data-Creates-Better-Context-Relevance/2002096 (Accessed: 4 June 2018).
Florès, L., 2014. How to Measure Digital Marketing. 1st ed. London: Palgrave Macmillan UK. doi: 10.1057/9781137340696.
Gartner, 2017. Market Guide for Email Marketing. Available at: https://www.gartner.com/doc/3621346/market-guide-email-marketing (Accessed: 3 February 2018).
GetResponse, 2018. Email Marketing Benchmarks. Available at: https://www.getresponse.com/resources/reports/email-marketing-benchmarks.html (Accessed: 3 February 2018).
Ghirvu, A.I., 2013. The AIDA model for Advergames. USV Annals of Economics and Public Administration, 13(1), 90-98.
Goodrich, K., 2011. Anarchy of effects? Exploring attention to online advertising and multiple outcomes. Psychology and Marketing, 28(4), 417-440. doi: 10.1002/mar.20371.
Gopal, R.D., Tripathi, A.K. and Walter, Z.D., 2006. Economics of first-contact email advertising. Decision Support Systems, 42(3), 1366-1382. doi: 10.1016/j.dss.2005.11.004.
Hassan, S., Zaleha, S., Nadzim, A. and Shiratuddin, N., 2015. Strategic Use of Social Media for Small Business Based on the AIDA Model. Procedia - Social and Behavioral Sciences, 172, 262-269. doi: 10.1016/j.sbspro.2015.01.363.
Huey, B., 1999. Advertisings Double Helix: A Proposed New Process Model. Journal of Advertising Research, 39(May), 43-51.
Jordan, P., Mahdian, M., Vassilvitskii, S. and Vee, E., 2011. The multiple attribution problem in pay-per-conversion advertising. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Berlin Heidelberg, 31-43. doi: 10.1007/978-3-642-24829-0_5.
Kahneman, D., 1973. Attention and effort. 1st ed. Englewood Cliffs, NJ: Prentice Hall.
Kojima, T., Kimura, T., Yamaji, M. and Amasaka, K., 2010. Proposal and Development of the Direct Mail Method PMCI-DM For Effectively Attracting Customers. International Journal of Management & Information Systems, 14(5), 15-22. doi: 10.19030/ijmis.v14i5.9.
Kotler, P. and Keller, K.L., 2012. Marketing Management. 14th edn. Boston, MA: Prentice Hall.
Lagrosen, S., 2005. Effects of the internet on the marketing communication of service companies. Journal of Services Marketing, 19(2), 63-69. doi: 10.1108/08876040510591376.
Lavidge, R.J. and Steiner, G.A., 1961. A Model for Predictive Measurements of Advertising Effectiveness. Journal of Marketing, 25(6), 59. doi: 10.2307/1248516.
Lim, K.H., Lim, E.-P., Jiang, B. and Achananuparp, P., 2016. Using Online Controlled Experiments to Examine Authority Effects on User Behavior in Email Campaigns. in Proceedings of the 27th ACM Conference on Hypertext and Social Media. Halifax: ACM, 255-260. doi: 10.1145/2914586.2914619.
Lin, Y.-S. and Huang, J.-Y., 2006. Internet blogs as a tourism marketing medium: A case study. Journal of Business Research, 59(10-11), 1201-1205. doi: 10.1016/j.jbusres.2005.11.005.
Lukka, V. and James, P.T.J., 2014. Attitudes toward Facebook advertising. Journal of Management and Marketing Research, 14, 1-26.
Maclnnis, D.J. and Jaworski, B.J., 1989. Information Processing from Advertisements: Toward an Integrative Framework. Journal of Marketing, 1-23. doi: 10.2307/1251376.
Martí Parreño, J., Cabrera García-Ochoa, Y. and Aldás Manzano, J., 2013. La publicidad actual: retos y oportunidades. Pensar la Publicidad. Revista Internacional de Investigaciones Publicitarias, 6(2), 327-343. doi: 10.5209/rev_PEPU.2012.v6.n2.41219.
Martin, B., Van Durme, J., Raulas, M. and Merisavo, M., 2003. Email advertising: exploratory insights from Finland. Journal of Advertising Research, 43(3), 293-300. doi: 10.1017/S0021849903030265.
McGuire, W.J., 1978. An information-processing model of advertising effectiveness. in Davis, H. L. and Silk, A. J. (eds) Behavioral and Management Science in Marketing. New York: Ronald Press, 156-180.
Merriam-Webster, 2011. Dictionary.
Micheaux, A.L., 2011. Managing e-mail Advertising Frequency from the Consumer Perspective. Journal of Advertising, 40(4), 45-66. doi: 10.2753/JOA0091-3367400404.
Mihart, C., 2012. Modelling the Influence of Integrated Marketing Communication on Consumer Behaviour: An Approach based on Hierarchy of Effects Concept. Procedia - Social and Behavioral Sciences, 62, 975-980. doi: 10.1016/j.sbspro.2012.09.166.
Moriarty, S., 1983. Beyond the Hierarchy of Effects: A Conceptual Framework. Current Issues and Research in Advertising. Taylor & Francis Group, 6(1), 45-55.
Moriarty, S., Mitchell, N.D., Wells, W.D., Crawford, R., Brennan, L. and Spence-Stone, R., 2012. Advertising & IMC: Principles and practice. Boston, MA: Prentice Hall.
Mullen, J. and Daniels, D., 2011. Email marketing: an hour a day. 1st ed. Indianapolis, IN: John Wiley & Sons.
Petty, R.E. and Cacioppo, J.T., 1986. The elaboration likelihood model of persuasion. Advances in experimental social psychology, 19, 123-205. doi: 10.1007/978-1-4612-4964-1_1.
Petty, R.E., Cacioppo, J.T. and Goldman, R., 1981. Personal Involvement as a Determinant of Argument-Based Persuasion. Journal of Personality and Social Psychology, 41(5), 847-855.
Petty, R.E., Cacioppo, J.T. and Schumann, D., 1983. Central and Peripheral Routes to Advertising Effectiveness: The Moderating Role of The Moderating Role of Involvement. Journal of Consumer Research, 10(2), 135-146. doi: 10.1086/208954.
Rehman, F.U., Javed, F., Nawaz, T., Ahmed, I. and Hyder, S., 2014a. Some Insights in the Historical Prospective of Hierarchy of Effects Model: A Short Review. Information Management and Business Review, 6(6), 301-308.
Rehman, F.U., Nawaz, T., Ilyas, M. and Hyder, S., 2014b. A Comparative Analysis of Mobile and Email Marketing Using AIDA Model. Journal of Basic and Applied Scientific Research, 4(6), 38-49.
Reimers, V., Chao, C-W., Gorman, S., 2016. Permission email marketing and its influence on online shopping. Asia Pacific Journal of Marketing and Logistics, 28(2), 308-322. doi: 10.1108/APJML-03-2015-0037.
Rettie, R. and Chittenden, L., 2003. Email Marketing: Success Factors. Kingston Business School - Occasional Paper Series.
Sahni, N.S., Wheeler, S.C. and Chintagunta, P., 2018. Personalization in Email Marketing: The Role of Non-Informative Advertising Content. Marketing Science, 37(2), 236-258. doi: 10.1287/mksc.2017.1066.
Scholten, M., 1996. Lost and found: The information-processing model of advertising effectiveness. Journal of Business Research, 37(2), 97-104. doi: 10.1016/0148-2963(96)00058-6.
Sigurdsson, V., Menon, R.G.V., Sigurdarson, J.P., Kristjansson, J.S. and Foxall, G.R., 2013. A test of the behavioral perspective model in the context of an e-mail marketing experiment. The Psychological Record, 63(2), 295-308. doi: 10.11133/j.tpr.2013.63.2.005.
Sigurdsson, V., Hinriksson, H., and Menon, R.G.V., 2015. Operant Behavioral Economics for E-mail Marketing: An Experiment Based on the Behavioral Perspective Model Testing the Effectiveness of Motivational Operation, Utilitarian and Informational Stimuli. Managerial and Decision Economics, 37(4-5), 337-344. doi:10.1002/mde.2725.
Smart, K. and Cappel, J., 2003. Assessing the response to and success of email marketing promotions. Issues in Information Systems, 4(1), 309-315.
Smith, R.E., Chen, J. and Yang, X., 2008. The Impact of Advertising Creativity on the Hierarchy of Effects. Journal of Advertising, 37(4), 47-61. doi: 10.2753/JOA0091-3367370404.
Solomon, M., Bamossy, G., Askegaard, S. and Hogg, M., 2013. Consumer behaviour: a European perspective. 5th ed. Harlow: Pearson.
Solomon, M.R. and Rabolt, N.J., 2009. Consumer behavior: in fashion. 2nd ed. Boston, MA: Prentice Hall.
Strong, E.K.J., 1925. Theories of selling. Journal of Applied Psychology, 9(1), 75-86. doi: 10.1037/h0070123.
Su, K.W., Huang, P.H., Chen, P.H. and Li, Y.T., 2016. The impact of formats and interactive modes on the effectiveness of mobile advertisements. Journal of Ambient Intelligence and Humanized Computing. Springer Berlin Heidelberg, 7(6), 817-827. doi: 10.1007/s12652-016-0343-x.
Theerthaana, P. and Sharad, S., 2014. A Study to Improve the Response in Email Campaigning by Comparing Data Mining Segmentation Approaches in Aditi Technologies. International journal of management and business research, 4(4), 273-293.
Vakratsas, D., and Ambler, T., 1999. How Advertising Works: What Do We Really Know? Journal of Marketing, 63(1), 26-43. doi: 10.2307/1251999
White, T.B., Zahay, D.L., Thorbjornsen, H. and Shavitt, S., 2008. Getting too personal: Reactance to highly personalized email solicitations. Marketing Letters. Springer US, 19(1), 39-50. doi: 10.1007/s11002-007-9027-9.
Wijaya, B.S., 2015. The Development of Hierarchy of Effects Model in Advertising. International Research Journal of Business Studies, 5(1), 73-85. doi: 10.21632/irjbs.5.1.73-85.
Wilson, E.V., Hall-Phillips, A. and Djamasbi, S., 2015. Cognitive predictors of consumers intention to comply with social marketing email appeals. Computers in Human Behavior, 52, 307-314. doi: 10.1016/j.chb.2015.06.014.
Wood, N.T. and Burkhalter, J.N., 2014. Tweet this, not that: A comparison between brand promotions in microblogging environments using celebrity and company-generated tweets. Journal of Marketing Communications. Routledge, 20(1-2), 129-146. doi: 10.1080/13527266.2013.797784.
Wu, J., Li, K.J. and Liu, J.S., 2018. Bayesian Inference for Assessing Effects of Email Marketing Campaigns. Journal of Business & Economic Statistics, 36(2), 253-266. doi: 10.1080/07350015.2016.1141096.
Yoo, C.Y., Kim, K. and Stout, P.A., 2004. Assessing the Effects of Animation in Online Banner Advertising: Hierarchy of Effects Model. Journal of Interactive Advertising, 4(2), 49-60. doi: 10.1080/15252019.2004.10722087.
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