Abstract

The objective of the article is to enrich knowledge about marketing personalization of the optimization of marketing campaigns. In the article, differences in how customers perceive individual tools of marketing communication in the online environment were evaluated. When creating campaigns, only the customer’s view of the product (segmentation) is often taken into account. This article recommends some bases depending on campaign optimization variables. From a methodological point of view, a homogeneity analysis was used to analyse the hypotheses that assessed the impact of instruments, as well as the impact depending on identification variables, such as gender, education and social status. Based on the outputs these facts were analysed. A questionnaire was used. (Data collection took place in early 2017). Our research has an application character and, therefore, one of the most attractive findings is in the area of practice, where focusing marketing campaigns on sales support in visual forms was recommended. In the vast majority of cases, the maker of marketing activities focuses on the construction of segments based on assumptions in strong association with the product. We optimize this approach because different customer groups respond differently to different tools and forms of tools and to their mutual combinations. Limitations of applications can be determined depending on the nature of the base file and therefore for countries with a distinctly different structure, the outputs do not have to be valid. Applying the lessons learned from the field of diversification of the impact of individual instruments in the early stages of campaigns can be recommended or in campaigns where there is an explicit problem with the exact determination of customer segments and the optimal tools    

Keywords: marketing tools, customer personalization, personalization of marketing communication, optimization of marketing campaigns, Slovak market.

JEL Classification: M30, M37, М31 .

Cite as: Gavurova, B., Bacik, R., Fedorko, R., & Rigelsky, M. (2018). Analytical view of online marketing tools in the dimension of marketing campaigns’ personalization in Slovakia. Marketing and Management of Innovations, 2, 186-200. https://doi.org/10.21272/mmi.2018.2-15

This work is licensed under a Creative Commons Attribution 4.0 International License

References

1. Bednarčík, Z. (2013). The importance of strategic marketing management in companies for an increase in theirs competitiveness. In: 16th International Colloquium on Regional Sciences. Brno: Masarykova univerzita, pp. 252-258.
2. Fernandez-Lanvin, D., Deandres-Suarez, J., Gonzales-Rodriguez, M., Pariente-Martinez, B. (2018). The dimension of age and gender as user model demographic factors for automatic personalization in e-commerce sites. Computer Standards & Interfaces.
3. Foret, M. (2008). Marketing research – we know our customers (Marketingový prúzkum – poznávame svoje zákazníky). Brno: Computer Press. 124 p. 1st Edition.
4. Grancay, M., Grancay, N., Drutarovska, J., Mura, L. (2015). Gravity model of  trade of the Czech and Slovak Republics 1995-2012: How have determinants of trade changed. Politicka  Ekonomie, 63 (6),  pp. 759-777.
5. Janouch, V. (2010). Internet Marketing: Enforce the web and social networks. (Internetový marketing: prosaďte se na webu a sociálních sítích). Praha: Computer Press. 304 p. 1th Edition.
6. Kim, D., Ammeter, A. P. (2018). Shifts in online consumer behavior: A preliminary investigation of the net generation. Journal of Theoretical and Applied Electronic Commerce Research, 13(1), pp. 1-25.
7. Kotler, P., Armstrong, G. (2007). Marketing. Praha: Grada Publishing. 856 p. 6th Edition
8. Kotler, P., Keller, L. K. (2012). Marketing management. New Jersey: Pearson Education. 816 p. 14th edition.
9. Kwon, S., Ha. S., Kowal, Ch. (2017). How online self-customization creates identification: Antecedents and consequences of consumer-customized product identification and the role of product involvement. Computers in Human Behavior, 75, pp. 1-13.
10. Lee, E. J., Park, J. K. (2009). Online service personalization for apparel shopping. Journal of Retailing and Consumer Services, 16(2), pp. 83-91.
11. Li, C., Liu, J. (2017). A name alone is not enough: A reexamination of web-based personalization effect. Computers in Human Behavior, 72, pp. 132-139.
12. Matic, A., Pielot, M., Oliver, N. (2017). OMG! How did it know that?” Reactions to Highly-Personalized Ads. UMAP 2017 – Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, pp. 41-46.
13. McDarby, F., O´hora, D., Ośhea, D., Byrne, M. (2018). Aking the sweetness out of the “Share a Coke’ marketing campaign: the influence of personalized labelling on elementary school children’s bottled drink choices. Pediatric obesity, 13(1), pp. 63-69.
14. Mura, L., Machová, R., Tóth, Z. (2015). Evaluation of innovation performance of the business networks. Hradec Economic Days,  5(5), pp. 41-47.
15. Porter, M. (1985). Competitive advantage. The Academy of Management Review, 10(4), pp. 873-875.
16. Štefko, R., Fedorko, R., Bačík, R. (2014). The Significance of Internet Marketing Tools in Terms of Building a Positive Image of an Higher Education Institution. In: Crafting global competitive economies: 2020 Vision strategic planning & smart implementation, Vols. I-IV, pp: 1764-1772.
17. Tran, T. P. (2017). Personalized ads on Facebook: An effective marketing tool for online marketers. Journal of Retailing and Consumer Services, 39, pp. 230-242.
18. Xu, H., ZOU, X., Wang, H. (2006). Consumers attitudes of e-commerce in china, Consumers attitudes of e-commerce in china, 7(2), pp. 201-207.
19. Xiao, Bo and Benbasat, Izak. (2011). Product-Related Deception in E-Commerce: A Theoretical Perspective, In: MIS Quarterly, 35: 1, pp.169-195.
20. Makris C., Siaterlis K. and Vikatos P. (2017). Personalized Hotlink Assignment using Social Networks. In Proceedings of the 13th International Conference on Web Information Systems and Technologies – Volume 1: WEBIST, pp. 71-79.
21. Sahni, N. S., Wheeler, S. Ch., Chintagunta, P. K., (2016). Personalization in Email Marketing: The Role of Non-Informative Advertising Content. Stanford University Graduate School of Business Research Paper No. 16-14. Available at SSRN: https://ssrn.com/abstract=2725251 or http://dx.doi.org/10.2139/ssrn.2725251.
22. Schwarzl, S., & Grabowska, M. (2015). Online marketing strategies: the future is here. Journal of International Studies, 8(2), 187-196.
23. Haim, M., Graefe, A., Brosius H., (2018). Burst of the Filter Bubble?, Effects of personalization on the diversity of Google News, In: Digital Journalism, 6:3, pp. 330-343.
24. Wątróbski, J., Jankowski, J., Ziemba, P. (2016), Multistage Performance Modelling in Digital Marketing Management, Economics and Sociology, 9(2), 101-125. DOI: 10.14254/2071-789X.2016/9-2/7