Innovation of shopping experience based on smartphone behavior in purchasing process

Authors:
R. Bacik1, L. Kakalejcik2, B. Gavurova2
1. University of Prešov in Prešov (Prešov, Slovak Republic)
2. Technical University of Košice (Košice, Slovak Republic)
Pages:
99 - 111
Language:
English
Cite as:


Annotation

The main aim of the study is to analyze the use of smartphones by customers in the purchasing process and provide recommendations for innovation in shopping experience. In order to analyze interdependencies by defining the basic attributes of user clusters and their comparisons, data obtained from a consumer survey conducted by Google - Consumer Barometer was used. Factor analysis and k-means cluster analysis was executed in order to analyze the data and divide users into homogenous groups of users. By executing so, we have identified spatial correlations as a side product of our analysis. Based on the results it was possible to identify the most popular activities in the pre-purchasing stage - finding ideas, getting a store location, finding where to buy the product. The results pointed out to 2 groups of active smartphone users in terms of purchase, and 2 more conservative clusters – mostly containing users from European countries. The results of our study will help e-commerce subjects to better understand the omnichannel behavior of users who are increasingly using mobile devices - smartphones - in the purchasing process.


Keywords
e-commerce, mobile devices, smartphone, smartphone adoption, mobile marketing


Links
  1. Alhlou, F., Asif, S., & Fettman, E. (2016). Google Analytics Breakthrough: From Zero to Business Impact. John Wiley & Sons.
  2. Bucko, J., Kakalejčík, L., & Nastišin, Ľ. (2015, September). Use of smartphones during purchasing process. In Central European Conference in Finance and Economics (CEFE2015), Technical University of Košice, 91-97.
  3. Consumer Barometer (2017a). Trended data. www.consumerbarometer.com. Retrieved from https://www.consumerbarometer.com/en/trending/?countryCode=SK&category=TRN-NOFILTER-ALL. 
  4. Consumer Barometer (2017b). Methodology. www.consumerbarometer.com. Retrieved from:https://www.consumerbarometer.com/en/about/. 
  5. DELOITTE (2015). 2015 Global Mobile Consumer Survey: US Edition The rise of the always-connected consumer. www2.deloitte.com. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/us/Documents/technology-media-telecommunications/us-tmt-global-mobile-executive-summary-2015.pdf. 
  6. DIGITASLBI (2015). Connected Commerce. www.digitaslbi.com. Retrieved from http://www.digitaslbi.com/Global/ConnectedCommerce2015-Deck-FINAL.pdf. 
  7. Dorman, A.J. (2013). Omni-Channel Retail and the New Age Consumer: An Empirical Analysis of Direct-to-Consumer Channel Interaction in the Retail Industry (senior thesis). Retrieved from Claremont: Claremont McKenna College.
  8. Edelman, D.C., & Singer, M. (2016). Competing on Customer Journeys. Measuring Marketing Insights: Turning Data into Action. www.google.com. Retrieved from https://www.google.com/analytics/resources/white-paper-hbr-measuring-marketing-insights-collection.html. 
  9. Einav, L., Levin, J., Popov, I., & Sundaresan, N. (2014). Growth, adoption, and use of mobile E-commerce. The American economic review, 104(5), 489-494. 
  10. Groß, M. (2015). Mobile shopping: a classification framework and literature review. International Journal of Retail & Distribution Management, 43(3), 221-241.
  11. Hagyari, P., Bacik, R., & Fedorko, R. (2016). Analysis of the key factors of reputation management in conditions of city marketing. Polish Journal of Management Studies, 13(1), 69-80.
  12. Halligan, B., & Shah, D. (2014). Inbound Marketing: Get found using Google, Social Media and Blogs. New Jersey: John Wiley & Sons. 
  13. Holmes, A., Byrne, A., & Rowley, J. (2013). Mobile shopping behaviour: insights into attitudes, shopping process involvement and location. International Journal of Retail & Distribution Management, 42(1), 25-39.
  14. Juaneda-Ayensa, E., Mosquera, A., & Murillo, Y. S. (2016). Omnichannel customer behavior: key drivers of technology acceptance and use and their effects on purchase intention. Frontiers in psychology, 7, 1-11. 
  15. Korchagin, P., Korneeva, E., & Nikitina, N. (2015). Factors that Influence the Effectiveness of Russian Telecommunication Companies. Economics & Sociology, 8(3), 119-130.
  16. Kráľ, P., Kanderová, M., Kaščáková, A., Nedelová, G., & Valenčáková, V. (2009). Viacrozmerné štatistické metódy so zameraním na riešenie problémov ekonomickej praxe. Banská Bystrica: Ekonomická fakulta UMB. [In Slovak]. 
  17. Lazaris, C., Vrechopoulos, A. P., Doukidis, G. I., & Fraidaki, A. (2015). Mobile Apps for Omnichannel Retailing: Revealing the Emerging Showroom Phenomenon. In MCIS.
  18. Olivier, X., & Treblanche, N. S. (2016). An investigation into the antecedents and outcomes of the m-shopping experience. The Business and Management Review, 7(5), 263-267. 
  19. Palová, D., & Vejačka, M. (2015). FASTER Platform – an Online Tool for EU Accountants Education. MIPRO 2015, Rijeka: Croatian Society for Information and Communication Technology, Electronics and Microelectronics, 838-843. 
  20. Peltola, S., Vainio, H., & Nieminen, M. (2015, August). Key factors in developing omnichannel customer experience with finnish retailers. In International Conference on HCI in Business (pp. 335-346). Springer, Cham.
  21. Piotrowicz, W., & Cuthbertson, R. (2014). Introduction to the special issue information technology in retail: Toward omnichannel retailing. International Journal of Electronic Commerce, 18(4), 5-16.
  22. Pollák, F., Nastišin, Ľ., & Kakalejčík, L. (2015). Analysis of the Use of Smartphones during Purchasing Process for a Selected Group of Customers within Slovak Market Conditions. Management: Science and Education, 4(1), 77-79. 
  23. Poushter, J. (2016). Smartphone Ownership and Internet Usage Continues to Climb in Emerging Economies. www.pewglobal.org. Retrieved from http://www.pewglobal.org/files/2016/02/pew_research_center_global_technology_report_final_ february_22__2016.pdf. 
  24. Research New Zealand (2015). A Report on a Survey of New Zealanders’ Use of Smartphones and other Mobile Communication Devices 2015. www.researchnz.com. Retrieved from: http://www.researchnz.com /pdf/special%20reports/research%20new%20zealand%20special%20report%20-%20use%20of%20 smartphones.pdf. 
  25. Roberge, M. (2015). The Sales Acceleration Formula: Using Data, Technology, and Inbound Selling to go from $0 to $100 Million. Hoboken: John Wiley & Sons. 
  26. SALESFORCE (2014). 2014 Mobile Behavior Report: Combining mobile device tracking and consumer survey data to build a powerful mobile strategy. www.marketingcloud.com. Retrieved from https://www.marketingcloud.com/sites/exacttarget/files/deliverables/etmc-2014mobilebehaviorreport.pdf. 
  27. Scott, D.M. (2013). The New Rules of Marketing & PR: How to Use Social Media, Online Video, Mobile Applications, Blogs, News Releases & Viral Marketing to Reach Buyers Directly. New Jersey: John Wiley & Sons. 
  28. Shirkhodaie, M., & Rastgoo-deylami, M. (2016). Positive Word of Mouth Marketing: Explaining the Roles of Value Congruity and Brand Love. Journal of Competitiveness, 8(1), 19-37.
  29. Sterling, G. (2015). It’s Official: Google Says More Searches Now On Mobile than On Desktop. searchengineland.com.  Retrieved from: http://searchengineland.com/its-official-google-says-more-searches-now-on-mobile-than-on-desktop-220369. 
  30. Svatošová, V. (2013). Motivation of Online Buyer Behavior. Journal of Competitiveness, 5(3), 14-30.
  31. Thakur, R. (2016). Understanding customer engagement and loyalty: a case of mobile devices for shopping. Journal of Retailing and Consumer Services, 32, 151-163.
  32. Tossell, C., Kortum, P., Shepard, C., Rahmati, A., & Zhong, L. (2015). Exploring Smartphone Addiction: Insights from Long-Term Telemetric Behavioral Measures. International Journal of Interactive Mobile Technologies, 9(2), 37-43. 
  33. 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.
  34. Watrobski, J., Jankowski, J., & Ziemba, P. (2016). Multistage Performance Modelling in Digital Marketing Management. Economics & Sociology, 9(2), 101-119.