Abstract
During the last decades, the internet has become an increasingly important channel for businesses to sell products and communicate with customers. Web analytics helps companies to understand customer behavior and optimizes processes to satisfy the customer needs but there is still room for improvement in real-time visualization in the context of business content. In this paper, we describe a graph-based visualization showing the entirety of the website activities at a glance. To increase the tangibility of customer behavior, the graph adapts to the website interactions in real time using smooth transitions from one state to another. Furthermore, we incorporate machine learning in our data integration process to deal with the dynamics of change of website content over time. Finally, we conduct an evaluation in the form of expert interviews revealing that our approach is suitable to optimize digitalized business processes, initiate marketing campaigns, increase the tangibility to the customer, and put a stronger focus on customer needs.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chitkara, B., Mahmood, S.: Importance of web analytics for the success of a startup business. In: Batra, U., Roy, N.R., Panda, B. (eds.) REDSET 2019. CCIS, vol. 1230, pp. 366–380. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-5830-6_31
Gupta, S., Leszkiewicz, A., Kumar, V., Bijmolt, T., Potapov, D.: Digital analytics: modeling for insights and new methods. J. Interact. Market. 51, 26–43 (2020)
Filvà, D.A., Forment, M.A., García-Peñalvo, F.J., Escudero, D.F., Casañ, M.J.: Clickstream for learning analytics to assess students’ behavior with Scratch. Future Gener. Comput. Syst. 93, 673–686 (2019)
Leitner, P., Maier, K., Ebner, M.: Web analytics as extension for a learning analytics dashboard of a massive open online platform. In: Ifenthaler, D., Gibson, D. (eds.) Adoption of Data Analytics in Higher Education Learning and Teaching. AALT, pp. 375–390. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-47392-1_19
Kirsh, I.: Directions and speeds of mouse movements on a website and reading patterns. In: Chbeir, R., Manolopoulos, Y., Akerkar, R., Mizera-Pietraszko, J. (eds.) Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics, Biarritz, New York, pp. 129–138, ACM (2020)
Ostapenko, A.: Developing Models to Visualize and Analyze User Interaction for Financial Technology Websites. Polytechnic Institute, Worcester (2020)
Ortega, J.L., Aguillo, I.F.: Network visualisation as a way to the web usage analysis. In: Aslib Proceedings, vol. 65, no. 1, pp. 40–53. Emerald Group Publishing Limited (2013)
Kamps, I., Schetter, D.: Web-Analyse (Web-Analytics) – messen, analysieren und entscheiden. In: Kamps, I., Schetter, D. (eds.) Performance Marketing. Der Wegweiser zu einem mess- und steuerbaren Marketing - Einführung in Instrumente, Methoden und Technik, pp. 157–174, Springer Fachmedien, Wiesbaden (2017). https://doi.org/10.1007/978-3-658-18453-7_10
Lemon, K.N., Verhoef, P.C.: Understanding customer experience throughout the customer journey. J. Market. 80(6), 69–96 (2016)
Liu, Z., Wang, Y., Dontcheva, M., Hoffman, M., Walker, S., Wilson, A.: Patterns and sequences: interactive exploration of clickstreams to understand common visitor paths. IEEE Trans. Vis. Comput. Graph. 23(1), 321–330 (2017)
Baumann, A., Haupt, J., Gebert, F., Lessmann, S.: Changing perspectives: using graph metrics to predict purchase probabilities. Expert Syst. Appl. 94, 1–21 (2018)
Anderl, E., Becker, I., Wangenheim, F.V., Schumann, J.H.: Mapping the customer journey: a graph-based framework for online attribution modeling. SSRN J. 1–36 (2014)
Zhou, X., Karpur, A., Luo, L., Huang, Q.: StarMap for category-agnostic keypoint and viewpoint estimation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11205, pp. 328–345. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01246-5_20
Rubinov, M., Sporns, O.: Complex network measures of brain connectivity: uses and interpretations. NeuroImage 52(3), 1059–1069 (2010)
Uutela, K., Hämäläinen, M., Somersalo, E.: Visualization of magnetoencephalographic data using minimum current estimates. NeuroImage 10(2), 173–180 (1999)
Cevikalp, H., Yavuz, H.S., Triggs, B.: Face recognition based on videos by using convex hulls. IEEE Trans. Circuits Syst. Video Technol. 1–13 (2020)
Hassler, M.: Digital und Web Analytics. Besucherverhalten verstehen, Website optimieren, MITP Verlags GmbH, Frechen, Metriken auswerten (2019)
Jansen, B.J.: Understanding user-web interactions via web analytics. In: Synthesis Lectures on Information Concepts, Retrieval, and Services, vol. 1, no. 1, pp. 1–102. Morgan & Claypool Publishers (2009)
Web Analytics Association: Web Analytics Definitions, Version 4.0, Washington DC (2007)
Newman, M.E.J.: Networks. An introduction. University Press, Oxford (2010)
West, D.B.: Introduction to Graph Theory, 2nd edn. Prentice Hall, New York (2001)
Bange, C.: Werkzeuge für analytische Informationssysteme. In: Gluchowski, P., Chamoni, P. (eds.) Analytische Informationssysteme, pp. 97–126. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-47763-2_6
Kemper, H.-G., Mehanna, W., Unger, C.: Business Intelligence — Grundlagen und praktische Anwendungen. Vieweg+Teubner, Wiesbaden (2004)
Strika, L.: FuzzyWuzzy: How to Measure String Distance on Python (2019), https://towardsdatascience.com/fuzzywuzzy-how-to-measure-string-distance-on-python-4e8852d7c18f. Accessed 13 Jan 2021
Sokolova, M., Japkowicz, N., Szpakowicz, S.: Beyond accuracy, F-score and ROC: a family of discriminant measures for performance evaluation. In: Sattar, A., Kang, B. (eds.) AI 2006. LNCS (LNAI), vol. 4304, pp. 1015–1021. Springer, Heidelberg (2006). https://doi.org/10.1007/11941439_114
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Scheidthauer, N., Knoll, J., Gross, R. (2021). Visualizing Customer Journeys: How to Illustrate the Entire Customer Interaction Universe of a Commercial Website in Real Time. In: Krieger, U.R., Eichler, G., Erfurth, C., Fahrnberger, G. (eds) Innovations for Community Services. I4CS 2021. Communications in Computer and Information Science, vol 1404. Springer, Cham. https://doi.org/10.1007/978-3-030-75004-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-75004-6_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-75003-9
Online ISBN: 978-3-030-75004-6
eBook Packages: Computer ScienceComputer Science (R0)