A common data representation model for customer behavior tracking

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Imagen de portada del número Las comunicaciones en el nuevo paradigma de marketing.
PDF HTML Customer behavior data model figure 01 (Spanish) Customer behavior data model figure 02 (Spanish) Customer behavior data model figure 03 (Spanish) Customer behavior data model figure 04 (Spanish) Customer behavior data model figure 05 (Spanish) Customer behavior data model figure 06 (Spanish) Customer behavior data model figure 07 (Spanish) Customer behavior data model figure 08 (Spanish) Icono14 Customer behavior data model updated (Spanish) Table 01 (Spanish) Table 02 (Spanish) Table 03 (Spanish) Table 04 (Spanish) Table 05 (Spanish) Table 06 (Spanish) Table 07 (Spanish) Table 08 (Spanish)
Published: 01-07-2017
Accepted: 26-06-2017
DOI: https://doi.org/10.7195/ri14.v15i2.1078
Keywords:
Customer experience, Customer behavior, Customer intelligence, Behavioral data model, Customer predictive analytic, Customer behavior patterns
Dimensions

Main Article Content

Nicolas Martin Casariego Sarasquete
(ES)
IE
ncasariego@faculty.ie.edu
https://orcid.org/0000-0003-1135-1642 (unauthenticated)

Abstract

Customer behavior has drastically changed in recent years. Being able to anticipate your customer’s’ behavior is the holy grail for every business leader. Now we are able to track and store part of the observed customer behavior, thanks to digital transformation processes, social networks adoption, cloud infrastructure and big data technology availability. This observed behavior is made up of repetitive transactions and recurring purchases, as well as navigation and interactions through digital properties, channels, devices, applications and social networks. The present article establishes the foundation for a common data representation model of tracked customer behavior. With this data model in place, organizations will be able to represent any given customer-centric business model allowing to analyze the most popular marketing problems: like segmentation, cross-selling, retention, etc. Also most popular analytic and predictive software tools could be used for consumer behavior storage and analysis.

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Article Details

Issue

Vol. 15 No. 2 (2017): Communications in the new marketing paradigm. Experiences, relevance, engagement and personalization

Section

Monograph

Author Biography

Nicolas Martin Casariego Sarasquete, IE

Adjunct Professor
(IE Business School)
Co-Director of Customer Analytics Farm
(IE School of Human Sciences & Technology)

How to Cite

Casariego Sarasquete, N. M. (2017). A common data representation model for customer behavior tracking. Journal ICONO 14, 15(2), 55-91. https://doi.org/10.7195/ri14.v15i2.1078

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