Demystifying Big Data Analytics for Business Intelligence Through the Lens of Marketing Mix
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
---|---|
Pages (from-to) | 28-32 |
Journal / Publication | Big Data Research |
Volume | 2 |
Issue number | 1 |
Online published | 18 Feb 2015 |
Publication status | Published - Mar 2015 |
Link(s)
Abstract
Big data analytics have been embraced as a disruptive technology that will reshape business intelligence, which is a domain that relies on data analytics to gain business insights for better decision-making. Rooted in the recent literature, we investigate the landscape of big data analytics through the lens of a marketing mix framework in this paper. We identify the data sources, methods, and applications related to five important marketing perspectives, namely people, product, place, price, and promotion, that lay the foundation for marketing intelligence. We then discuss several challenging research issues and future directions of research in big data analytics and marketing related business intelligence in general.
Research Area(s)
- Big data analytics, Business intelligence, Marketing intelligence, Marketing mix, Survey versus log data
Citation Format(s)
Demystifying Big Data Analytics for Business Intelligence Through the Lens of Marketing Mix. / Fan, Shaokun; Lau, Raymond Y.K.; Zhao, J. Leon.
In: Big Data Research, Vol. 2, No. 1, 03.2015, p. 28-32.
In: Big Data Research, Vol. 2, No. 1, 03.2015, p. 28-32.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review