Marketing analytics: Methods, practice, implementation, and links to other fields. (1st April 2019)

• Record Type: Journal Article
• Authors: France, Stephen L.; Ghose, Sanjoy
• Is Part Of: Expert systems with applications. Volume 119(2019)
• Page Start: 456
• Page End: 475
• Publication Date: 2019-04-01
• Subjects: Analytics -- Prediction -- Marketing -- Visualization -- Segmentation -- Data mining; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2018.11.002
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A business focused overview of the current state of marketing analytics. An integrative review at the boundary of expert systems, marketing science, statistics, and operations research. The topics of visualization, segmentation, and class prediction are featured. Practical implementation advice is given, along with a directory of open source R routines. Abstract: Marketing analytics is a diverse field, with both academic researchers and practitioners coming from a range of backgrounds including marketing, expert systems, statistics, and operations research. This paper provides an integrative review at the boundary of these areas. The aim is to give researchers in the intelligent and expert systems community the opportunity to gain a broad view of the marketing analytics area and provide a starting point for future interdisciplinary collaboration. The topics of visualization, segmentation, and class prediction are featured. Links between the disciplines are emphasized. For each of these topics, a historical overview is given, starting with initial work in the 1960s and carrying through to the present day. Recent innovations for modern, large, and complex "big data" sets are described. Practical implementation advice is given, along with a directory of open source R routines for implementing marketing analytics techniques.