Marketing analytics is a diverse field, with both academic researchers and practitioners coming from a range of backgrounds including marketing, operations research, statistics, and computer science. This paper provides an integrative review at the boundary of these four areas. 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.
From a broad perspective, the work in REF surveyed the theoretical foundations of marketing analytics, which is a diverse field emerging from operations research, marketing, statistics, and computer science.
Marketing Analytics: Methods, Practice, Implementation, and Links to Other Fields
Computer Science Mathematics