Marketing Analytics: Methods, Practice, Implementation, and Links to Other Fields

TL;DR

This paper offers an integrative review of marketing analytics, covering methods, historical development, recent innovations, and practical implementation, aiming to foster interdisciplinary collaboration among researchers and practitioners.

Contribution

It provides a comprehensive overview of marketing analytics, linking various disciplines, and includes practical guidance and open source tools for modern data challenges.

Findings

Historical overview from 1960s to present

Discussion of recent innovations for big data

Practical implementation advice and 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.