Challenges in Usage of Unstructured Data in Marketing Decision Making: An Abstract

Abstract

Marketing analytics has become an important tool for business practice, enabling companies to improve their marketing decisions and thereby business performance. While marketers are actively using structured data (SD) to support their decisions, usage of unstructured data (UD) remains overlooked by most organizations. Yet over 80% of available data is unstructured, meaning that companies cannot afford ignoring its potential in multiple areas of marketing decision making. Previous studies on usage of UD in marketing decision making are mainly focused on development of tools and approaches that can be used to work with such type of data (e.g., Büschken and Allenby 2016) or address opportunities of using UD in marketing decision making, suggesting instances when different types of such data can be used (e.g., Decker and Trusov 2010; Malthouse et al. 2013). This study generates deeper insights into the practice of using UD in marketing decision making by analyzing key challenges associated with usage of UD. More specifically, this study addresses the following research questions: What challenges do marketing managers face when using (or attempting to use) UD to support decision making? What are the main stumbling blocks related to the usage of analytics (and UD in particular) in marketing decision making? The study relies on in-depth qualitative interviews with marketing professionals representing international FMCG companies in Northern Europe. As a result, it develops a categorization of challenges related to the usage of UD, which are primary causes of hesitance towards usage of such data in marketing decision making. Mainly, the challenges are related to volumes and quality of data; limited ability of tools to work with different types of UD; skills of marketing managers; as well as outdated organizational routines. For managers, the present study points to diverse challenges related to the use of UD, both within and outside the power of their influence. The study analyzes common challenges related to data and tools; to managerial skills; and to aspects of organizational culture hindering the adoption of analytics. Furthermore, it highlights the need to simplify sharing of data between different parties that need it and to introduce centralized data management functions supporting this process.