Capability Maturity Model for data-driven marketing

Abstract

Data-driven decision-making is gaining buzz and popularity across organizational functions and industries. Consequently, data analysis and marketing analytics enable companies of various size and business volume to leverage sustainable performance outcomes and continuous growth through data-driven marketing. Still, marketing professionals lack the tools, skillsets and procedures in turning this data into insights, and, furthermore, insights into action. Furthermore, research has yet not addressed these issues of data-driven marketing practice. Hence, this thesis aims to tackle a gap in current research and practice, and to gain further knowledge into the fragmented research on data-driven marketing. The goal of this study is to discover and understand the current level of data- driven decision-making as well as marketing analytics usage in marketing departments. Additionally, this thesis seeks to discover possible barriers that hinder such process development and usage of analytics for marketers. In doing so, this thesis aims to identify and create a model that describes the degree to which marketing analytical insights and data-driven methods are used in an organization and what may block the progression in this model for marketers. This thesis takes a qualitative approach to the research dilemma. The data and methodology used in this research include ten marketing professionals’ interviews, as well as a thorough literature review to describe the theoretical framework and to position for this thesis. The data-driven marketing maturity and capability of each case organization was evaluated through qualitative analysis by reflecting the interviewees’ answers on the different levels of the Maturity Model. Through this, a Data-driven Marketing Capability Maturity Model was conceptualized. The thesis further extends the existing research on Capability Maturity Models by introducing barriers to data-driven marketing. These barriers were classified into three different categories: organizational structure barriers, organizational culture barriers and top management barriers. The barriers were placed onto the Data-driven Marketing Capability Maturity Model, to identify the major obstacles to moving forward in each level.