| dc.description.abstract | The grocery industry has experienced great changes as a result of the continuous and growing influence of technology. Groceries are a necessity and a routine in customers’ lives, which differentiates the way in which customers make purchase decisions and build shopping habits in comparison to other industries within the retail area. Additionally, grocery retailing is a highly competitive industry with low profit margins, making it imperative for marketers to implement tactics to maximize ROI. Through the use of customer data, marketers in the grocery industry are often looking for ways to enhance customer experiences and improve business practices. We aim to address this topic by investigating how data-driven marketing can be applied in the grocery industry through the analysis of shopping basket data. Firstly, we draw upon past literature to define the customer journey in the grocery industry, and outline the importance of utilizing data as a marketing tool. We define market basket analysis, substitution and complementarity, as these are the research methods that we will utilize to analyze our data set. Based on relevant theory, we then determined the following data-driven marketing implications that are particularly relevant in the grocery industry: store layout, targeted marketing campaigns, and loyalty programs. In collaboration with Norwegian grocery retailer Rema 1000, we used market basket analysis to identify product relationships and top association rules for varying products within the store. Through the analysis of the data-driven implications, past research, and our results, we discuss how the application of data can be used to provide a personalized customer experience, improve customer loyalty, and better business practices. | |