Data-Driven Marketing in Grocery industry to Enhance Sales and customer loyalty

Abstract Nowadays, data-driven marketing has garnered significant attention from researchers due to the use of advanced technologies and the increase in stored data within businesses. Numerous articles and models have been presented regarding this approach in marketing. The primary aim of this study was to identify the main and sub-components of data-driven marketing in the grocery industry. To this end, a systematic literature review method was employed in this research. Based on the PRISMA method, 36 articles were selected for analysis. After analyzing the articles, 13 main components were identified. These components include Technology Acceptance, Customer Segmentation, Personalization, Predictive Analytics, Pricing Optimization, Customer Relationship Management (CRM), Marketing Channel Optimization, Data Integration and Management, Campaign Performance Measurement, Customer Loyalty Programs, Smart Placement and Arrangement, and Data-Driven Monitoring of Competitors. Additionally, two metrics—sales enhance and customer loyalty—were proposed as performance criteria for the final model in the grocery industry. Recommendations were also provided to grocery businesses on how to implement these model components.