Role of Data Analytics in Enhancing Retail Customer Retention through Customer Satisfaction and Engagement: Evidence from Bangalore Retail Customers

Abstract

The retail sector in Bangalore has experienced rapid digital transformation, creating significant opportunities for retailers to leverage data analytics for enhancing customer retention. This study examines the role of data analytics in improving customer retention among retail customers in Bangalore by focusing on customer data collection, customer segmentation, predictive analytics, personalized marketing, artificial intelligence (AI), and big data analytics. A quantitative research approach was adopted using a structured questionnaire administered to 385 retail customers. The collected data were analyzed using descriptive statistics, reliability analysis, correlation, Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). The findings reveal that data analytics significantly contributes to customer retention, with AI and Big Data Analytics emerging as the strongest predictor (β = 0.402), followed by Predictive Analytics (β = 0.368) and Customer Engagement (β = 0.356). The CFA results confirmed the reliability and validity of the measurement model, while SEM results supported all proposed relationships. The study concludes that data-driven retail strategies improve customer satisfaction, customer engagement, and long-term customer loyalty. The findings provide valuable managerial insights for retailers seeking to enhance competitiveness and sustainable growth through advanced analytics and customer-centric decision-making.