Optimizing Marketing Analytics in Philippine Retail: A Mediated Model of Lead Generation and Customer Relationship Management

Abstract

This study investigates the impact of Marketing Analytics on Marketing Performance, with Lead Generation and Customer Relationship Management (CRM) as mediators in the retail sector. This study employs a quantitative research design using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze how analytics usage impacts marketing performance among 158 retail companies in the Philippines. Data was collected via a Likert-scale survey and validated through rigorous statistical tests for common method bias, endogeneity, and both formative and reflective measurement models. Survey data from 158 retail businesses, represented by 316 executives, were analyzed using PLS-SEM to test the relationships among Marketing Analytics, Lead Generation, CRM, and Marketing Performance. The results confirm that Marketing Analytics significantly enhances Marketing Performance, directly and indirectly. Lead Generation strengthens the link between analytics and CRM, while CRM converts data-driven insights into sustained customer engagement and long-term business growth. This study introduces the Marketing Analytics Integration Framework for Retail, emphasizing that analytics is most effective when integrated with lead generation and CRM. It highlights the need for CRM-driven lead management, predictive analytics for demand forecasting, and omnichannel engagement. By focusing on the Philippine retail industry, this study provides empirical evidence on how businesses can optimize Marketing Analytics by providing actionable insights on how businesses can optimize analytics-driven marketing strategies.