Optimization of SME Marketing Strategies through Digital Data-Based Customer Profitability Analysis: A Case Study of SMEs in the Former Surakarta Residency

This study explores the potential of digital data-based customer profitability analysis in optimizing marketing strategies for Small and Medium Enterprises (SMEs) in the former Surakarta Residency, Indonesia. Using a mixed-method approach, including semi-structured interviews with 15 SME owners/managers, direct observations, document analysis, and an online survey of 250 customers, the research investigates the current state of digital data adoption, challenges in implementation, and the impact of customer profitability analysis on marketing effectiveness. The study employs RFM (Recency, Frequency, Monetary) analysis for customer segmentation and calculates Customer Lifetime Value (CLV) to identify key profitability drivers. Findings reveal limited awareness and implementation of digital data-based customer profitability analysis among SMEs, primarily due to resource constraints and technical expertise limitations. The research identifies four customer segments, with 15% (Platinum customers) contributing significantly to profitability. Purchase frequency and average transaction value emerge as primary profitability drivers. The study concludes that while digital data-based customer profitability analysis offers significant potential for optimizing SME marketing strategies, realizing this potential requires collaborative efforts from SME stakeholders, policymakers, and support institutions to address implementation challenges and build a supportive ecosystem for data-driven marketing practices.