Data-Driven Marketing Strategies in Conventional and Online Retail for Customer Loyalty Enhancement
DOI:
https://doi.org/10.31334/dgzc4107Kata Kunci:
Data-driven marketing; Conventional retail; Online retail; Customer loyalty; Retail type moderation; Personalization strategies;Abstrak
This study aims to analyze data-driven marketing strategies in conventional and online retail and their influence on customer loyalty, with retail type as a moderating variable. Using a quantitative approach, data was collected through surveys from 200 respondents across various regions in East Java (Surabaya, Malang, Blitar, Kediri, Probolinggo, and Jember) who are customers of Alfamart and Indomaret. Data analysis employed Structural Equation Modeling with PLS 3.0. Results show that personalization of promotion and communication (β=0.279, p=0.002), data-based segmentation and targeting (β=0.262, p=0.002), and digital channel utilization (β=0.251, p=0.005) significantly and positively affect customer loyalty. However, most moderating effects of retail type were not significant, except for the negative moderating effect of online retail on the relationship between personalization and loyalty (β=-0.370, p=0.004). The model explains 70.2% of loyalty variation. Companies should prioritize optimizing core data-driven marketing components rather than focusing excessively on retail channel expansion.
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