Approaches to customer data management in digital retail platforms

this article explores various approaches to customer data management within digital platforms operating in the retail sector. While such strategies increasingly shape competitive advantage, a stable methodological framework in this domain has yet to emerge. The tightening of regulatory constraints, the rapid expansion in the volume of collected data, and the growing diversity of user scenarios have created a context in which traditional operational models and managerial routines lose their effectiveness. The objective of the study is to identify the core directions present in academic and applied literature on the topic and to systematize the prevailing approaches to structuring customer data management within platform-based environments. The analysis of sources reveals a significant fragmentation in research perspectives: some authors focus on the marketing use of data, others emphasize behavioral modeling and digital analytics, while still others address platform architectures and market trends. However, essential issues such as ethical infrastructure, regulatory interoperability, and technological isolation in the context of ecosystem competition remain underexamined. The article offers a structured synthesis of existing analytical approaches and formulates key characteristics of a flexible data management infrastructure applicable to retail platforms. The author’s contribution is supported by practical experience drawn from the Tkaniti project, launched in 2020 as an online store specializing in Italian fabrics and accessories. The findings are relevant for scholars in the field of digital transformation, platform architects, and strategic planners in the retail industry.

CDP architecture, customer analytics, customer data, data management, digital retail, platform ecosystems