Quality and Analysis of CRM Data: Implications for Brand Strategy Development Case Study Miroglio Fashion S.R.L

This thesis explores the significance of data quality in contemporary business environments, particularly in the context of Miroglio Fashion, a leading Italian company in the fashion industry. The study highlights how effective data management practices can enhance organizational success, offering competitive advantages through operational efficiency and informed decision-making. The research begins by examining the history, mission, and brand portfolio of Miroglio Fashion, including its key brands such as Motivi, Oltre, Fiorella Rubino, Elena Mirò, and Luisa Viola. The role of Miroglio Fashion’s Digital Team is also explored, particularly how it integrates Customer Relationship Management (CRM) systems to maintain and manage customer interactions, improve marketing efficiency, and foster long-term customer loyalty. Central to this thesis is an in-depth exploration of data quality fundamentals, including its importance in marketing planning, compliance, data completeness, and organizational structure. A case study focusing on the brand Oltre illustrates the practical implications of data quality. By examining Oltre’s newsletter strategy, customer behaviour, and engagement patterns, the thesis demonstrates how high-quality data can drive more effective marketing campaigns and improved customer loyalty. The analysis also reveals that companies with superior data quality often experience better business outcomes, including enhanced decision-making, reduced operational errors, and a greater ability to respond to market changes. The thesis delves into the innovations in data quality management, particularly AI-driven data cleansing, validation, and predictive analytics. These technologies help businesses maintain high standards of data governance and accuracy, ensuring data consistency across various systems and platforms. The study also presents the tools and methodologies used for data collection at Miroglio Fashion, including software, as well as manual data verification processes. Loyalty programs are a major focus of this thesis, analysing their structure, objectives, and impact on customer engagement. The research discusses different types of loyalty programs, the marketing aspects involved, and the challenges and opportunities they present. In particular, the study looks at how Miroglio Fashion uses loyalty credits and vouchers as part of its campaign strategy, emphasizing the importance of accurate data in personalizing customer offers and optimizing program effectiveness. The future of data management is examined through the lens of Customer Data Platforms (CDP), with a focus on Miroglio Fashion’s future projects. CDPs enable businesses to consolidate customer data from various sources, providing a unified view that enhances customer segmentation, targeting, and personalized marketing efforts. The thesis argues that investing in such platforms not only improves data quality but also supports long-term business sustainability by fostering better customer relationships and more effective marketing strategies. In conclusion, the research underscores the dynamic nature of data quality in today’s fast-paced business world. The study demonstrates that high-quality data is essential for achieving operational efficiency, improving decision-making, and maintaining a competitive edge in the marketplace.