Data Analytics for Sales Strategies: Lessons in Customer Management

When it comes to data management in today’s business landscape, a key focus lies on enhancing sales strategies. Through the effective utilization of data, companies can derive valuable insights about their customer base, identify behavioral patterns, and make well-informed decisions to boost their sales endeavors. This article delves into the critical facets of customer management through data science, a practice that not only drives revenue growth but also fosters stronger customer relationships, ultimately delivering a sustainable competitive edge in the digital age. The study employed a qualitative research methodology with an exploratory approach, carrying out data collection and analysis via a bibliometric review of 279 academic-scientific references sourced from indexed databases. The research findings underscore the advantages of leveraging data analytics in sales strategies and customer management, facilitating objective decision-making through customer relationship management technologies. Furthermore, the study sheds light on the challenges and opportunities associated with data analytics in sales processes, homing in on customer segmentation, operational efficiency, competitive positioning, and enhanced customer interactions. The conclusion reinforces the significance of data management in refining sales strategies and elevating customer management, with key focal points encompassing tailored customer experiences, operational effectiveness, competitive benefits, enhanced customer rapport, and hurdles in data analysis. Recommendations revolve around investments in technology, sustainability practices, ethical considerations, and continuous monitoring. Subsequent research avenues could delve into the ramifications of artificial intelligence and machine learning, sustainability dimensions in data, and pivotal concerns regarding data privacy and security. Received: 11 January 2025 | Revised:18 March 2025 | Accepted: 14 August 2025 Conflicts of Interest The author declares that he has no conflict of interest in this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Gabriel Silva-Atencio: Conceptualization, Methodology, Validation, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.