DATA QUALITY ISSUES IN CUSTOMER DATABASES AND THEIR SOLUTIONS

Data quality issues in customer databases represent a fundamental research area of strategic importance for modern business. While the rapidly growing volume of customer information in the context of digitalization provides companies with new opportunities, it also leads to the emergence of incomplete, duplicate, outdated, inconsistent, or incorrectly formatted records. These problems not only negatively affect operational processes but also reduce customer satisfaction, diminish the effectiveness of marketing strategies, and result in financial losses for companies. The aim of this study is to provide a systematic classification of the most common data quality problems in customer databases, analyze their impact on business operations, and develop solutions. The study combines theoretical and applied approaches, with a conceptual framework derived from the literature and reinforced by case studies and practical applications. Within the methodology, quantitative data analysis was applied to calculate indicators of incompleteness, duplication, and inconsistency, as well as to compare the effectiveness of data cleaning, standardization, and enrichment methods. The findings reveal that incomplete data hinder customer interaction, duplicate records make campaign management inefficient, outdated data undermine the reliability of decision-making processes, inconsistent records complicate system integration, and incorrectly formatted entries reduce the quality of reporting. The study also emphasizes that data quality issues should not be viewed solely as a technical matter; organizational culture, employee training, and data governance mechanisms are integral components of this process. The results demonstrate that ensuring high data quality in customer databases is a strategic imperative for companies seeking sustainable competitive advantage, and this imperative requires the comprehensive implementation of managerial approaches in combination with technical solutions.