Clean Customer Master Data for Customer Analytics: A Neglected Element of Data Monetization

Despite the demonstrable benefits of data monetization initiatives for achieving competitive advantages, many of these efforts struggle to realize their potential. Companies often find it challenging to sustain even initially successful data monetization initiatives due to formidable data quality issues. This reflects a disconnect between advancements in data monetization research—which range from digitization to digitalization and digital transformation—and their practical implementation within companies. Consequently, misguided approaches to data monetization are relatively common. A critical prerequisite for successful data monetization is the establishment and maintenance of clean, high-quality data. This study underscores the importance of data quality by conducting an in-depth analysis of Medical Inc., a company that prepares pristine customer master data for advanced customer analytics. The investigation aims to elucidate Medical Inc.’s approach for addressing data cleanliness challenges and developing a general framework for the process of cleansing customer master data. This framework illuminates a relatively unexplored aspect of data monetization, thereby supplementing existing research on digitization, digitalization, and digital transformation.