Building the foundation for customer data quality in CRM systems for financial services firms

The digital revolution has led to firms with massive amounts of information. Thus, the storage, collection and appropriate use of such data is a major challenge for firms as they struggle to implement profitable integrated marketing communication strategies. Given this, the goal of our article is to analyze the types of customer-based data that organizations can collect to learn about their customers and determine methods by which the collection of such information can ensure higher data quality for use in Customer Relationship Management (CRM)-based systems. Our work also studies the relative value of each type of data in developing higher quality customer data and superior CRM systems. These data tell managers how to organize their priorities in terms of data learning activities to create the highest quality CRM data so that improved performance can ensue. Our findings show that capturing the results of personalized communications and detailed transactions of customer interactions will yield the highest results and perhaps should be the organization's focus.