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Customer data integration (CDI) offers organizations a means to identify and keep track of individual customers in an efficient manner. As a form of data processing, CDI steps include the following: combining separate pieces of information for individual customers into one customer record, regularly updating the records, eliminating duplicate or outdated customer information, ensuring customer protection, and applying research methods to customer data. In essence, customer data integration keeps information accurate, comprehensive, and readily available.
Customer identity resolution is a primary aim of customer data integration. Various factors such as different versions of a person’s name and different provided phone numbers can make maintaining accurate information on a single customer difficult. CDI methods focus on compiling, correcting, and updating data while cleansing databases of wasteful information like duplicate documents. This contact information data may be gained through past customer transactions or by marketing to the customer via phone, mail, or computer technology.
A strong customer data integration framework thus streamlines the storage of information within systems. Data input relies on electronic databases, and these databases may be filled with dozens of information entry fields just for a single customer. Even subdivisions like names and addresses may have numerous versions and branches of a single piece of information.
Adding to the complexity, many organizations take varying chunks of customer information and use them in different departments, and sometimes different locations altogether. The same information may be needed by a cashier in an organization’s store and by a call center worker miles away. As the information travels through various agencies, its format may be altered. Information changes can be facilitated by customer habits like a change of address or a change in marital status as well. Enhanced forms of data processing can answer some of these obstacles.
Once a comprehensive view of customers is accomplished, organizations can utilize the enhanced information for research purposes. For example, an organization may seek out certain demographics — classifications like gender and income level — within its database and target a new product to this demographic. CDI also allows an organization to track a customer’s lifestyle changes, such as a rise in income level, and invest in that customer accordingly. Through CDI research, organizations can solidify customer experience management and yield satisfied customers.
Customer data integration is a needed component of an organization’s enterprise architecture (EA) framework. An EA framework outlines the structure, operations, and interconnections between different divisions of an organization. Such frameworks consider technology and data collection as cornerstones on which a company builds its day-to-day operations. CDI helps strengthen this foundation by utilizing technology to provide the most efficient and accurate data possible.