Customer data integration (CDI) combines and updates customer information, eliminates duplicates, and protects customer data. CDI simplifies data storage and allows for research and targeting of demographics. It is a necessary component of an organization’s enterprise architecture framework.
Customer data integration (CDI) offers organizations a means to identify and track individual customers efficiently. As a form of data processing, the steps of the CDI include the following: combine separate information for individual customers into a single customer record, update records regularly, eliminate duplicate or obsolete customer information, ensure customer protection, and enforce research methods to customer data. Ultimately, integrating customer data keeps information accurate, complete, and readily available.
Resolving customer identity is a primary goal of customer data integration. Various factors, such as different versions of a person’s name and different phone numbers provided, can make it difficult to maintain accurate information about an individual customer. CDI methods focus on compiling, correcting, and updating data while cleaning databases of useless information such as duplicate documents. This contact information may be obtained through transactions with past customers or through marketing to the customer by telephone, mail or computer technology.
A robust customer data integration framework therefore simplifies the storage of information within the systems. Data entry relies on electronic databases, and these databases can be populated with dozens of information entry fields just for a single customer. Even subdivisions such as names and addresses can have numerous versions and branches of a single piece of information.
Adding to the complexity, many organizations take different chunks of customer information and use them in different departments and sometimes completely different locations. The same information might be needed by a cashier in an organization’s store and a call center employee miles away. As information travels through various agencies, its format can be altered. Changes to information can be facilitated by customer habits, such as a change of address or even a change in marital status. Advanced forms of data processing can address some of these hurdles.
Once a complete view of customers is obtained, organizations can use the advanced information for research purposes. For example, an organization can search its database for certain demographics – classifications such as gender and income level – and target a new product to this demographic. CDI also allows an organization to track changes in a client’s lifestyle, such as an increase in income level, and invest in that client accordingly. Through CDI research, organizations can consolidate customer experience management and achieve satisfied customers.
Customer data integration is a necessary component of an organization’s enterprise architecture (EA) framework. An EA framework outlines the structure, operations and interconnections between the different divisions of an organization. Such frameworks view technology and data collection as the cornerstones upon which a company builds its day-to-day operations. CDI helps strengthen this foundation by using technology to deliver the most efficient and accurate data possible.
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