Customer Identification. Part 2.

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In the last few years, new CDI technology has emerged that can improve the speed and accuracy of customer identification without requiring a large-scale customer data warehouse. This new technology differs from previous data integration technologies in that it uses what is called a “knowledge-based” approach.

Using a knowledge-driven approach, identity information is first matched against the merchant's CDI database, which contains complete information about the consumer. This database, built from multiple storage media, contains virtually namibia whatsapp data variation of a person's name and address, and a company's name and address, including a complete list of previous addresses. Information about first names, middle names, nicknames, maiden/married names, old and new addresses are stored, analyzed, and cross-referenced. Within this knowledge base, references (such as numbers) are assigned to each address, person, or company. The same reference is maintained for each person, regardless of changes to their name or address. When a match occurs, this persistent reference is passed back to the application, allowing new data to be easily linked to previous records. What was once a convoluted, time-consuming process of address cleansing, address reprocessing, and name matching is now simplified to a straightforward number match that can be performed easily in real time.

Using this technology, companies can instantly determine that a woman calling herself Mary Smith of 123 Elm. St. (first name, maiden name, old address) is actually a current customer, listed in customer information files as Elizabeth Jones of 243 Oak St. (middle name, married name, new address). All of Mary's customer information, which may be scattered across multiple databases, can be instantly found. Mary can be instantly identified as a high-value customer, and all of her information can be used to tailor her experience to her needs. Matching differences in names and addresses would not be possible without a knowledge-based approach.