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Who are your customers? 

How do you find your customers in your data bases when you have only their contact information?

 

About Mematch

Imagine identifying your customers third party data by name, address, telephone # and other contact info against your administrative customer databases.

How would you efficiently match slight variations on your customers names and address against your master administrative database standard name and address?

How can you set up an efficient process that uses different matching criteria to cross match and identify your customers?

Business Case

  • Client has a file with customer contact info that needs to be cross referenced against another file having a field of interest such as “Customer ID#”.
  • Since contact info is not kept in a standard format and may have slight variations in both files, a simple match by “Name”, “Address”, “City”, “Zip Code” and “State” or other information may produce only a few matches.
  • Manual variations of “Name”, “Address”, “City”, “Zip Code” and “State” or other information will increase # of matches but are time consuming and error prompt.

The MeMatch Solution

  • The algorithm matches variations of contact info in both files to produce a file with the corresponding customer ID.
  • The algorithm allows for the use of the sounds like criteria
    The algorithm criteria is table driven. It assumes that the criteria Rank, crit field, in the criteria table indicates the accuracy and strictness of a given criteria when compared to others. For example It assumes that crit #1 is the most accurate and strict, # 2 the second most accurate and strict.
  • The algorithm goes in sequential order and loops through "n" number of matching criteria in the criteria table. A criteria table outlines the rule for matching records. For example a criteria may require exact matches on name, address, city, state and zip code. Another criteria may required matches on the first 7 characters of name, and full matches on address, city, state and zip.

 

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