Who are your customers?
do you find your customers in your data bases when you have only
their contact information?
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?
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 algorithm matches variations of contact
info in both files to produce a file with the corresponding
The algorithm allows for the use of the sounds
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.