List Work Resources

1. When you provide a suppression list, it’s typical that 50% – 99% of these names will be found on the original mailing list. If you expect us to match a full 100%, or anticipate a low match rate of <50%, please let us know.
    
2. We can Dedupe by Individual if you want every individual person on your list to receive the mailing. 
   • Duplicate records are detected based on first name, last name, and mailing address. 
   • These must be an exact match in your data for our software to catch it. 
   • Example Data: 
     • John Smith, 123 Main Street, Everywhere, PA 12345 
     • Jon Smith, 123 Main Street, Everywhere, PA 12345 
     • John Smith, 123 Main Street, Everywhere, PA 12345 
     • Jane Smith, 123 Main Street, Everywhere, PA 12345 
   • If your data includes the example records above: 
     • Record #3 will be suppressed because the first name, last name, and address are the same as #1.  
     • Records #1 and #2 will be mailed, because the first name is spelled differently in each record. 
     • Record #4 will be mailed, because the first name is different.
        
3. We can Dedupe by Address if you want one item per mailing address to be mailed. 
   • Duplicate records are detected based on address and zip code. 
   • These must be an exact match in your data for our software to catch it. 
   • Example Data: 
     • John Smith, 123 Main Street, Everywhere, PA 12345 
     • Jane Smith, 123 Main Street, Everywhere, PA 12345 
     • Sally Jones, 123 Main Street, Everywhere, PA 12345 
   • If your data includes the example records above: 
     • The first record (John Smith) will receive the mailing.  
     • The other two (Jane Smith and Sally Jones) will be suppressed. 

1. Per USPS recommendations, Graphcom uses upper case address blocks for most mailings, unless otherwise specified by the client for aesthetic purposes. For example: 123 MAIN STREET.
    
2. Graphcom addresses mail pieces in the following format, unless otherwise specified.

The data that is used for deduping and that appears on your mailings is only as good as the data in your database. Below are examples of common data mistakes that can affect the quality of your mailing. 

Example 1: Differently spelled instances of the same name. If you have “John Smith” and “Jon Smith” in your database at the same address, they will not be deduped. 

Example 2: Extra spaces. If you have “John Smith” and “John  Smith” in your database at the same address, they will not be deduped.

Example 3:  Missing capitalization. If you have “Jon Mcclintock” in your database, our software will not know to correct it to be “Jon McClintock” instead.

Example 4: Missing Prefixes. If the salutation line of your letter is designed as “<Prefix> <LastName>” but the record for “John Smith” is missing the “Mr.” in the prefix field, the salutation will appear as “Dear Smith”.