matchIT Data Quality Suite
Addressing And Address Validation Software
Address validation and correction is an extension of the requirements for effective data profiling, marketing, database management, and list management, and the addressIT features powerful and proven address correction software to reliably correct and update your marketing/mailing lists and contact database.
Standardized addresses are required to take advantage of USPS® mailing discounts, and ensure your marketing, communications, and ultimately the accuracy of your data is at peak performance.
addressIT by our partnership, is fully certified by the United States Postal Service® to:
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Correct misspellings, directionals (N, SE, etc.) and designators (ST, BLVD, etc.)
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Update 5 - digit ZIP® codes and add the ZIP + 4® code and carrier routes
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Assign Line - of - Travel (LOT) for greater postal discounts
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Add congressional and county code
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Correct multiple lines of address information
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Identify and analyze un-coded addresses so previously undeliverable addresses can be corrected and included with the rest of your mailings.
In the end, the matchIT suite with the addressIT module can increase the accuracy of matched records and help create an accurate view of each customer, resulting in a more accountable and precise view of your clients and prospects.
Delivery Point Validation (DPV)
CASS Certified software solutions can only determine whether an address falls within a given address "range." Delivery Point Validation takes address correction to the highest level by interrogating the address at the building level to determine whether an address is deliverable. In essence it is the difference between knowing that 100 to 1600 Main Street is a deliverable address range, but 109, 111, 113 were torn down to create a new shopping mall and parking lot.
Any company engaging in direct marketing, or has the requirement to create a correct and accurate view of their contact data, should employ addressIT's DPV capabilities to reduce mailing/marketing failure rates or to reduce the propensity for fraud. Failing to do so will only create a myopic view of your data.
