Non-standardized Address Data

Non-standardized address data is the bane of the marketer’s existence. Address errors, though seemingly minor, can reek of unprofessionalism in the eyes of your clients, and can often lead to your materials being slowed down by the post office, or even sent astray. How do you send mail promos to an address that might not exist? Worse off, isn’t it terrible when your sales rep sends a contract to a potential buyer, only to have it redlined with corrections to their billing address?

What is a standardized address?

The United States Postal Service has issued guidelines for postal addressing standards. They request that delivery address and last line of addresses be complete, standardized, and validated with Zip+4 and City State files.

A standardized address adheres to USPS guidelines by being “fully spelled out” and “abbreviated by using the Postal Service standard abbreviations.”  Furthermore, a complete address is one that “has all the address elements necessary to allow an exact match with the current Postal Service ZIP+4 and City State files to obtain the finest level of ZIP+4 and delivery point codes for the delivery address. A complete address may be required on mail at some automation rates.”

Address data must first be standardized and completed before it can be verified. There are further guidelines for Business Addressing Standards.

For example, here is ActivePrime Inc’s address, as a user might have typed it up:

ActivePrime
800 west el camino road
suite 180
mountain view

A completed address:

ActivePrime, Inc
800 West El Camino Real
Suite 180
Mountain View, CA 94040-2586

A standardized address:

ActivePrime Inc
800 W El Camino Real, Ste 180
Mountain View CA 94040-2586

Where does non-standardized address data come from?

Incomplete, unstandardized data generally comes from user entry. Could be your prospects entering their info into sign up forms at tradeshows or on your website, or your sales rep adding a new record to CRM On Demand. Or say you have a list of new Leads – the address data can be all over the place – and I’m not spending the time to go through and standardize every single address before importing. Neither should your sales reps or marketers.

Even if you do have pristine data, things often get bungled upon import. Perhaps Address 1 and Address 2 data is split into different fields in your report, and you didn’t map both when you imported. Or maybe you swapped what. Or what if the Address 1 and Address 2 data was contained in the same cell, separated by a line break, and then lost somewhere in the process of converting to CSV and importing into CRM On Demand.

How can address errors be prevented?

Generally, the best solution to mindful of address data standardizations at all time. Can you always remember to check your csv file for the data format before importing, then map the fields correctly to preserve your data? Neither can I.

You could also set up an complete address validation field on your records. This could be a custom field simply called “Complete Addres?” that gets updated with a field validation formula for completeness. For US Addresses, try something like:

((([<PrimaryBillToCountry>] IS NOT NULL) AND ([<PrimaryBillToStreetAddress>] IS NOT NULL) AND ([<PrimaryBillToCity>] IS NOT NULL)) AND 
(([<PrimaryBillToCountry>] <> 'US') OR 
(([<PrimaryBillToState>] IS NOT NULL) AND 
([<PrimaryBillToPostalCode>] IS NOT NULL))))

This formula is true when the Country, Address, and City are all NOT NULL, and that either Country is NOT US or State&Zip are NOT NULL.

This solution checks for address completion, but does nothing with regard to address standardization.

How can you fix non-standardized address errors?

You can ask your Sales Reps or Marketing Team to set aside a few hours to manually go through their records and correct addressing errors. This generally wastes time, and where would they look up the correct addresses to verify their data against?

Software packages offer tools to standardize your data. These tools often involve exporting the data from your CRM to a spreadsheet, uploading them into the software for standardization, and then re-inserting the standardized data into your CRM. These tools also need to connect to a standarization database that is up to date.

What are ActivePrime’s solutions?

ActivePrime's solution to non-standardized data is CleanVerify™, a hosted tool that standardizes and verifies address data directly in Oracle CRM On Demand. Learn more about CleanVerify.