Database: The Address Quality Gatekeeper

Keep human error out of your data

Collecting and maintaining accurate address information is an issue for companies of all sizes. The ramifications of poor address quality can be far-reaching and expensive. What you need is a gatekeeper.

In the past, organizations often didn’t take steps to tackle issues with inaccurate customer information because it resided in multiple, unconnected databases. Individual business units kept their own records, so departments like sales, service, marketing and billing may have had data on the same customer in different formats on different servers with no standardization. Even with integrated CRM systems, this issue is pervasive. Though the technology has improved, the challenge of normalizing data across disparate sources still exists.

Address Quality Myths
Many companies prefer to cling to beliefs about address data quality instead of pursuing a solution. Some of the more prevalent assumptions include:

Customer DIY: The fact is, your customers will not police their own data quality. They won’t even notice they made the mistakes. If they don’t receive their orders, guess who looks bad. Unless you have processes in place to validate address information and check for duplicates, your master file is likely to become a tangled mess of partial, duplicate and erroneous data.

Call center limitations: No matter how well they are trained, a customer service representative or telemarketer isn’t going to know if the customer neglected to supply street directionals or that house number digits have been transposed. Garbage in, garbage out.

Returned mail: Some documents are quite expensive to correct and remail. The cost to manually recreate applications such as brokerage statements can be three to five times the amount spent to produce the original. Undelivered marketing materials can result in missed sales opportunities. This gets especially critical on multichannel campaigns where related content is communicated based on an anticipated in-home date.

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