data Setting data quality standards is a necessary best practice for your marketing database in order to efficiently and effectively convert prospects into paying customers. Commitment to consistency is quite possibly the most important thing to remember.

Whether you are just getting started or recognize the need for a massive data clean up, we recommend you implement these standards as soon as possible:

Abbreviations vs. Full Version

Set data quality standards around what fields use abbreviations and which do not. There’s no right choice, but pick one and stick with it.
Street Name – St. or Street
State – NY or New York
Country – U.S. or United States of America

Decide how fields should be recorded and put processes into place to enforce them. You could include updating forms to default to these settings, incorporating drop downs, and conducting training for anyone who enters data into the system.


When requesting numeric information on your online forms, where possible give the option of preset ranges for items like budgets, time frames (1-3 months) etc. In the other numeric fields, make sure they are formatted and can only be entered in one specific way.

Phone Number – 123.456.7890 or 123-456-7890 or (123)4567890
Dates – 10.1.16 or 10.1.2016 or October 1, 2016 or Oct-1-16

Pay particular attention to the Date field as this is one you will use to sort when analyzing your data.


Typos aren’t always easy for a database to catch. To try and avoid these types of errors use drop down fields whenever possible: commonly used job titles, areas of interest, or any other similar field regularly used in your industry.


Create and implement processes that easily allow you to identify duplicates and merge the records together. Set automated reports that recognize dupes based on email, phone number, and/or mailing address. While this begins with an automated system, it will also involve a manual review and approval of the merges. Therefore, training needs to take place to help determine which entry should be the master, and which should be deleted.

Bounce Backs

Monitor returned emails and direct mail pieces and make updates to the database in a timely fashion. Excessive bounce backs is an indication of dirty data. Don’t let this happen to you!

By implementing a consistent and controlled management process of your database, your marketing efforts will be that much more powerful and effective. What data quality standards do you have in place? Which do you find are the most helpful? Reach out and let us know. And if you have any questions about setting and implementing data standards or analyzing your current marketing data, please don’t hesitate to send us an email or give a call at 571-606-3106, the Yetis are waiting to hear from you.

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