Genuine, Authentic and Accurate Data… What’s the Difference?
At the heart of our data validation suite is our company’s mission: Deliver the most genuine, authentic and accurate data as possible to our customers. Often we’re asked to clarify the differences between “genuine, authentic and accurate” data.
This is how we explain the differences between these three very important data validation points:
Example 1 – Accurate Data
Mike Wilson visits your website and fills out a registration form. When Mike enters his address, he inadvertently types in “123 Mian Strt” instead of “123 Main Street. This is an example of data that is NOT ACCURATE even though Mike Wilson is a real person and meant to enter his valid information. Accuracy issues with mailing address data waste an exorbitant amount of time and money in postage and printing. With the most accurate data, companies reduce wasted mailing costs, paper and resources.
Example 2 – Authentic Data
Mike Wilson visits your website and fills out a registration form. When he enters his address, he types in 123 Main Street, Los Angeles, CA. While the information and address that Mike entered is technically accurate, our web services confirm that the address is a large parking lot, and Mike’s IP address is in another country. Further, the bank identification number tells you that this is a prepaid gift card which may be a red flag as well. This Mike Wilson is NOT authentic. Data authenticity is a critical step in detecting and preventing fraud data and orders from entering your systems.
Example 3 – Genuine Data
Mike Wilson visits your website and registers with the name Mickey Mouse. He enters the address 1313 Disneyland Railroad, Anaheim, CA. This is an accurate, real name and address; however, it is definitely NOT genuine. When people use bogus, vulgar or celebrity names in lieu of their genuine information, they have no place in your contact database.
Making sure that your data is genuine, authentic and accurate is one of the most vital components in data quality excellence.
If you have questions about data validation, feel free to call us we’re happy to talk!