Outsource Solutions: Database Marketing
Next, analyze the appended data files. For each vendor’s file, determine:
• What is the overall match rate? How many of your names and addresses was the provider able to match at the individual level?
For each variable or data element appended, ask:
• What is its coverage? Of all the records the provider was able to find, how many pieces of information or what portion of the data elements you specified was it able to append? All things being equal, the higher the coverage the better, says Wheaton. However, he suggests marketers dig deeper to understand what lies behind the coverage rate. “High coverage based on overly aggressive matching criteria will inflate coverage at the expense of quality,” he cautions.
• What is its precision? If you are appending age, for example, is it a range or an exact date of birth? The exact date of birth, notes Wheaton, can be critical for some campaigns, such as an insurance company marketing Medicare supplemental insurance.
• What type of data is it? Is it self-reported, actual or modeled? Data providers may model several data characteristics to provide an inferred result. Income is a classic example, says Wheaton, who explains that characteristics such as age, home value, vehicle ownership and neighborhood census data can be used to generate an income estimate.
• What is the breadth of coverage? How many of your desired data elements was the vendor able to match? Well-known providers of general data usually have a large overlap between their databases. However, there are some differences. For example, says Grossman, one vendor may only achieve a 12-percent match rate on golf, which may be an important psychographic, whereas another vendor achieves a 47-percent match rate with the same names.
Check for Accuracy
Include a number of decoy files with the names and addresses of friends and family in your sample data file. When you get the overlay results or data back, ask them to verify the accuracy of the information appended to their files.