Using a mix of in-house techniques and outside database vendors to clean up its databases and produce more accurate contacts, Unisys discovered that about 10% of contacts within key accounts ended up being bad or out of date, compared with about 25% as little as a year ago.
The first thing Unisys executives did was determine the key accounts they should target for cleaning. "The company has done a very good job of really determining that these are the target accounts we're going to focus our resources on—because they are either good customers or have a [high probability of] turning into good customers," said Jon Balcerek, database marketing manager for Unisys' Inside Sales & Marketing Group.
Then, Unisys' Inside Sales & Marketing reps called contacts in those companies, especially ones they had not contacted for some time, to ensure that those individuals' titles and other information was correct. At the same time, they found out who the decision-makers were in other areas of the company. Unisys wants to be a "solutions company" and sell its services to those not directly in IT departments, Balcerek said.
Inside Sales & Marketing reps also received valuable input from the company's Outside Sales & Marketing reps, since they are often aware of executives who had changed companies as well as new contacts at target companies.
Choosing the right vendors to help with this project was also essential, Balcerek said. One vendor, idExec, an online executive database company, had a "very high hit rate" against Unisys' lists.
Finding the right database appending vendor and taking other steps to ensure accuracy will greatly improve the reach of b-to-b marketers' databases, said experts at the National Center for Database Marketing 2006 conference in Orlando, Fla., last month.
Ruth Stevens, president of eMarketing Strategy, and Bernice Grossman, president of DMRS Group, shared results of a sample study comparing b-to-b database vendors, and gave tips on improving match rates and hit rates.
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First, the consultants recommended, seek out database marketing vendors that will effectively append your company's b-to-b list against other b-to-b addresses.
"The key element is to make sure they have plenty of b-to-b database experience, which is a totally different animal [than b-to-c]. Ask them for a list of fields they can append," Stevens said.
After choosing potential database marketing vendors, ask each of them to conduct a database appending test of around 10,000 names. "Most vendors are willing to conduct a free sample," Stevens said.
Seed the test list with some company names with which you are familiar, along with those of friends or colleagues, to evaluate the accuracy of the data that come back. Then give the vendors a few weeks to conduct their tests, Stevens suggested.
Once you have test results, compare match rates, hit rates, accuracy and price among the vendors, said Stevens and Grossman. Match rates are typically low for b-to-b databases, but a 50% match rate "is not unheard of," Stevens said.
To illustrate the value of database appending, Stevens and Grossman compared database marketing vendor services in a sample test, using an unidentified b-to-b client's list. Fields in the list of 10,000 files included: last name, first name, title, company, address 1, address 2, city, state and ZIP code.
Major database marketing vendors participated, including Equifax, infoUSA's Donnelly Marketing division and MarketModel, and appended several b-to-b database fields, including: SIC, franchise, headquarters, number of employees and number of employees local.
The vendors were able to match between 42% and 61.9% of the test company's list, "good percentages for b-to-b," Grossman said. The fields with the highest hit rates were: SIC, number of employees local and sales volume local.
In fact, even though the data were not "clean"—some of the information was likely out of date—Donnelley Marketing was able to match the most records in the test, at 61.89%, while Equifax matched 50.74% and MarketModel matched 42.15%.
To improve match rates, watch for company names written differently on different lists, such as "IBM" and "International Business Machines," Grossman said.