Bad prospect data may be costing companies millions. At the same time, consumers are concerned about maintaining their privacy. The solution, according to representatives of Epsilon Targeting and Marketfish is respectful, effective data appending.
The problem, after all, is clear, according to an e-book announced on March 10. "Assessing the Impact of Dirty Data on Sales & Marketing Performance," a DemandGen report released in partnership with ZoomInfo, found many organizations are relying on prospect data that is 20 percent to 40 percent wrong. Plus, 30 percent of businesses have no strategy in place to update inaccurate or incomplete information.
"With eight out of 10 companies surveyed indicating dirty data is hindering lead-generation campaigns and two-thirds expressing concern that inaccurate databases are limiting their marketing efforts, data is no longer an issue companies can afford to ignore," according to the report.
The strategy companies should employ is data appending that preserves consumer privacy, say Don Hinman, senior vice president at Epsilon Targeting, a division of Irving, Texas-based data provider Epsilon, and Dave Scott, CEO of Seattle-based self-service lead generation platform provider Marketfish. Here are four of their tips for implementing that strategy.
1. Use "anonymous" non-personally identifiable information (PII).
Scott says some platforms allow marketers to filter by attributes "without exposing the underlying data."
Independent linkage systems, such as assigning numbers to prospects rather than names and addresses, can also work to maintain consumer privacy, Hinman says. Or companies can use data that includes consumer names and addresses along with other information, then discard the names and addresses after appending the files.
Marketers can also use “geo-aggregate” data, which don't include names and addresses, such as ZIP +4 information or non-PII facts gleaned from IP addresses in those areas, Hinman says.
Perhaps not surprisingly, though, data appending that originally includes name and address information tends to be more accurate. Hinman says the typical match rate of appended data to an existing file using names and addresses with cities and states results in a 90 percent to 95 percent append rate. But email, which often doesn't have a “terrestrial” name and address, fares worse—with a 25 percent to 30 percent match rate.