For as long as marketers have been compiling customer
records, those records have been inaccurate and incomplete. A retail marketing
executive, for example, recently said that in the process of cleaning up its
database the company discovered hundreds of customers with the same email
address: 123@aol.com. His anecdote elicited nervous laughter from many in
the audience as they recognized that their customer records were also in need of
some housekeeping.
Database integrity isn’t just a B2C issue, and the problem
can be even more complex in a B2B environment as people change jobs, titles or
responsibilities and records quickly become outdated. In addition, B2B buyers
are least as likely as B2C buyers to use tactics such as entering wrong emailaddresses or phone numbers to avoid a follow-up from a salesperson as they
research new products or services for their companies.
In response, marketers are developing strategies to bring
some order to their customer records, especially as more look to further tailor
their marketing messages to specific segments of their database.
“Data integrity is becoming a lot more top of mind thanks to
a greater proliferation of sales and marketing automation, and marketers now
look to further segment their campaigns by targeting multiple industries with
multiple products,” said Shawn Dyer, Director of Data Strategies for Televerde,
a B2B marketing agency that helps companies find and convert qualified buyers.
“This requires that the data be as clean and accurate as possible.
Metaphorically, those records have been up in the attic for a while, where they
were collecting dust and no one really knew what was there. Now they’re down on
the dining room table where people can get a better look at them.”
The Price Of Bad Data
A push for greater profitability and ROI is also spurring
marketers to focus on data integrity, Dyer said. “We’re seeing a real paradigm
shift in conjunction with the marketing department now owning at least a
certain portion of the revenue,” he said. “Marketers are asking themselves,
‘How much does bad data cost?’”
The answer, according to a recent survey by NetProspex,
is that poor records can significantly impact the cost and success rate of a
marketing campaign. For example, untargeted email programs cost more than three
times as much as targeted email campaigns, according to the company’s B2B
Marketing Data Benchmark Report, which found inaccuracies or missing data in a
sizeable number of the more than 100 million marketing records it examined. In
addition, companies that keep their data clean create seven times as many
inquiries as those that don’t.
The report also found that 71% of IT buyers surveyed refuse
to provide their real business email address when completing web registration
forms.
But not everyone has budgeted for maintenance and repair
because the costs are often invisible, experts said. “We just wonder why our
campaigns aren't performing and then buy more leads,” said Mary Firme, Chief
Lead Accelerator of ReachForce, a provider of cloud-based software
and lead data services. “We find that B2B marketers without a plan to clean
their dirty data may waste on average $80,000 to $90,000 for a database of
100,000 records. So it's a significant problem.
Data will always decay, said Michael Bird, President of
NetProspex. “Nearly 50 million people changed jobs in 2011,” he said. “People
register online with bad information. They don’t want to give up that
information.”
Bird said that marketers can use progressive profiling to
help counter the problem of incomplete records. The idea is to have the user
provide a little more information each time they fill out a form. “The key is
to keep it simple and don’t ask them to give up too much information all at
once,” he said. “In addition, you want to provide great content. People are
more willing to give up just a little bit of information if they are getting
some value in return.”
According to Bird, the first step to a cleaner database is
identifying the pain points – email, phone, company details, etc. – and
methodically addressing them. “Don’t try to do everything at once,” he said,
adding that it was important to determine the most important pieces of customer
data based on the company’s targeted audience, business goals and objectives,
and the methods of communication.
