A high-quality B2B prospect
database can dramatically improve lead conversion by up to 260%. Eloqua
In Part 2, I described how to
build a B2B prospect database from the ground up. However, it’s more likely that your
initial experience will be inheriting a database that someone else has built.
If you’re lucky, it will be well built and well maintained. If not, you’ll have
to overhaul it before you can use it to effectively power a direct digital marketing
program that will fill the funnel with sales leads and opportunities. Here are the
most frequent problems and how you can correct them.
Data Input Policy
Most databases are populated
from multiple sources, primarily sales and marketing personnel. Without a
policy for examining, culling and amending incoming information, you are likely
to populate your database with a significant percentage of non-prospects.
For example, an audit I
conducted at one company showed that the number of accounts in the database was
about twice the estimated number of accounts in the global market. On the surface,
this appeared reasonable, because it was a fast-growing emerging market. However,
a closer examination of accounts by geography showed that one region had five
times more accounts than the estimated number in the region. Furthermore, many
of the accounts had no contacts, making them useless for
direct marketing purposes. Investigation showed that a salesperson in the
region routinely pulled attendee lists from seminars, trade events and professional organizations in the region and had a sales administrator input the accounts
into the database—even though many had little relationship to the target
market. The lack of a policy regulating database input had resulted in almost 70%
of the regional data and 25% of the total database account information being of
no marketing value.
Salespeople are a great
source of prospect account information. But there should be a data entry policy
whereby 1) all incoming data is examined, 2) irrelevant accounts are culled and
not added to the database, and 3) relevant accounts are appended to provide complete
and accurate contact information (ideally, three to five people who are members
of the buying team). This function is best performed by an administrator with
overall responsibility for the database and the direct digital marketing
campaigns. While this is more time consuming and initially more costly than
simply dumping companies and institutions into your database, it is less time
consuming and costly than cluttering your database and marketing to accounts
that aren’t remotely prospective buyers.
Effective database management begins with a data entry policy to ensure account and contact information integrity.
Sales is not the only
culprit. Marketing can cause the same problems by sourcing low-quality lists,
and adding the information to the database without using the same three-stage
process (examine, cull and append). In my conversations with marketing managers
at different companies, I’ve learned that most of the lists acquired from
low-cost offshore sources contained a high degree of account and contact information
that, upon investigation, was incorrect and of no value. Regardless of
where you source your lists, include an initial test phase where you take a
small, manageable number of account contacts and verify that the information is
accurate and the contact is a qualified prospect. Although I usually acquire lists from higher quality sources, I always do this before I
enter into a large volume sourcing agreement with any company. And I also conduct
ongoing testing of random samples to verify that quality is maintained.
Regardless of how inaccurate
data got into your database, the only remedy is to do what should have been
done initially: examine account and contact data, remove irrelevant accounts
and append contact information for relevant accounts. In the example I
referenced, we examined all accounts that had no contact information or only a
single contact. Irrelevant accounts were removed, while contacts were corrected
and new contacts added for relevant accounts.
Quarterly Database Maintenance
Industry estimates indicate
that the contact data in a B2B prospect database decays at a 25% to 30% rate
every year, primarily due to contacts' job changes. Without a periodic database
maintenance program, over half the information in your prospect database can be
inaccurate within 2 years. This can make your direct marketing programs largely
ineffective.
I’ve used, and I strongly
recommend, a quarterly database maintenance program that combines automated and
manual processes for cleansing, appending and refreshing database records.
Cleansing identifies duplicate and incomplete records.
Automated de-duping of names, titles and companies repeated in inconsistent
ways should produce a single record with current, accurate information. Manual
inspection and verification may be required to correct some records.
Appending may be required to add missing information, such
as email addresses or phone numbers. Some of this information may be available
and accessible from other records through automated methods, but manual
processes are often required.
Refreshing helps to remove records that are outdated or
invalid, and, where available, replaces them with new records with accurate
information.
Quarterly database maintenance cleanses, appends and refreshes account and contact data to maintain database integrity.
CRM Disambiguation
The customer relationship
management (CRM) database is the central repository for most company’s customer
data. However, the CRM usually serves several masters, including sales,
customer billing, customer support and marketing. Each function has a slightly different
use for the database.
Billing is primarily concerned with present customers (as opposed to prospective
customers and past customers) across the business enterprise.
Service is primarily concerned with present and past customers across the
business enterprise.
Sales
personnel are primarily concerned with present customers (account management)
and prospective customers (to meet forecasts and quotas), but with a more
narrow focus (region or territory) than the enterprise (exception for the top
sales executive).
Marketing
is primarily focused on generating demand with new, prospective customers or
selling new products or services to present customers, but with an ability to
segment prospects and customers for targeted direct marketing campaigns.
CRM setup should support customer data use by all enterprise business functions.
If the CRM system setup is properly
planned, it can effectively support all of the functions. However, if the CRM
setup is skewed for one function, its ability to support one or more of the
other functions may be compromised. For example, one company I worked with had heavily
modified its CRM to accommodate a highly customized billing process. The modifications
essentially transformed the CRM into a hybrid ERP, which met many of the
billing and business operation requirements, but limited the CRMs ability to
support marketing campaigns. A marketing automation system was selected that
provided the capability, but without such a workaround, the direct digital
marketing program would have been limited and much less effective.
The Misleading Illusion of Data Quantity
Database management is about
optimization, not maximization. Too many irrelevant, inaccurate or incomplete
records in your prospect database are almost as bad as too few. Not only do
they occupy unnecessary storage space and needlessly consume computing power; they
can mislead executives in their analysis and planning.
For example, one company
continually missed its quarterly bookings target. The company had over 3,700
accounts in its database, which should have been more than sufficient to meet
the quarterly targets. Upon investigation, there were only 1,000 to 1,200
target accounts globally, growing at about a 30% rate annually. And the
3,700 accounts in the database only included about 40% to 60% of the target
accounts. Furthermore, over 300 of the accounts had no contacts, and of the over
20,000 contacts in the database, only about 8,500 had complete
information. Finally, there was no maintenance program in place, so it was unclear
how much of the contact data was accurate. The database was completely
overhauled over the next 4 to 6 months to acquire and append complete and accurate contact
information for target accounts. As a result, we produced twice as many sales
opportunities as the prior year—less data of higher quality doubled the
results.
Putting Your Database to Work
Now that your database is
shipshape, it’s time to set sail with a direct digital marketing program that
will engage prospects, nurture them through the early phases of the buying
process, and deliver well-qualified opportunities to sales at the right time in
the buying cycle.
Part 4 looks at developing
the right assets for digital direct marketing campaigns.
