B-to-B Prospecting Data Just Keeps Getting Better

The most reliable and scalable approach to finding new B-to-B customers is outbound communications, whether by mail, phone or email, to potential prospects, using rented or purchased lists. B-to-B marketers typically select targets from prospecting lists based on such traditional variables as industry, company size and job role, or title. But new research indicates that B-to-B prospecting data is much more detailed these days, and includes a plethora of variables to choose from

The most reliable and scalable approach to finding new B-to-B customers is outbound communications, whether by mail, phone or email, to potential prospects, using rented or purchased lists. B-to-B marketers typically select targets from prospecting lists based on such traditional variables as industry, company size, and job role or title. But new research (opens as a pdf) indicates that B-to-B prospecting data is much more detailed these days, and includes a plethora of variables to choose from—for refining your targeting, or for building predictive models—to pick your targets even more effectively.

My colleague Bernice Grossman and I recently conducted a new study (opens as a pdf) indicating that B-to-B marketers now have the opportunity to target prospects more efficiently than ever before. In fact, you might say that business marketers now have access to prospecting data as rich and varied as that available in consumer markets.

To get an understanding of the depth of data available to B-to-B marketers for prospecting, we invited a set of reputable vendors to open their vaults and share details about the nature and quantity of the fields they offer. Seven vendors participated, giving us a nice range of data sources, including both compiled lists and response lists.

We provided each vendor with a set of 30 variables that B-to-B marketers often use, including not only company size and industry, but also elements like the year the company was established, fiscal year end, Fortune Magazine ranking, SOHO (small office/home office) business indicator, growing/shrinking indicator, and other useful variables that can give marketers insight into the relative likelihood of a prospect’s conversion to a customer. We learned that some vendors provide all these data elements on most of the accounts on their files, while others offer only a few.

We also asked the participating vendors to tell us what other fields they make available, and this is where things got interesting. In response to our request for sample records on five well-known firms, the reported results included as many as 100 lines per firm. Furthermore, two of the vendors, Harte-Hanks and HG Data, supply details about installed technology, and their fields thus run into the thousands. The quantity was so vast that we published it in a supplementary spreadsheet, so that our research report itself would be kept to a readable size.

Some of the more intriguing fields now available to marketers include:

  • Spending levels on legal services, insurance, advertising, accounting services, utilities and office equipment (Infogroup)
  • Self-identifying keywords used on the company website (ALC)
  • Technology usage “intensity” score, by product (HG Data)
  • Out-of-business indicator, plus credit rating and parent/subsidiary linkages (Salesforce.com)
  • Company SWOT analysis (OneSource)
  • Whether the company conducts e-commerce (ALC)
  • List of company competitors (OneSource)
  • Biographies of company contacts (OneSource)
  • Employees who travel internationally (Harte-Hanks)
  • Employees who use mobile technology (Harte-Hanks)
  • Links to LinkedIn profiles of company managers (Stirista)
  • Executive race, religion, country of origin and second language (Stirista)

Imagine what marketers could do with a treasure trove of data elements like these to help identify high-potential prospects.

Matter of fact, we asked the vendors to tell us the fields that their clients find most valuable for predictive purposes. Several fresh and interesting ideas surfaced:

  • A venture capital trigger, from OneSource, indicating that a firm has received fresh funding and thus has budget to spend.
  • Tech purchase likelihood scores from Harte-Hanks, built from internal models and appended to enhance the profile of each account.
  • A “prospectability” score custom-modeled by OneSource to match target accounts with specific sales efforts.
  • PRISM-like business clusters offered by Salesforce.com (appended from D&B), which provide a simple profile for gaining customer insights and finding look-alikes.
  • “Call status code,” Infogroup’s assessment of the authenticity of the company record, based on Infogroup’s ongoing phone-based data verification program.

We conclude from this study that B-to-B prospecting data is richer and more varied than most marketers would have thought. We recommend that marketers test several vendors, to see which best suit their needs, and conduct a comparative test before you buy.

Readers who would like to see our past studies on the quality and quantity of prospecting data available in business markets can access them here. Bernice and I are always open to ideas for future studies. We welcome your feedback and suggestions.

A version of this article appeared in Biznology, the digital marketing blog.

Marketing Data: Do I Own My Own Name?

I’ve always been uncomfortable with the position taken by some privacy advocates that each of us owns our own information—and thus has some form of property rights derived from this information—and that marketers shouldn’t have use of that information without first having permission and providing compensation

I’ve always been uncomfortable with the position taken by some privacy advocates that each of us owns our own information—and thus has some form of property rights derived from this information—and that marketers shouldn’t have use of that information without first having permission and providing compensation. To this, I say—hey OK, but let’s be pragmatic.

Certainly, if I’m a celebrity, where my name and likeness has commercial value, perhaps as an endorsement, such an “ownership” rationale is a valid one.

But in the exchange of customer data for marketing purposes, this argument lacks merit, in my opinion. The value of my name on a mailing list, for example—mail, email, telephone, otherwise—has nothing to do with “my” name being on the list or, for that matter, “your” name being on that same list. (Even when we are both see ourselves as celebrities.)

Rather, the value of both our names being on the same list is by knowing the shared attribute that placed us both there—alongside the thousands of others on that list. In the world of response lists, it’s the sweat equity of the business where you and I both chose to become a customer that deserves the compensation in any data transaction, as it alone built the list by building a business where you and I both chose to become customers.

Yes, that marketer must provide notice, choice, security, sensitivity, marketing data for marketing use only, and perform other ethical obligations that are part of the self-regulatory process that have governed this business for nearly 50 years—recognizing that customer data is our most important asset, and that consumer trust and acceptance serves as the foundation of the data-driven marketing field. Privacy policies, preference centers, in-house suppressions and DMAchoice collectively serve the consumer empowerment process by enabling transparency and control in this data exchange.

In the world of compiled lists, where third parties assemble observed data for marketing purposes, again there is the sweat equity of the entities assembling and analyzing that data to “create” or “discover” the shared attributes of that data. Knowing these attributes is where the combined data derive their value. Marketers deploy activity based on these attributes to generate commerce. While the relationship between individuals and these third parties may be indirect, we still have the same ethical codes and opt-out tools governing the process. Recently, in the case of Acxiom, we’ve seen such a data compiler working to establish a direct relationship with consumers, providing individuals with the ability to inspect the data the company holds and to suggest corrections—as if the firm were a (highly regulated) credit bureau. (It is not.)

The fact that my name—Chet Dalzell—is on both response and compiled lists, to me, doesn’t entitle me to anything except to expect and demand that these movers of data act as responsible stewards of this information using well established ethics and self-regulatory methods. (Granted, in the US, there are legal requirements that must be met in such sensitive areas as credit, personal finance, health and children’s data.)

This flow of data, as the Direct Marketing Association most recently reaffirmed, generates huge social and economic value—and, in my view, my own participation as a customer in the marketplace is my agreement to allow such data exchange to happen. In fact, were it not for such flows, I might never have been provided an opportunity to become a customer in the first place. Benefits to consumers accumulate, while harm is nowhere part of the marketing ecosystem—other than to protect from identity theft and fraud. I find it fascinating some would-be regulators fail to grasp this truth.

That’s why inflexible government regulations—and opt-in-only regimes—and technology strictures that interfere with my interaction with brands are so troublesome. Such restrictions may claim to be about privacy; more often than not, they’re really motivated by political grand-standing, anti-competitive business models, and the forced building of new data siloes that do nothing to advance consumer protection—and potentially ruin data-driven marketing.

Yes, I own my name—and by choosing to be a customer of your brand, so do you own your customer list. Of course, I am the ultimate regulator in this process. For whim or reason, I can choose to take my business elsewhere.

Now, what about my Twitter, Facebook, Google and Yahoo! profiles?