While b-to-b targeting models have traditionally been very simple and undiscriminating because of the lack of available data for business targeting, the emergence of Web- harvesting technology and new b-to-b data compilers may begin to change that.
Unlike the consumer marketplace, where marketers can purchase hundreds of different demographic and psychographic data points for targeting individuals and households, b-to-b marketers, on the whole, have a limited selection of available data for their direct marketing efforts. What we see are standard company attributes offered by traditional data compliers like D&B and infoUSA, which include criteria such as organizational structure, years in business, number of employees, sales volume and standard industry classification (SIC).
How has b-to-b data been gathered historically? Through yellow pages, public filings and millions of annual phone calls to businesses. This process requires long update cycles and leads to a limited number of collected attributes. Not exactly an optimal method.
Based on this shallow data, the average b-to-b marketers defined their prospects/customers by some combination of title code within company size (e.g., small/medium/ enterprise) and industry vertical (e.g., public/retail/financial). This segmentation implied that all companies within a certain industry and/or company size have the same needs and motivations. We all know this is not true. The other downside is that this simplistic view of the target audience does not provide any insight into how to craft marketing messages that will resonate with particular customers and prospects."
But now, with the emergence of the Internet, b-to-b data compilation is changing in useful and exciting ways; a new answer is within reach.
Companies of all sizes, from large enterprises to sole proprietorships, are establishing Web sites to promote their products and services. These Web sites contain very relevant information about each business, and this data can be accessed and gathered through Web harvesting, a technology designed to extract and store data from Web pages and Web servers. The wealth of company data that can be extracted from a Web site is astonishing.
The new breed of data compilers are taking advantage of this information and building large b-to-b databases with detailed business profiles. For example, a company like Netvention offers a long list of b-to-b attributes, which are gathered through Web harvesting and include items such as company name, address, and telephone/fax numbers; individual contact names and titles; business category; listing of products and/or services; e-commerce capabilities; Web site size, complexity, and popularity; Web site maintenance level and hosting arrangement; and underpinning technologies used to support the Web site.
Company attributes collected through Web harvesting can provide a wealth of insight regarding technology adoption and technology preferences at the organizational level. This is a huge benefit for small- and medium-sized businesses where technology attitude and culture vary greatly from one company to the other. They can also be used to predict behavior, such as likelihood to make a purchase through Web/catalog or likelihood to purchase different technology related products and/or services.
What does this all mean? A traditional b-to-b list—i.e., a house and/or compiled file—can be merged with a b-to-b database built through Web harvesting based on a company name and address match. By doing so, direct marketers can significantly enhance their targeting capabilities and go beyond SIC codes and company size.
Slavi Samardzija is a director of the Advanced Analytic Center in the Strategic Services group of Wunderman New York. His e-mail address is firstname.lastname@example.org.