B2B Data: It's Not About the What, It's About the Why

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B2B Data: It's Not About the What, It's About the Why
B2B Data: It's Not About the What, It's About the Why

While B2C marketing has matured significantly over the past two decades, the B2B world remains stuck in the Stone Age, says Jim Swift, president and CEO of B2B insights provider Cortera.

“Companies are going through this process of trying to understand who their companies are [and] figure out how to get more like them, and they're still relying on demographic data largely,” Swift says. By contrast, B2C marketers have evolved past that stage and are now using online and purchase behavior data to make decisions.

Swift partially attributes B2B's late-bloomer development to the challenge of discovering innovative ways to describe businesses. Traditionally, these businesses use Standard Industrial Classification (SIC) codes, (which are four digit business identification codes assigned by the U.S. government), sales volumes, or employee headcount. Swift also says that the large number of privately-owned businesses, which aren't obliged to release financial figures, can also hinder business's abilities to build profiles and indentify prospects. According to research by Harvard University and New York University, there are approximately 6 million private employer firms in the United States. 

“I don't think any B2B marketer would tell you that they feel like they have a lot of information about companies. If you ask them how they segment, they would almost all say based on the industry the business is in and based on how big we think they are,” Swift says. “I think what they don't understand is how potentially inaccurate demographic data is. SIC codes apply very neatly to smaller businesses that tend to be highly specialized in old school industries, but if you're an Internet company, there's no SIC code that describes you. I don't think they've been updated in 20 or 30 years.”

To help B2B businesses evolve, Cortera has taken a stab at re-inventing the data-driven wheel by launching Lookalikes on March 19. Lookalikes automatically analyzes businesses' behaviors, such as previous purchasing habits, methods of payment, and recent hires, to compile a company profile. For example, Cortera might measure a manufacturer's postage rates or office supply purchases. Cortera then aligns the profile against its database of companies to find lookalike prospects that resemble current customers.

“Businesses have their own fingerprint – just like a person,” Swift says. “They're unique, and I think describing their behavior is a more accurate way of describing what's really going on for any purpose, whether I'm trying to market to them, sell to them, make a risk decision, [or] invest in them.”

Aaron Bolshaw, director of marketing and inside sales of financial reporting and transportation management company HA Advantage, says HA Advantage piloted Lookalikes a little over a year ago to save time building and identifying prospects. Given the specificity of HA Advantage's customers, wholesale distributors and manufacturers who ship less than a truck load, Bolshaw says finding potential customers was  “very labor intensive.”

“There's no place to get that information unless I were to go to the actual carriers and ask them for a file of the customers which....would never happen,”

Before implementing Lookalikes, HA Advantage had primarily been targeting prospects based on demographic data. Since employing Lookalikes, HA Advantage has been able to locate prospects six times more quickly, Bolshaw says.

By analyzing behavioral data, HA Advantage was also able to broaden its target audience. Bolshaw says that HA Advantage initially targeted more rural manufactures and distributors who were “off the beaten path” but realized their services appealed to those in metropolitan communities as well

“If an account or a business is growing, I'm going to have better success in that account,” Bolshaw says. “It's taking it from the box of eight colored crayons to the big, huge box of 120.”

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