HG Data (www.hgdata.com), a global leader in enabling B2B technology companies to target sales and marketing programs by the installed technology environments of their customers and prospects, announced it has secured $2 million in additional Series A funding led by venture capital fund Rincon Venture Partners, bringing its total Series A funding to $5.5 million. Also participating in the round was Epic Ventures, and several angel investors.
The funds will enable HG Data to exponentially accelerate customer acquisition with continued expansion into international markets and significant growth in its partner channel. The funds will also be used by HG Data to add more than a dozen engineers and data scientists to the team.
“At Rincon Venture Partners, we love to join forces with serially successful teams who have reunited to tackle markets in which they have previously experienced success. HG Data is the quintessential example of the type of investment we pursue: a talented, capital efficient team that has disrupted a long-standing market with an easy-to-use and difficult-to-copy solution, “ says John Greathouse, general partner, Rincon Venture Partners. “When the biggest players in your market begin aggressively courting you as a potential partner, you know you have arrived. We are honored to have a seat on the HG Data rocket ship.”
HG Data is the world’s only provider of targeting by installed technology with the scale, accuracy and detail required by the world’s largest technology companies, and now HG Data includes as customers more than 25% of the Fortune 500 software companies as well as more than 40% of the Fortune 500 hardware companies.
“Looking forward, HG Data will accelerate our creation and delivery of unrivaled market intelligence for our global technology clients and distribution partners, providing more and better data that is extraordinarily easy to use,” says Craig Harris, founder and CEO of HG Data. “HG Data is creating an entirely new category of global competitive intelligence through its machine learning algorithms which can derive competitive insights from the vast and largely unmined unstructured information that is contained across the open and archived web.”
Source: HG Data Press Release