Lattice Engines adds intent-to-buy to its prospect sifting

[Updated 5.14.15 4 p.m. PT with a comment from 6Sense.]

There are two words to describe B2B predictive lead scorer Lattice Engines‘ new direction, announced today.

New leads.

And the two words behind those words: Intent data.

“We are good at predicting who in your database will buy your products,” CMO Brian Kardon told me.

He’s referring to the corporate data clues Lattice has used to qualify which of those companies in your customer relationship management system are the best bets. A company’s new funding, its large purchase of servers, or its opening of a new office could indicate the need for, say, property insurance, storage systems, or office supplies.

Now the company is expanding into assessing new leads, possible customers that are not in your database.

To find them, marketers often buy lists and sift through them. Offering an alternative, Lattice is announcing today it is adding a new layer of signals called Prospect Discovery, which surfaces people who are searching for office equipment, for instance, or posting on social media for the best human resources software.

This kind of intent data is an early warning system for what a company’s employees are in the market for. By keeping track of corporate domains, Lattice can determine that three employees from Company X are researching the same products. Other data sources can include blogs, communications on LinkedIn, or searches on industry trade publications. Bombora (formerly Madison Logic Data), one of Lattice’s intent data providers, specializes in tracking white paper downloads, webinar and trade show registrations, visits to articles in trade publications, and the like.

Above: A Lattice Engines screen showing intent data.

Image Credit: Lattice Engines

Prospect Discovery is released today as a closed beta for selected customers, with general availability by late summer. Kardon said this additional data can bring 10 to 20 percent more leads.

This now gives Lattice three legs to its predictive lead stool — its previously existing firmographic (the corporate equivalent of demographic) profiles and behavioral data based on individual actions like website visits, and now intent data.

One kind of data could be insufficient, Kardon said. “If someone is searching for flash storage, but their credit rating just dropped, they don’t have the money” to buy your products, he said.

This combination of data for lead prospecting is new, he said. Speaking of predictions, Kardon predicted such predictive lead competitors as Infer and Mintigo will need three years or so to catch up.

However, 6Sense, another predictive lead scoring competitor, points out that they’ve been using intent data as a differentiator since their founding in 2013.