What if you knew the concerns that were uppermost in your customer’s mind, right now?
Or, which of the folks in your Eloqua database are most intensively researching the topic of the white paper you’re about to blast out — this week?
Or, best of all: Which Fortune 1000 companies are intent about buying something you have on offer — ASAP?
I recently learned these things actually are knowable, today, given just a few machine-learning algorithms and a database the size of a small outer planet.
As a former editor-in-chief and current content marketer, such news makes my heart race. Until now, even with focus groups and surveys, the best we could really do was guess what topics mattered to our audiences and what they’d like to learn. Now we have actual behavioral data.
And it turns out that Erik Matlick, a fellow I know from my past life as a Web publisher, is among those making it happen.
I’ve done business with Matlick over the years, despite which he still takes my calls. So I called.
Over many years, Matlick built a series of companies (MediaBrains, IndustryBrains and Madison Logic) that increasingly leveraged Web data to deliver value to Web publishers and their customers. Those companies were a series of learning experiences leading to his latest, Bombora — a kind of data cooperative among roughly 3,500 B2B publisher sites.
Bombora tracks the billions of interactions readers have with all those sites’ content every month. At the moment, Bombora is tracking between 700 million and 1.2 billion interactions every day, and can identify from which of roughly 1.8 million corporate entities those interactions emanate.
To make sense of it all, Bombora developed a single uniform taxonomy of B2B topics with about 2,800 leafs, which it applies to all the content in the cooperative, according to Rob Armstrong, the company’s head of product. “Imagine a leaf like ‘intrusion detection’ on a branch called ‘security’ off a major limb like ‘technology,’” Armstrong says.