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Lead Cloud on the Horizon

It’s the Catch-22 of B2B marketing: If you want lead quality, you probably have to sacrifice lead quantity; if you’re looking for lots of leads, quality’s out the window.

But that kind of thinking is a bit retrograde, says Amnon Mishor, founder of Leadspace, a company that describes itself as something like “Match.com for business.”

A traditional lead database isn’t going to cut it anymore because it doesn’t scale and it doesn’t pull in dynamic customer data. In Mishor’s view, the future belongs to something he refers to as the “lead cloud”—the real time and on-demand analysis of information gathered from the social Web and married to ideal buyer profiles. In other words, using Big Data analytics to get a bead on your leads before they even engage with you.

To get that done, B2B marketers need to model their ideal customers and think about investing in tech solutions to gather a volume of relevant data—and it all comes back to quality versus quantity, although from Mishor’s perspective, if B2B marketers get on the tech train (predictive analytics, machine learning, natural language processes, automation), “quality versus quantity” can easily become “quality and quantity.” No need to choose between them—which is good because one is just as important as the other. A quantity of bad data won’t serve your marketing goals; but too few leads, even if they’re of quality, won’t make an impact.

“If you can get rid of the junk, it’s good, but you must have the quantity, as well,” Mishor says. “Don’t believe any solution that tells you you’ll get a better lead base with Big Data analytics without scale.”

Take a traditional lead gen effort. Let’s say you’re trying to reach out to IT people. What do you do first? You hit up your database or you buy a list of however many thousands of IT job titles you think you’ll need. Then you try to market your product to them.

“When you just stick to inbound marketing, all prospects fill out the same form; they all choose from the same categories—‘Yes, I’m in IT;’ ‘Yes, I’m in marketing,’—but it doesn’t matter if they’re a consultant or if they’re high level or low level,” Mishor says. “In that case, all the leads just look the same.”

But if you’re making an effort to collect more nuanced data about prospects—culled from comments they leave on blogs, from what they tweet about, from what they share—you can go well beyond the job title to pull in information like seniority level, interests, whether a person is in a position to spend money with a vendor.

The same goes for qualified leads garnered from, for example, event attendance. When a prospect attends an event, it’s pretty clear he or she is interested in what you’re about, but that kind of lead is costly—maybe even hundreds of dollars each. By looking at what prospects say online, you can identify their interests and target them just as accurately—but infinitely more easily and cost-effectively.

It seems like the future of database marketing won’t actually include any databases—at least not in the conventional sense.

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