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B2B LEAD GENERATION
One consequence of Big Data and marketing automation is the exponential growth in the number of leads. On any given day, a large company might have tens of thousands of interactions with potential customers, everything from ready-to-go buyers calling into sales to interested observers downloading a white paper for their boss.
It's easy to know how to handle the hot leads; you sell them. And it's easy to know how to handle the truly horrible leads, including the bots, and spammers and incentivized leads; you delete them. But what about the vast gray area in between, those thousands of touches that might someday be sales but aren't quite there yet?
The answer isn't so simple.
The first step, say experts in lead qualification, is getting sales and marketing to agree on how to define optimal leads in the first place.
“Marketers who try to define the optimal lead on their own are making a mistake,” said Jason Hekl, service director-demand creation strategies at SiriusDecisions Inc., the company that developed the “demand waterfall” for lead scoring and management. “Defining lead qualification criteria should be a collaborative effort by marketing and sales, which often means balancing what sales wants against what marketing can deliver.”
The driving metric for lead qualification should be sales conversions, Hekl said, not meetings taken, for example, or any other activity that doesn't directly affect the bottom line.
“You have to look at whom you're actually selling to,” said Dave Green, director of marketing partnerships at researcher Meclabs. “If lead scoring is out of touch with the ideal customer, you have to fine-tune it.”
Once the key customer profile has been built, marketers can match this ideal against the leads coming in and decide how to handle them based on their resemblance to that ideal.
“Lead nurturing should start once a lead is generated, and it's even more important for suboptimal leads,” said Frans Van Hulle, CEO at ReviMedia, a maker of automated lead generation and lead sharing platforms. “The ultimate goal is to cultivate leads and create more engagement, so it's important to collect as much information as possible about users to help them make a buying decision.”
During the lead-nurturing phase, a successful marketing department will be able to convert the suboptimal leads to stronger ones while wasting a minimal amount of time and energy on poor ones. The key to this, Hekl said, is to base predictive lead models on real-world behavior.
“I agree that lead scoring is underutilized and overcomplicated for many large organizations,” he said. “One problem is that marketers are designing lead-scoring models to identify prospects who will agree to take an appointment when they should be using scoring to identify the prospects who will drive revenue.
“Too many marketers fail to do the analysis first and base their scoring models entirely on assumptions,” Hekl said. “Then they turn on those scoring models without first running simple simulations.”