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Summary:

Sales intelligence startup Infer is racking up customers and transactions for its software that analyzes thousands of data points in order to score potential leads on the likelihood they’ll convert. For some customers, the scores have become instrumental metrics.

Infer Co-founder and CEO Vik Singh
photo: Infer CEO Vik Singh

Infer, a Palo Alto, Calif.-based startup that helps businesses predict the best leads by analyzing their marketing and CRM data, claims its business is on fire since the company launched in April along with a $10 million venture capital investment. Customer bookings have doubled and the company is making 200 percent more predictions (tens of millions a month in total) for those customers, Founder and CEO Vik Singh told me.

Here’s a fast recap on the way Infer works: It takes lead data from CRM and marketing systems, analyzes it against thousands of external signals (e.g., whether the potential customers is hiring in a particular field, how big it is and its known buying habits) and then generates a score for each lead predicting the likelihood the customer will be able to convert them.

Infer has always had a good roster of users — Tableau, Jive, Box and Zendesk were among them at the time of launch — but word of mouth appears to be spreading as they find more and more uses for it. “We’ve kind of been going down [Highway] 101 here [and racking up customers],” Singh said.

That’s because Infer is now not just used for figuring out which leads to expend effort on, but for all sorts of things, he added. Some customers are using Infer to split leads among sales reps more fairly, while others are making strategic plans around when to approach certain leads.

The most interesting example Singh gave, though — and one that epitomizes the shift in the way some companies now prioritize data analysis over context-free numbers or gut feelings — is how Zendesk uses Infer’s scores as a way to measure the actual value of lead-generation efforts during board meetings. There’s no more boasting about generating 10 million leads if they came from some generic email lists and very few are ever likely to convert.

“If you do that today,” Singh said, “you’ll get laughed out by the board.”

  1. Interesting examples of using predictive analytics.

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  2. reeves dominik Monday, December 9, 2013

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