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EverString has raised $12 million to help companies sell more stuff

EverString, a big data startup that helps companies identify prospective sales leads and new clients though predictive analytics, has raised $12 million in a series A funding round. Lightspeed Venture Partners led the round, which also included existing investors Sequoia Capital and IDG Ventures. While there are a host of marketing analytics services in the market like Silverpop and Eloqua that businesses use to aggregate numerous sales leads and find potential customers, EverString’s technology goes beyond whatever data is hosted internally within a company and branches out to the open web, explained EverString’s co-founder and CEO, Vincent Yang.

As organizations increasingly look for an edge to give their sales teams the best chance of success, the allure of big data and predictive intelligence becomes attractive. The promise of predictive intelligence for sales organizations is that it allows sales teams to chase the deals most likely to convert, or set their pricing at the most appropriate level. It’s a busy space with vendors like Infer,SalesPredict and Zilliant all delivering variations on this theme. Another one of these players is EverString, a company delivering an adaptive learning engine that is focused on helping organizations both identify and engage with their customers. EverString was founded back in 2012 and id today announcing a series A funding round. Lightspeed Venture Partners, along with participation from Sequoia Capital and IDG Ventures is shelling out some $12 million in an effort to give EverString the boost it needs. The timing of this deal is interesting – it’s only a few weeks since Salesforce.com announced its acquisition of RelateIQ. That deal was worth some $390 million and valued RelateIQ nearly 60% higher than it’s most recent funding round which, incredibly, closed only a few weeks before the acquisition.

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Written by Scarlett Madison

Scarlett Madison is a mom and a friend. She blogs for a living at Social News Watch but really prefers to read more than write. Find her on Twitter, Facebook, and Pinterest.

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