Data-Driven Arms Race for Customers Is Fueling Hot Enterprise Company Infer

Press Release: Infer Inc. Doubles Total Revenue Bookings in Six Months Since Launch this Year

PALO ALTO, CALIFORNIA – October 22, 2013Infer Inc., a company that delivers predictive applications to help companies win more customers, today announced it has doubled its customer bookings since launching in the end of April. Helping leading businesses like Box, Jive, Tableau and Zendesk accurately predict and act on their highest potential customers, Infer’s platform is now computing millions of predictive lead scores a month. Additionally, Infer’s product engagement has increased dramatically, with the company now computing 200 percent more predictions for customers than just six months ago.

Infer’s platform mines companies’ historical customer data, pulls in thousands of external signals from the web, and uses advanced data science to deliver actionable insights that help businesses prioritize their flow of leads and ultimately win more customers in less time.

When the company launched, Infer had already attained profitability and inked multi-year agreements with some of the fastest growing companies in the market today. Over the last two quarters, Infer has signed several new customers, including AdRoll, the most widely adopted retargeting platform,New Relic, the most popular application monitoring service, Nitro, an acclaimed PDF tool provider, Xactly, a fast-growing SaaS sales performance management solution, Xamarin, a hot mobile development framework company, and numerous other high growth businesses.

One customer benefiting immensely from Infer’s accurate customer predictions and external web signals is Tableau, which will be sharing details about its lift story with Infer during this week’s Eloqua Experience conference at 11am PT on Friday, October 25th. “We love data – Infer helps us be smarter with it. It would have been nearly impossible for us to discover the powerful signals Infer crawls from the web. Now, our marketing investments can work harder and produce bigger pay-offs,” said Elissa Fink, CMO at Tableau Software.

To support its growing customer base, Infer has aggressively built out the company’s engineering and sales teams, doubling its all-star staff with several top caliber engineering hires. Infer has hired eight-year Google veteran and double-digit patent holder Cassie Doll; founder of a machine learning company acquired by Facebook, Joe Gershenson; MIT PhD candidate (dropout) formerly at Microsoft, Meelap Shah, and many other talented employees since raising $10 million in Series A. The company also hired Jamie Grenney, an eleven-year veteran of, as its VP of marketing.

“We’ve been very fortunate to draw so many brilliant technical minds away from the consumer Web and into the enterprise space,” said Vik Singh, co-founder and CEO of Infer. “No one has yet been able to build a repeatable, intelligent, consumer-like solution for any function of the enterprise – and that’s exactly what we’re doing for sales and marketing. We’re bringing the predictive power of Google to every business out there so we can help them grow faster, while fueling an arms race powered by data.”

About Infer
Founded in 2010, Infer delivers data-powered business applications that help companies win more customers. It leverages proven data science to rapidly model the untapped data sitting in enterprises, along with thousands of external signals from the web. Inspired by the simplicity of the consumer web, Infer delivers seamless, cloud-based applications that anyone can get up and running in just days. Customers include several of the Fortune 1000 and numerous high growth companies like AdRoll, Box, Jive Software, New Relic, Tableau, Xactly and Zendesk. Headquartered in Palo Alto, California, Infer is funded by leading investors, including Redpoint Ventures, Andreessen Horowitz, Social+Capital Partnership and Sutter Hill Ventures. For more information, visit or read the company’s blog at

Transform Your Pipeline Today

See Firsthand How Infer Uses Your Own Data To Create Custom Scoring Models