Infer Raises $10 Million In Series A
Infer is a startup that works on helps companies win more business by offering data-powered decisions around who their highest potential customers are. Infer has announced today that they have raised $10 million in Series A funding, led by Redpoint Ventures. Andreessen Horowitz, Social+Capital Partnership, Sutter Hill Ventures, and several angel investors also participated in this round.
Infer uses data collected from the won/lost records in a company’s sales/marketing databases to make recommendations. The company uses hundreds of signals from untapped web sources to build statistical models about customers that have a high propensity to buy. One of Infer’s largest customers is Box, a file storage and solutions company. Some of the data utilized in the models include customer data, company financials, social media presence, job listings, legal filings, etc.
“Infer’s predictive solution has helped our sales force deal with lead overload by prioritizing those with the highest likelihood to engage and close,” stated Box’s EVP of sales Jim Herbold. “The application integrates quickly, and delivers real lift — in our case, more than doubling the conversion rate from our highest volume lead sources.”
Infer has customer agreements with multiple customers and has hit profitability. Infer was founded by Vik Singh, whom is known for helping create the open search platform Yahoo! BOSS. Other co-founders in the company include Yang Zhang and Chung Wu. Zhang previously worked at Google, Microsoft, and Yahoo! Wu used to be a front-end tech lead for the Google Public Data project.
“When my co-founders and I set out to create Infer, we were shocked by how poorly even the biggest, most innovative companies manage and act on their own internal data — especially given the amazing advances we’ve seen in the data science used for the consumer web,” said Singh in a statement. “For example, there’s way more intelligence being applied in Facebook’s newsfeed telling you that your friends are getting drinks across the street than there is in helping companies make critical decisions that could have serious consequences like massive layoffs. It’s time for a change. We intend to bring the product thinking and data intelligence of the consumer space to the enterprise, and deliver data science applications that solve real problems and ‘just work’ seamlessly in existing workflows.”