Startup C9 Raises $12M for Big Data Analytics
Big Data has been showing up on lists of hot business intelligence (BI) trends for years now – including this list of top BI trends for 2013 published by Enterprise Apps Today earlier this year. And Gartner has predicted a big future for Big Data. Still, hype has lagged reality.
Judging by the numbers of Big Data startups raising venture capital, however, this could be the year Big Data really takes off.
The latest is C9, a company that uses a cloud-based Big Data platform to power its software that analyzes and optimizes revenue across marketing, sales, service and support. The startup received a $12 million Series D round led by existing investors Mayfield Fund, InterWest Partners and Leapfrog Ventures, bringing its total raised to $40 million. The cash will be used for sales, marketing and engineering initiatives.
The company also announced its appointment of Greenplum veteran Michael Howard as chief executive officer. In addition to Greenplum, the Big Data division of EMC, Howard held executive positions with Ingrian Networks (acquired by Safenet), Outerbay (acquired by HP), Veritas and Oracle, where he led the acquisitions of Thinking Machines, OneMeaning and Carleton Corporation.
“C9's differentiation is its ability to capture large volumes of data — at incredible speed — and use predictive analytics to identify trends that pinpoint what deals are likely to convert into revenue,” Howard said.
Bruce Cleveland, general partner, InterWest Partners and former senior vice president of Products at Siebel Systems, lauded Howard's “Big Data expertise and savvy leadership skills,” saying they are “exactly what the company needs to scale to the next level.”
New Analytics Apps
C9 also unrolled two new analytic applications: Active Forecast and Active Insights, and new capabilities to its C9 Active Data Platform.
According to the company, C9 Active Forecast combines historical pipeline trends with sales judgment to enable sales people, sales managers and sales operations to accurately predict deal close rates, resulting in more accurate forecasts. It addresses enterprise sales requirements including support for deal splits and overlay organizations. Because it automatically inherits the sales hierarchy from source CRM systems, the solution is quick to deploy.
C9 Active Insights gives users prebuilt, ready-to-use dashboards and reports that highlight key changes in pipeline, scan the C9 Active Data Platform for specific events that may indicate potential pipeline risk, and automatically notify relevant parties. C9 Active Insights can be customized using point-and-click tools to change the layout or data in any dashboard or report. It can also be used across a range of platforms including mobile phones and tablets.
C9 also introduced 27 new platform capabilities in the C9 Active Data Platform, including real-time, device independent reporting, performance improvements in data replication and query optimization, real-time push notification on deals to watch, and new transparent data exchange for spreadsheet reporting.
C9 says it currently manages $1.8 trillion in pipeline for companies around the world, including Box, LinkedIn and Stanley Black & Decker.
Among dozens of others Big Data startups that have raised venture capital in 2013 are: RelateIQ, which raised $29 million for its relationship management platform; WibiData, a company that develops Big Data apps for industry verticals and nabbed $15 million; and Skytree, which raised $18 million for its solution that applies machine learning principles to Big Data sets.
Drew Robb is a writer who has been writing about IT, engineering, and other topics. Originating from Scotland, he currently resides in Florida. Highly skilled in rapid prototyping innovative and reliable systems. He has been an editor and professional writer full-time for more than 20 years. He works as a freelancer at Enterprise Apps Today, CIO Insight and other IT publications. He is also an editor-in chief of an international engineering journal. He enjoys solving data problems and learning abstractions that will allow for better infrastructure.
