Venture capital dollars are pouring into a new class of startups that provide data services to small and mid-sized companies. Their goal, in a nutshell, is to automate tasks once assigned to a data scientist or teams of technologists, making big-data capabilities possible for smaller companies.
The space is nascent, but one analyst pegs investor funding in data-related companies in the hundreds of millions.Israel-based SiSense set up shop in Redwood City, CA about a year ago and raised a $10 million Series B funding round earlier this month led by Battery Ventures, along with Opus Capital and Genesis Partners. "You don't need a PhD," the company says on its website, which touts its tools for "non-technical users to perform tasks that once required support from a team of database admins, engineers, and data scientists."
Another $10 million just went to Infer, a platform that tacks on unstructured web data to proprietary customer data, using predictive analysis to determine customer leads with the most potential. The system can be integrated with popular sales and marketing platforms Salesforce, Marketo and Eloqua. Infer's Series A funding round followed three years of development, and was led by Redpoint Ventures, and included Andreessen Horowitz, Social+Capital Partnership, Sutter Hill Ventures, and angels.
"Where are the killer applications that leverage data science but don't require you to be a data scientist to understand and run with?" asked Infer CEO and co-founder Vik Singh in an introductory post on the company's blog this week. Mr. Singh helped build the Yahoo BOSS open search platform and recently sat in as Entrepreneur in Residence at Sutter Hill Ventures.
DataGravity, which has collected $42 million from venture capitalists in the past year, aims to serve small and mid-tier companies, and foster "a new wave in the consumerization of IT." The firm's future clients don't have the luxury of hiring a data scientist, nor do they have the budgets to afford the often expensive and time-consuming consulting services and system integrations used by the P&Gs and Walmarts of the world, suggested president and co-founder John Joseph, who spoke with Ad Age after scoring a $30 million series B round of funding in January.
AgilOne calls itself a "data scientist in the cloud." The company grabbed $10 million in Series B funding led by Mayfield Fund, and joined by Sequoia Capital, in November. That brought its total funding to $16 million since 2011. The firm's platform integrates marketer data and analytics tools for clients such as PetCareRx and Sports Authority.
It's no secret that data scientists -- which tend to have computer science and engineering, statistics, or mathematics backgrounds -- are so hard to come by that their employers are in constant fear of them getting poached by rivals.
Tranzlogic provides a platform featuring aggregated transactional shopper data that is white labeled for end-use by merchants. The firm has yet to receive VC funding, and CEO Charles Hogan seems OK with that. "We probably get solicited twice a week," by VCs and investment bankers, he said. "We're positioned as financial services with big data and software-as-a-service combined, and then rapid scale, so we kind of hit on all the sexy hot buttons."
The "rapid scale" is possible because the company distributes its platform through credit card processors with lots of merchant clients. "I'm leery of all VCs. I'm a true entrepreneur and I'm leery of all investors," Mr. Hogan said.
Despite the frothiness, a data sector bubble is probably a ways off. While there's no question marketers of all sizes are moving towards employing more data analysis and related tools in their work, there's a steep learning curve among many, suggested Forrester senior analyst Rob Brosnan. The platforms offered by the likes of AgilOne, DataGravity, SiSense and Infer, will most likely appeal to small- and mid-tier marketers in part because they're software platforms, not hardware systems requiring additional staff. "It's very close to where an ordinary marketer lives," he said.
Brosnan said the amount of money flowing in from VCs to data companies is in the hundreds of millions of dollars.
When working with older firms such as Oracle, SAP, IBM and others that offer data services, marketers have "got to buy a ton of expensive hardware from these guys," said Mr. Brosnan. Generally speaking, he added, the more traditional hardware-based services "are not purpose-built to your use case as a marketer."
Most smaller companies "probably are just not going to even want to own hardware…or have the people or the time to build it," he said.
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