By Kia Kokalitcheva. This article originally appeared on VentureBeat, May 20, 2014.
SAN FRANCISCO — A statistical model is not a product — yet.
Data nerds might be incredibly good at creating fancy datamodels and tools, but if they want to take those skills and create a company, they need to make sure they build an actual product that actual people want to use, says Scott Rainey, a partner at Redpoint Ventures.
“This isn’t about building a science project, it’s about building something that solves a business problem,” Rainey said during a panel discussion at our DataBeat conference yesterday.
Rainey, along with XSeed Capital’s Robert Siegel, Accel Partners’ Jake Flomenberg, and Data Collective’s Matt Ocko, discussed what it takes for a big data company (or entrepreneur) to capture their attention and investment, and also to make a real dent into the market.
The consensus: Even big data companies need to take a look at the market, realize they’re not alone, focus on shrinking their weaknesses, and create something that truly helps someone.
This is something we often hear in the context of consumer products: Do people really need yet another photo-sharing app or Uber-for-a-random-item?
Hint: no.
So this is an important moment for big data startups. You may have built some fancy data modeling tool, but why should any one of these venture capitalists give you their precious money? What problem are you solving and for what future customers?
You are just as much of a dime-a-dozen startup as the photo-sharing app if you can’t answer these basic questions.