OpenView, Data Point Capital Betting on Metrics in Fickle VC World
A quiet trend has taken hold in the world of venture capital. Call it the “Moneyball” approach, data-driven VC, or what have you: startup investors are increasingly using metrics, algorithms, and data science in an effort to support their portfolio companies, make better decisions, and gain a competitive edge.
This is neither surprising nor new. But recent developments have called further attention to the trend. Last week, Boston-based OpenView Venture Partners announced an unusual partnership with InsightSquared, a local startup working on business intelligence software.
OpenView (which is not an investor in InsightSquared) will provide the startup’s sales and marketing analytics software to its portfolio companies. In addition, OpenView Labs, the venture firm’s consulting and support arm, will use the software directly to try to improve its companies’ sales and marketing performance.
Financial terms of the deal weren’t given, but it sounds like a new way to benchmark OpenView’s investments, which are typically mid-stage tech companies looking to increase their annual sales from a few million dollars to $50-100 million.
“It’s part of a unique agreement,” says Fred Shilmover, InsightSquared’s CEO, “for a VC or private equity fund to have a strategic partnership with a software company to provide a product to them.”
He adds that data science is seeing “major interest from VC funds that invest heavily in tech and [software as a service] … They are becoming more and more data-driven because sales and marketing is more data-driven than ever, and analytics is critical.”
Investors from Google Ventures to General Catalyst have been using data on everything from companies’ revenue growth and customer sign-ups to social-media stats, market and competitive analyses, and founder track records to complement their intuitive skills in assessing people and business plans.
Indeed, the OpenView news comes on the heels of Bitly’s chief scientist, Hilary Mason, joining Accel Partners as a data scientist in residence. And at last week’s Data Driven Conference in San Francisco, partners from high-profile firms Andreessen Horowitz, Greylock Partners, and Khosla Ventures spoke on a panel about when it’s appropriate for investors to be data-driven, among other things.
Meanwhile, newer firms like Correlation Ventures, Palo Alto Venture Science, and Ironstone Group (a Bill Hambrecht-led venture fund that recently hired Thomas Thurston from Growth Science) have gained attention for their approach to using data and algorithms.
By the time the whole venture community is talking about an investment approach or sector, of course, it’s probably too late to cash in. Skeptics maintain that meaningful data on startups and markets is hard to come by—especially at early stages of investment—and that using algorithms to assess founders and management teams is folly.
But I get the sense that smaller, niche firms can still get a leg up using the metrics and market trends they have the most experience with. Take Data Point Capital, for instance, which invests in … Next Page »