What top enterprise VCs are thinking, using data effectively, ethics, Light, and Flipkart
Top VCs on the changing landscape for enterprise startups
TechCrunch had our debut confab for enterprise types this week at Yerba Buena Center in SF, where we heard from Aaron Levie, CEO of Box, Apple VP Susan Prescott of Apple, and Microsoft Azure CTO Mark Russinovich. We were sold out, which perhaps isn’t all that surprising given the amount of interest in enterprise these days. Expect more events to come.
Our Silicon Valley editor Connie Loizos hosted a panel with leading enterprise VCs, and she selected the most interesting points from that conversation and from her calls with them for Extra Crunch members. Hear a bit from Jason Green of Emergence Capital, Rebecca Lynn of Canvas Ventures and Maha Ibrahim of Canaan Partners and what they are investing in these days.
And if you want to hear even more from Jason Green and yours truly, head over to TechCrunch’s VC podcast Equity, where we shot live from Yerba Buena along with host Kate Clark with a special focus on enterprise startups.
Maha Ibrahim: I feel like people are focusing too much on metrics and not as much on [the total addressable market]. We make money [when a startup strikes on a] huge, huge market.
But there’s [also] so much correlation between consumer and enterprise startups in that we want customers that love the product. We want customers that come back and come back and come back to us, without us having to pay for them to come back. So the equivalent in a consumer company would be me having to spend advertising dollars to acquire that customer again, as opposed to that customer just coming back because he or she loves what I’m doing. The same goes for the enterprise.
How early-stage startups can use data effectively
Silicon Valley may be obsessed with using data to improve startup outcomes, but the reality is quite a bit more nuanced. Koen Bok, co-founder of interactive design tool Framer, has put together an extensive guide here on how to to use data — and when not to.