Dec 19, 2013 · 42m · mad
Fred Wilson, USV // Data Driven NYC #18 // Sep 2013 (interviewed by Matt Turck)
Fred Wilson · 28m spoken Matt Turck · 5m spoken Margaret Oest · 46s spoken Carl Angel · 45s spoken NYU Student · 26s spoken Victor Coppola · 21s spoken Gary Russo · 14s spoken
0:00 / 0:00
▶ Watch on YouTube →
gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this Data Driven NYC event hosted by Matt Turck, venture capitalist Fred Wilson of Union Square Ventures discusses USV's investment thesis on proprietary data assets, network effects, machine learning, and emerging opportunities in healthcare and decentralized finance.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 15.8% of the talking time here. How this is scored →
Matt as informed peer 3.1 Guest teaching 5.2 Guest disagreement 2.0 Matt pushing back 1.6
speaking balance: gold is Matt, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 25:01 Blunt rejection of defense tech
Fred shuts down an audience member's question about defense industry opportunities by explicitly refusing to back government spying, placing it alongside gambling and pornography.
Hardest push from Matt ▶ 11:01 Bloomberg counterexample challengeMatt directly challenges Fred's premise that businesses require proprietary data assets by pointing out Bloomberg's multi-billion dollar success aggregating third-party data.
Biggest teaching moment ▶ 11:21 Reframing Bloomberg's true moatFred re-educates the host on Bloomberg's business model, explaining that its actual defensibility stems from native messaging and transactional network effects rather than data aggregation.
Matt holds his own ▶ 11:01 Matt presses Fred on data ownership thesisMatt demonstrates sharp sector domain knowledge by raising Bloomberg as a prominent counterexample to Fred's thesis on external data aggregation.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Matt as informed peer | Guest teaching | Guest disagreement | Matt pushing back | Why |
|---|---|---|---|---|---|---|
| USV Thesis: Proprietary Data Assets and Network Effects | 4 | 5 | 1 | 1 | Matt sets up the discussion by referencing historical USV blog posts on proprietary data assets and asking how USV's focus evolved toward network effects. Fred explains how software alone offers no defensibility and uses an illustrative hypothetical story to highlight how native data assets create moat. | |
| Building Data Networks and the Edmodo Example | 3 | 4 | 1 | 3 | Matt probes Fred on whether open source communities constitute data networks. Fred candidly admits he lacks a bulletproof argument for open source data networks before detailing how portfolio company Edmodo built free network effects among teachers. | |
| Data Aggregation vs. Internal Messaging Networks | 6 | 6 | 3 | 6 | Matt directly challenges Fred's thesis by citing Bloomberg as a massive business built on aggregating external data rather than owning proprietary sources. Fred counters by clarifying that Bloomberg's true moat is internal messaging and transactional communications native to the terminal. | |
| Machine Learning Inflection and Twitter's Data Ecosystem | 4 | 5 | 1 | 1 | Matt asks about machine learning inflection points and highlights Twitter's role in open-sourcing infrastructure and providing data firehoses. Fred articulates three core architectural differences distinguishing Twitter from Facebook. | |
| Big Data in Healthcare and DIY Data Science | 3 | 4 | 0 | 0 | Matt references Fred's post on DIY data science and asks about USV's thesis on healthcare big data. Fred outlines USV's multi-year research approach and reflects on the absence of a central hub like GitHub for casual data hackers. | |
| New York's Data Science Advantages and Team Dynamics | 4 | 5 | 1 | 1 | Matt highlights New York's institutional university investments in data science and asks about early-stage startup team composition. Fred links NY's data roots back to 1980s Wall Street quants and advises that early consumer startups need great product builders over dedicated data scientists. | |
| Audience Q&A: Government Defense and Developer Infrastructure | 2 | 5 | 6 | 2 | During audience questions, Fred emphatically rejects defense and government surveillance investments, putting spying alongside porn and gambling as excluded categories. He also clarifies USV's focus on developer platforms rather than raw infrastructure tools. | |
| Audience Q&A: Evaluating Early Growth and Marketplace Networks | 1 | 6 | 0 | 0 | Audience members ask about growth metrics and marketplace dynamics like Lending Club. Fred delivers a detailed analysis on why marketplace networks must grow organically from grassroots users before institutional capital enters. | |
| Audience Q&A: Healthcare Opportunities, Bitcoin, and Transparency | 1 | 7 | 5 | 0 | Fred delivers an impassioned pitch on Bitcoin as the native programmable payments layer for the internet, while forcefully advocating radical data transparency in healthcare and criticizing governmental surveillance double standards. |
Statements from this episode (20)
Wilson: USV invested $2.5M in Indeed before its $1.4B acquisition
“We put two and a half million dollars into the company. That's all the money that they ever needed and They sold for a 1,000,000,004, you know, so you know, that's as good as it gets, really, in the venture business.”
Wilson: Data is only defensible if it is proprietary first-party data
“The only defensibility that you can get with data is defensibility around your own data. If you're getting data from somebody else, it's not defensible, because they can give it to somebody else as well.”
Wilson: Google search holds an almost insurmountable data advantage
“I would even argue that Google benefits from network effects and the data that they have that, in their search business, I think, almost an insurmountable advantage because of the data asset that they have. And the network effects around that.”
Wilson: Software alone lacks defensibility without proprietary data and networks
“Shows the problem of thinking that software is any kind of defensible advantage. I don't think it is. But if there was something about The data, ah, and the network around that software that made it so that it wouldn't be easy to leave the first company and go…”
Wilson: 5M teachers and 70M students use Edmodo in the US
“So today, four years later, five million teachers, seventy million students are using it in the K through 12 system here in the United States.”
Wilson: Bloomberg's main retention driver is native messaging, not market data
“The most important data which is the, Transactional and conversational messaging that goes on inside the platform is created natively for the platform and stays inside the platform. And I think that's the glue that keeps everybody on Bloomberg.”
Wilson: Startups should build platform services on data rather than sell raw data
“I don't think selling the data is the right thing to do. I think the right thing to do is to build services on your platform that take advantage of the data that let the people who might buy the data from you instead come and build businesses And transact on y…”
Wilson: Machine learning hit a major inflection point around 2013
“I think that machine learning is, has hit an inflection point in the past few years artificial intelligence, machine learning, whatever we want to call it To the point where, ah, we're starting to see, ah, these, ah, dreams that we've had for 30 plus years in …”
Wilson: USV avoids investing in 'pitchforks and shovels' big data infrastructure
“We are not investors in companies that are providing the pitchforks and shovels for the big data business.”
Wilson: Three core differences define Twitter versus Facebook
“I think the important ones are default public versus default private follower versus friending. One-way follow model versus a two-way following model. And open fire hose versus closed fire hose. I think those three things tell you everything you need to know a…”
Wilson: USV studied education for three years before investing in Duolingo
“We looked at education for about three years before we made our first education investment, and then we quickly made about five or six. So we have Edmodo, Duolingo, Codecademy, Skillshare, Stack Exchange, if you want to call that education.”
Wilson: Consumer internet startups should build simple products before data science
“In consumer internet, even if big data and machine learning is going to be the thing that ultimately locks in your value proposition for the long haul, I don't think you get into the market and get the scale position that allows you to access that data with da…”
Wilson: USV will not invest in porn, spying, or gambling
“I won't invest in porn. I won't invest in spying. I won't invest in gambling. Those would be three things I wouldn't do.”
Wilson: USV thesis targets developer platforms like Twilio and MongoDB
“We have started to have a thesis around platforms that developers build on top of. Twilio SIF Science Firebase, and MongoDB. So we do like to invest in platforms for developers.”
Fred Wilson: LendingClub operates at one-third the cost of traditional lenders
“Lending Club can do that at Maybe a third of the cost of what a traditional lender can do it at.”
Wilson: Bootstrapping marketplaces with institutional users instead of grassroots is a mistake
“When entrepreneurs come in and say, We're gonna bootstrap you know, one side of our market, the demand side or the supply side, by going to institutions or going, you know, kind of bypassing the little guy and going to large chunks of supply or demand. That al…”
Fred Wilson: Successful healthcare startups will bypass hospitals and insurance companies
“And I think what will work for us in healthcare is to service the doctors and the patients and ignore the hospitals and the, Insurance companies and all the big honkin' bureaucratic institutions in healthcare.”
Wilson discloses USV's early investment in crypto exchange Coinbase
“We're invested in a company, Coinbase, that does that stuff, and they're great, and I love it”
Wilson in 2013: All mobile and micropayments should run on Bitcoin
“So that's what's interesting to me right now in payments and it's not like mobile payments or micropayments. Like, to my mind, all that should be running on, on bitcoin.”
Wilson: User value and team quality matter more than early business models
“I don't care about the business model because we can tweak the business model. We can get the business model right. What I care about are do you have users and are they getting value out of your product and how much value they're getting out of your product an…”