Data Network Effects
topic on 3 shows · 10 statements across 8 episodes
Lenny's Podcast 
the a16z Podcast 
20VC
10 statements about Data Network Effects, every show
Winters: Data network effects are underrated and widely misunderstood
“I still think data network effects are underrated. I think a lot of people confuse the idea of data network effects with data as a product you can charge people for, especially like businesses.”
Pande: Data network effects never go off patent like biotech drugs
“Data network effects never go off patent. They just get stronger and stronger and help companies grow even after, even decades after.”
Vijay Pande: Data network effects offer a permanent moat unlike drug patents
“The intriguing thing is about, ah, data network effect never goes off patent.”
Second-place players in data network markets drop to zero value
“And in fact, the value of the number two person goes to zero. Because they actually have a demonstrably poor product, which is why there aren't really any competitors to eBay.”
Premium pricing over competitors proves a true data network effect
“If you can really show that you're charging 20, 30, 40% more than the competition, that's a, and they're actually willing to pay for it, and they're switching from a lower priced product, either they're totally irrational, they say, hey, I want to lose more mo…”
Fragmented markets with equal competitors prevent data network effects
“You're never going to get to a network effect if it's a, if there are 25 companies doing exactly what you do, and they're all about the same size, and nobody gets the big, that nobody has like a just demonstrably better system, then the data is actually, it lo…”
Polovets: Data network effects build continuously, not overnight
“And I also think that most, like you mentioned, proprietary data and like data network effects, those things are not binary. So it's not like you don't have them on day 1000 and then you suddenly have them on day a 1001. And so they grow over time and the more…”
Data Network Effects Function Like Database Writes and Reads
“Think of it as a database with writes and reads. Those are the two actions that you typically perform in a database. As the number of writes goes up, the value of each read goes up as well, because the value of a read initially is close to nil, but as the numb…”
Sarver: Neural networks create compounding data network effects for incumbents
“Currently based on how neural networks work, that they require large data sets to be able to improve their models over time. And so therefore people with large data advantages can have better models, which then lead to better end products, which bring in more …”