You're listening to episode 1, why network effects are mission critical from the network effects masterclass Pete on the NFX podcast to watch the course visitnfx.com/masterclass. So the world can often seem chaotic, but underneath that apparent complexity, there's actually some wonderful simple math. And once you see it and understand it, the world it's calmer, and you can follow that math to your destination.
If you're gonna be spending your life's energy is building a startup, it's gonna take a 100% of your effort. You're trying to defend the business area that you've carved out. You might as well be working on a business that has network effects because then you'll have a shot at going the distance and making a real impact in the world and creating true value for your employees, for your investors, and for your whole net. I'm James Currier, and welcome to the Network Effects MasterClass.
Over the last 20 years, we've built 10 companies that have most of which also had network effects. Companies you've heard of like Lyft and DoorDash and Pete and good reads that use network effects to grow and build their defensibility and went on to great success. So we've seen the failures and the successes. We've seen the tactics and the details of what it takes to grow these network effects.
And with all that company building, with all those investments, what we noticed was that when the companies had real network effect, their success was 10, 2030x what companies were when they didn't have network effects. It was the most important fact in determining what would be a successful startup and what wasn't. In fact, between 2012 2018, we studied it. We kept track of it.
And notice the math is that 70 percent of all the value created in the technology sector is created by companies with network effects, and only 30% was created by companies without network effects. And once we saw the network effects playing out in these startups, it was clear to us that they were also playing out and how our lives went and how politics was going and how economics actually worked. We started seeing this everywhere. Once we saw it, once we understood it, we couldn't unsee it.
And that's why we're doing this master class for you. Once you learn this way of seeing, you will not be able to unsee it. You will see these patterns everywhere And the world that looks kind of chaotic on the surface is actually not as chaotic. It's actually quite understandable once you understand the network principles. We're gonna teach you about the tactics and the nuances, all the different types of network effects.
But the fundamental idea about network effects is that the more users a product has the more value every user gets from that product. That's the kernel of the idea of network effects. Now how that blossoms and flowers and its multiplicity of, of expressions, you will learn in this master class. Okay. So let's get started. You know, network effects are important. Because they're really at the engine of what's creating economic wealth in the world today.
They're at the engine of how politics works, how society works, economics works, yet so few people see them and understand them. It's like this hidden engine of the world that people aren't discussing, and we'd, we hardly have the language for it. And so what we want to do is bring out that language, bring out that understanding. You know, I first learned about network effects in 2004. I sold my first company tickled to monster.com.
And we were a fast growing user generated content site with matchmaking and social networking and test taking, a lot of user generated content. We were bought by this $7,000,000,000 company. And when we got there after we'd been acquired, we realized that they were horribly run. The way they talked to each other, the processes they had in place, the metrics they were using were inferior to the way we were doing it. Yet they were buying us and not us buying them.
And what we realized is the reason they were able to do that was because they had stumbled into a network effect in 1997. And that network effect allowed them to run the company horribly, but still make a $1,000,000,000 in revenue a year, and they could go to sleep, and they would wake up the next day and their business would still be there. And when we saw that, we realized we gotta study this stuff. We've got to understand what makes this work because we've discovered something important.
You list out the companies you admire. You list out the companies you think have impact. I will bet you they've got network effects in them. Salesforce even developed a network effect over time, even though they started without 1. Very impressive. Apple started without 1. Eventually, they got to iOS. Eventually, they got to their network effect businesses. And now they went from 40,000,000,000 to almost 2,000,000,000,000 in value built on top of these network effects.
We saw the pattern again and again, and that's why we called our firm network effect And that's why we've been publishing about it for the last few years. These things are incredibly important to value creation. You're trying to defend the business area that you've carved out. And the network effects are the best way to do that in the digital age. Durable competitive advantage. Where is that gonna come from?
Gonna come from 4 different defensibilities, but generally, it's gonna come from the greatest of those, which is network effects. We wanna be very clear in this master class about what network effects are and what they're not. They are not viral effects. Viral effects are things like candy crush and whatnot, where your existing users send out the product to another user, and you get a new user for free. And those are very exciting, and there are playbooks for viral effects.
But they aren't network effects. Network effects are about defensibility and retention. So the core idea of network effects is that every new user who joins a product increases the value of that product to every other user. Because of that value, they just won't leave. Okay? That creates stickiness. That creates defensibility. That creates longevity, which creates most value in startups in the long term. That's not virality.
You're going to learn that not all network effects are created equal and that not all nodes on your network are created equal. And you're going to learn to differentiate the different types of network effects and the different types of nodes that are gonna be on your network. You're gonna learn tactics for how to manage or grow each of your network effects. And tactics for how to bond each of these nodes onto your network. So network effects have always been important.
1000 years ago, you would have a marketplace where buyers and sellers would come, and the more buyers and sellers that came, the more value everyone would get out of it, and so more would come. That's a basic network effect. So we've always had network effect. You then move on to things like AT and T, which was the first time it was really written about in 1907.
The chairman of AT and T says, you should probably buy our stock because once we go into a town and we establish a network of telephones, once we get seven or eight people on that network, no one seems to be able to compete with us because everyone wants to join the biggest network available. The more people using the telephone, the more valuable the telephone becomes. The more valuable AT and T. So we kinda said, you should probably invest. This was the first time it was written about.
So then fast forward to 1976 when Microsoft stumbles into an operating system platform network effect, what we call a platform 2 sided platform network effect. They didn't know what it was. They'd never seen it before, but they stumbled into it, and it was incredibly durable because the more people they had using their OS the more people wanted to build software on top of their OS so they could get access to the market of people who are already using that OS.
And the more software was built on top of that OS, the more those people wanted to adopt the OS. Fast forward to 1998 when Microsoft is so powerful with this network effect, and all of their competitors are screaming bloody murder that they can't compete with these guys. No one understands why. So the Department of Justice in the state starts investigating Microsoft and looking to break them up because they're starting to appear like some kind of a monopoly.
The academics started studying network effects They started writing about it. People were trying to pull from the air. What is going on here? Why is this company so powerful?
Now once the DOJ decided not to break up Microsoft, A lot of the investigation into network effects really died down, but starting in 94 because of the internet, It's like the tide went out, and we could see the rocks, and we could see the things underneath the water for the first time because the internet made it possible to measure and to see the network effects happening, and it made it possible to build lots and lots of businesses with different types of network effects.
So by 2001, 2003, you do have some people starting to really study these network effects in academia. But it wasn't until the early 2000 and tens where there were such a preponderance of companies that were dominating through these network effects that we and started really investigating what was going on. We're just now able to discuss them. We're just now able to put language to it. We can now see them and use them as tools.
To actually construct these network effects, to construct these startups and direct them toward the destination we wanna drive them to. That just starts happening maybe 10 years ago. Okay?
Now more recently, because of web 3, we are Beller, again, to see the the tide goes out Currier, and we can see more of these raw more of the things underneath the surface that were not sealable before, and we start to see the detailed construction of networks, leading us to network bonding theory, which we started noticing in 2016 and have been writing about only in 2021. And we'll get to that in this master class.
But you should understand the historical context of the evolution of what we can even see and what we can discuss. That the internet Pete us see stuff, we can discuss it to a certain Flint. And now web 3 has happened, crypto has happened, and we can see even more and see the real mechanics of it.
We're just on the edge of this new discovery of network effects in the same way that people were just on the edge of understanding scale effect businesses back in the 1850s, and you had a lot of writing about capitalism and scale effect manufacturing and the laborers and the proletariat. And we had this new language that emerged back then when new business model was discovered, we now have the same thing happening around network of funds.
Another way of understanding how powerful network effects are is to look at the good Pete story. So good reads built a network of people who were reading and sharing their thoughts about books. Now Amazon had owned the concept of books in the American mind for about a decade, and along comes good reads, they got a big article in the Wall Street Journal saying they now represented book reading. At this point, Amazon could not lose their brand position to good reads.
And so they made an offer to buy good reads the day before they were supposed to close. Good reads said, you know what? We don't really wanna sell, but if you paid twice as much, as you just offered us, we'll we'll do it. And Amazon, they yelled and they screamed, but in the end, they ate it. They had to eat it. Because they couldn't create the network effect that good reads had made between the millions of members of people on that.
Amazon had bought the 2 competitors the Pete reads, but they were much smaller than good reads. And so in order to own the jewel, they had to pay whatever it took. And this played out again with Facebook. Zuckerberg woke up one day with what we call a direct network effect around Facebook. A personal direct network effect because it was about the people on the network with their real names.
A few years later, he woke up and noticed that someone had gotten what we call a personal direct utility network effect, which is even more powerful than his personal direct network effect called WhatsApp. And WhatsApp only had fifty people and had very little revenue, if any, but Zuckerberg was still willing to pay about $20,000,000,000 for that company.
Because he saw that they had a stronger network effect and would eventually be able to attack him from a stronger position And so he needed to buy them at any cost, and he did. That was episode 1 of 11 from the network effects master class. Stay tuned to the NFX podcast as we'll post 1 episode per week until we complete the course.
You can also watch this entire master class online atnfx.com/master class where you can log in, track your progress, and watch full videos, retranscripts, and find other related material. Thanks for listening to the NFX pod us.