a16z Podcast - a16z Podcast: Not all Network Effects Are Created Equal

Episode Date: August 1, 2016

From hardware and hardwires to smartphones and social, technology wants to connect. It's almost a native property of technology and especially software businesses, which is why network effects matter. "It was endemic to these technologies that they wanted to become connected and once connected, they become networks and once networks, they become network effects. Other products like cars or toasters or houses or whatever, aren't natively connected physically or through information sharing," observes James Currier. But not all network effects are equal -- not only can they be strong or weak, there are many different types depending on the business. Currier, who is the co-founder and managing partner of an accelerator (NFX Guild) that advises and runs a runs a program for all kinds of early-stage companies with network effects, shares their ever-evolving taxonomy for thinking about different types of network effects in this episode of the a16z podcast. These labels matter. It's not just words, but language that aids understanding -- and the corresponding growth playbook -- that can help build businesses with network effects, especially given the specific challenges they face. And finally, why did some companies with network effects take off but others didn't? The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

Hi everyone, welcome to the A6 and Z podcast. I'm Sonal. Today's episode closes out our special series on network effects. You can find the other pieces at OnA6inZ.com. And we're wrapping up by talking about the taxonomy and types and evolution of network effects. Joining us for that conversation is James Currier, who's a co-founder and managing partner of NFX Guild, which is an early stage accelerator that runs a program for companies with network effects, which can range with all kinds of businesses. Also joining us for that. conversation is A6NZ partner, Anu Heri Heron. And we kick off this conversation, which was recorded months ago, talking about the history and evolution of network effects before we break down the taxonomy of network effects and why all network effects aren't equal and why the language for figuring out the differences between them matters. The first time it was used was 1907 in a annual report by AT&T. And they started noticing that because they had a lot of people connected to the telephone network, other people wanted to connect to the network, and that each of their customers got happier when they got a new customer, because they could now call more

people. And they said, because of that effect, AT&T said, I think we have a pretty good business here. And that was the first time someone coined the term network effects. Okay, because the first time I heard about it was, I think, when it came to the coinage of Metcalfe's law. Correct. Yeah. So that was during the Internet era, right?

I think there was a gap between when AT&T used it in their annual report and then Ethernet cards came into practice. If you look at Ethernet card, it's interesting to note, actually, network effects began with hardware. It was first the telephone, then the Ethernet, and in today's world, we talk about it in the context of software companies like Facebook. So Metcalf's law, in Ethernet card, the way it came about is the cost of the printer is really high. And so the Ethernet card actually enabled various people to connect to the printer, which reduced the cost, of the device. And that was an incentive for different groups within a company to even start adapting the internet cards because the value proposition was you could subsidize the cost of the device and you didn't need a printer for each person. So that's how Metcalf's law was born,

which sort of became the measure for network effects. Okay, so just to clarify by Metcalf's law, you mean, it's not really a law, like a lot of these laws, it's really just a description, like a descriptive formulation, that the power of a network doubles as n number of users get added to it? I think it's exponentially increase in value as each user joins the platform. Okay, there we go. And it wasn't even him who did this. I think it was George Gilder who actually described this phenomenon, but it's that the value of a network increases exponentially. It's square the number of connections in the network. So that's the Metcalf Law. You know, from 1907, it took until 1974 until academics started looking at this because they started

to see these effects, particularly in technology businesses. And Metcalf's Law came along a little bit after that. And then, you know, the network effect of the Microsoft operating system came to the four at the end of the 90s when the Department of Justice was looking at whether that network effect that they had between their operating system and all of the operating apps on top of it was just too much in crowding everybody else out. And I think that's, that is the important nugget, which is like, if you build network effects, you do become the dominant player in the industry for a while. And that's really why today, when we look at companies in internally from an investing standpoint, we try to figure out, A, whether they have network effects or do they have a pathway to achieving network effects because it's a big differentiator from the rest of, you know, from the competitive landscape.

Network effects are one of the few ways we have left for software businesses to have a moat, to create a mode around their business so that competitors can't eat away at their margins. Yeah. So in the olden days, there was lots of defensibilities that companies could have. You could have a port in the right spot. You could have an iron mine in the right spot. You could have ways of defending your business, but as we've moved into the software realm, we've eliminated distance, we've eliminated time, we've eliminated a lot of things that used to give people defensibility. And we're really left with only four major types of defensibility. And what are those four types? Well, the ones that we still have left over are brand. And there's actually three types of brand defensibilities. We have scale like you'd see with an Amazon, right? They're just so big. They have

such lower prices. It's hard to compete. And then you have what we call embedding. And that's typically used by companies in the B2B SaaS space, where you embed your software into another corporation's operations to the extent that they can't take you out. And once you're in there, you're defensible. So again, these are the four defensibilities. And all of them are valuable and all of them are still working in the software and the digital world. But the way we look at it is the network effects is really the only one that's native to what we're doing. And therefore, it's the most powerful. When you say native, there is some power in that word. So when you say it's one of the few native ways. The reason why I think we refer to network effects as being native right now is

really the evolution of the internet from the web to mobile. So, and I usually think of it as the pre-2000 versus the post-2000 era because Facebook came post-2000. And social really became predominant. Facebook is not valuable if you're the only user on the platform. And it was not just social connections, right? You find news through Facebook. You find content through Facebook. You find events through Facebook. And so it became easier to derive that value. If you compare that to telephone or internet, you still needed a piece of hardware. That was more friction to get more people to adopt the hardware. That changed. Then from the Facebook Webira, it changed to mobile. That's how you saw all these messaging, even photo sharing apps.

It became even easier because mobile phone enabled you to take pictures. You could communicate via images. It was easier for platforms to build a network, I would argue, on mobile more than web. I don't disagree. I would maybe take a different shot at it, which is that it's native to technology in the sense that the technology wants to connect. So every Ethernet switch connects to every other Ethernet switch. Printers are connected to printers.

Mobile devices are connected to mobile devices. So ever since the 70s, when we started using chips or 60s, it was endemic to these technologies that they wanted to be connected. And once connected, they become networks. And once networks, you have the chance for network effects. And other products like cars or toasters or houses or whatever aren't natively connected physically or through information sharing. Like an inherent property. Yeah. So everything that is silicon wants to connect to everything else that's silicon.

through these little wires that we have. So it's not a, it's not unusual that we would find the first network effect come when we first had our first wires, which were the copper wires that connected the telephone system. I think actually Doug Engelbart was the first to make that observation about silicon wanting to connect. Anyway, I think that's an interesting observation. Everything that we touch is connected and you can't really have a network effect unless things are connected. Now, there are types of network effects that are outside of the technology which we can talk about. Let's actually talk about type of network effects because I think this is a good option you to really unpack these terms? Yeah. So academic literature, I know,

tries to classify network effects at the highest level into four types, right? One is direct network effects, which Facebook is a classic example of, where the organic consequence of the product itself is that you need to have connections with other users, and therefore you derive value from the network. All of this is just language to try to help give us insight, right? Insight as we build these businesses, insight as we analyze other businesses and where we want to take these companies and these experiences that we create for other people. So this is, you know, the language is evolving and we're changing it all the time. We sometimes use different words to try to piece it apart, but we actually have identified nine different types of network

effects. As I knew pointed out, the first one, the first cluster of network effects is what we call direct network effects. You then have what we call, instead of calling it local, we call it personal because there's a personal relationship that the human beings have to each other that drive their deep adoption of a particular platform. And Facebook would be a good example of that. But it's not just personal. I don't get a lot of utility out of Facebook. It's really sort of a media. It's like instead of watching TV, I use Facebook. But I use Facebook Messenger to do useful things. I use WhatsApp to do useful things. I've got to pick up my kids at school. I need that done. And I'll use those two services to get that done. Now, what's happening with

Facebook messengers, they're going to add payments and they're adding all sorts of other utilities. And I think that they, from what we can tell from their behavior, have realized that the personal utility direct network effect is actually more powerful than a regular personal direct network effect. That is actually the big point of the primary we put out around WeChat. It's not the social connection only, the personal connection that you're describing, but the more utility you drive, the more people will use it. Why does that distinction matter? Like, why would you go that far in the taxonomy? It matters because you're going to get a different level of engagement in terms of activity. So how many times you use it a day? And you're

going to get a longer life arc of that product. Right. So we all still, we all had telephones between 1900 and 2014. And now we're all on the mobile phones. And we have a personal number, as opposed to being attached to a phone. So it didn't change for 115 years. Facebook may be around, in 10 years, but it might not be. But it's pretty clear that messaging will be around because we're always going to be able to scan text with our eyes. That's a good interface for us. And so messaging is probably a longer term thing for a network effect business than just a personal connection. And there's a fourth one. And there's a fourth one, which is what we've called market networks. And a market network is a personal utility, but there's money involved. So there's an even

greater reason for you to want to stick with and use it because that's where you get your money. You have a network, a personal direct utility network where there's money being transacted. And so now you have even more reasons for you never to leave that because, hey, that's where I get my income. Do all marketplaces have network effects by definition? So I don't think that all marketplaces have network effects by definition. They have the potential, but different marketplaces are at different stages of development in their evolution. So a marketplace that is new and just begun and say it's six weeks or ten weeks, and they don't have sufficient liquidity. Someone could start that down the line or even a few weeks from now and they may have stiff competition.

A classic example, and we've talked about this before as well as Airbnb. The first three years of Airbnb was a real slog because it's a global marketplace and they were trying to build supply. At the same time, they were also trying to build demand. and they needed to sign up the homes. They needed to make sure that people trusted the marketplace and felt secure to make a booking. But three years into until then, the growth was really sluggish,

and you can almost see it in their graphs that they share. The Room Nights book just started growing enormously after the third year because they had sufficient liquidity, both supply and demand, and it started working. Then we've got three that are more two-sided network effects. And one of them is, let's say, where, you know, Microsoft was in the 90s, which was they had a platform, what we call a platform two-sided network effect, where you have a piece of software that everyone wants to plug into, and then you have developers or other companies that plug into your business so that everyone kind of has to use it because otherwise they don't get access to the other side of the platform.

We thought that the word platform described it better. It made us understand what was going on better so that we can measure. Are the developers actually writing software to that platform and have enough developers adopted that platform so that we feel like they're going to have a chance to win? What I find fascinating about this conversation and also as a person who loves words for a living is how why the words matter. What we're doing is we're looking for playbooks to grow the companies with the network effects. And so we need to identify which type of network effect are we going for and then we run the playbook on the growth around that. So now we're up to the two-sided network effects. and there's three of them.

One of them, we call the asymptoting two-sided marketplace network effect. It means it doesn't keep going, doesn't get better past a certain point. We're capable of seeing someone come in and compete with them pretty effectively on a lower price. The eighth and ninth network effects, which are, again, now less strong than the direct network effects or the direct network personal utility effects of the center of the core is what we call bandwagon effects. Literally just think of it as popularity. So the most recent good example of that is Slack. They do have a real network effect. They do have a real personal, direct, utilitarian network effect.

But they also have a bandwagon network effect, which is if you're using a tool, if you're using hip chat, it's kind of uncool. The bandwagon effect and the language effect are actually the network effects that exist between people without any software, without any technology actually connecting, which is if I come to you, Anu, and say, you know what, I actually think that hipchats better, you're going to look at me cross-eyed and say, dude, you're not cool. Yeah, you're right. Why aren't you on Slack? We would say that because Slack's a portfolio company. Right. Damn it. So that's a social reason why it's hard for me to use another network and I have to stick to the network that everybody else has already adopted.

And when I use it, it then benefits everybody else for real network effects. But there's a bandwagon effect which comes first that actually is impactful. Just one quick question, though, because when you talk about different types of defensibility that companies have in this, from a previous age and in this current age, that's just brand. Correct. But it's important to. tease out the difference between brand and a bandwagon when something's just getting going and everyone wants to get on it for social reasons. That's before it has a brand. A lot of people make this mistaken assumption. My business is growing just fine and adding all kinds of great value. I don't need any sales and marketing. So it kind of isn't interesting. I like that you're distinguishing this because it does make an argument for why certain levers need to be pulled at certain point.

That's exactly the point. The only reason we change this language around is so that we can figure out what playbook to run, what feature to build next. How much should we spend on the next feature? How much time should we spend and trying to do that. That's it. That's the only reason we tease these things out. And I think in the bandwagon also tying it to the vital growth point, it's not sometimes all of a sudden. So the product has to be good for the vital growth, but the key influencers also matter, right? Like who is using the product going back to your point? Who is using the product? Who is actually promoting the product? If you look at the original, when they launched Instagram, the people who tweeted that here is the new app that is Instagram actually influenced a lot of

people to sign up. Yeah. This point about, you know, who starts it to create the bandwidth effect matters for almost all the big networks you can think of. It was a guy named Scott who started Rise, R-Y-Z-E, in 2000, which was LinkedIn two years before LinkedIn. I don't remember that, right. But he wasn't Reed Hoffman. And Reed knew the top 4,000 people in Silicon Valley and emailed. And then once we were on, all the guys in New York wanted to be on. So where these networks start matters. Look, there was three college social networks that came before Facebook. But it was the first one started at Harvard. Besides where, what about when? When does it actually reach a point? You know you have a network effect. I think these businesses start with network effects by their design. Right. So you're saying

it's baked in from the get-go in a certain way. And then the question is, when do the network effects kick in so that you can tell it's going to be a $10 billion company? When do we know it is at that point that it is winner-take-all? It's very hard to determine the tipping point. And I think if you Once the companies themselves, they would tell you that they don't know when it tipped. And that is no single measure of network effect for a company and different value to the users. At the end of the day, you just want to make sure as there are more users on the platform, is it becoming more valuable. How do you measure what is valuable?

And that's different depending on which company. And also the competitive set. Because if there's three people going after the same thing and they're all growing quickly, you're like, oh, yes, especially these days with mobile on-demand services where you have a company in San Francisco. and other company in New York and both are growing really well in their respective cities. You know, that's not really a network effect yet. Well, it is a network effect. It's just not one you want to invest in.

So let's actually talk about what happens when they don't work. I mean, let's take the case of like MySpace and even a case like Pat because that to me felt like, I mean, granted it was capped at 150. But like, why wouldn't that, why didn't that work? Let me talk about the MySpace example. I think one of the key things about network effects is you need to have product market fit. Like you can't just build network effects and people are not just going to use your product without that. The challenge with MySpace was it allowed you to sign up anybody. It allowed you to have connections with any even strangers or personalities with the page or influencers.

And so you don't have a daily communication with them. And I think that was, there are many other reasons that I cited, but that is one of the the key drivers for why I think MySpace did not succeed. I don't think they had the strong retention that Facebook did as well. Facebook from day one measured their repeat usage and that kept growing. Our take on MySpace was that they didn't actually have a personal network effect because they didn't have real names. And in fact, what happened with Facebook is that they were the lucky ones who got to real names in a social context first. So LinkedIn got there first, Facebook got their second, but no one at that time was willing to accept real names in a social network.

Everybody was a pseudonym. MySpace, high five, tickle social networking. We had 30 million people before Facebook ever launched, but they had real names. And so that it becomes a personal direct network effect, which is stronger than just a regular network effect. Now, I would argue that MySpace became entertainment. It became like a TV show you're going to watch for two or three years. It didn't become anything with utility. So when you look at Facebook, Mark Zuckerberg on year three, changed the homepage to say Facebook is a social utility.

He knew that he needed to go toward utility in order to get a real network effect. Real names and real utility was going to provide you with that foundation. And without that, MySpace with it away like any TV show does. And in fact, Facebook in the first two years, I believe when they were trying to get the students to sign up, called it as a student directory. Because these universities didn't even have a good student directory where they could. actually look up and see who else is taking this course. Well, that was the origin of Facebook because there was a physical Facebook. And that was the utility for students to sign up, right?

It was a utility even from day one. Right. That makes sense. And then how about the case of path? I know that it had a built-in cap. But then at the end of the day, my WhatsApp group only has like 20 people in it. And it's incredibly engaged compared to my Facebook. Yeah.

I think for WhatsApp, they did crack the utility piece, which helped them build product market fit. Yes, they hacked the phone book, but that's not what the most exciting piece about them. The most exciting thing about them is they targeted international communities where SMS is expensive and WhatsApp was free. I remember I was one of the early WhatsApp users because I had to communicate with my family in India and I was paying steep amounts being in the U.S. per minute while WhatsApp was free and I could engage with them on a daily basis. It was actually a dollar for a year. I remember that was when I paid a dollar when I signed up. Yeah, I don't remember paying that. But the international community signed up because it was

an alternative option to SMS and it was essentially free and they used the phone book. And I think they kept the product really, really simple. And over time, they had partnerships with carriers which pushed WhatsApp onto the phones as well that helped their growth. Going back to the Path, I think Path just suffered from competition. I think that once Facebook mobile came out and once you had WhatsApp, you had so many other ways of getting the personal utility out of your phone. Had there been no competition like there was for Facebook when they were growing for two years in colleges, Path would have been a big company. Okay. So you know, earlier I was saying don't confuse virality with network effects.

A network effect is essentially for defensibility and retention, right? You continue to use a product that has a network effect because of the network effect. It's not a viral effect is different in the sense that it gets you new users. So the viral effect is about getting new users and the network effect is about keeping those users, and they're very, very different things. Now, a network effect type of a business often has a lot of interesting hooks, a lot of good raw material to develop viral hooks and viral paths, right, and viral loops on top of, but they're different. And when you're building a network effect business, you build certain features and language and

functionality, and when you're building your viral loops, you build different stuff on top of it. And I think the key distinction, especially from an investment point of view, we try to do, is, you know, Because is it viral growth or does it also have a network effect? And as James pointed out, you know, platforms or marketplaces don't need to have network vital growth to have network effects. The other layer I would add is the result of a viral growth is that your CAQ is pretty much zero, right?

Your customer acquisition costs to zero, which is great. We like businesses that are really growing organic and word of mouth, but then we also really care about do they have the potential to have strong network effects and defensibility. Great. Okay. Well, you guys, thank you for all those insights. A lot of terminology, but I think it's important. Thank you for joining the 860s podcast, James. And thank you, Anu. Thank you.