This week’s podcast is about network effects, as described by James Courrier and NFX.
You can listen to this podcast here, which has the slides and graphics mentioned. Also available at iTunes and Google Podcasts.
Here is the link to the TechMoat Consulting.
Here is the link to the China Tech Tour.
Here is the NFx Network Effects manual.
Here are NFX’s 16 network effects, in order of strength:
- Physical (e.g. landline telephones)
- Protocol (e.g. Ethernet)
- Personal Utility (e.g. iMessage, WhatsApp)
- Personal (e.g. Facebook)
- Market Network (e.g. HoneyBook, AngelList)
- Marketplace (e.g. eBay, Craigslist)
- Platform (e.g. Windows, iOS, Android)
- Asymptotic Marketplace (e.g. Uber, Lyft)
- Data (e.g. Waze, Yelp!)
- Tech Performance (e.g. Bittorrent,Skype)
- Language (e.g. Google, Xerox)
- Belief (currencies, religions)
- Bandwagon (e.g. Slack, Apple)
- Expertise (Figma, Microsoft Excel)
- Tribal (Apple, Harvard, NY Yankees…)
- Hub-and-Spoke (TikTok, Medium, Craigslist)
- 3 Types of Network Effects (Asia Tech Strategy – Daily Lesson / Update)
- Questions for Huawei’s CEO, JD & Jingxi, Metcalfe’s Law Is Dumb (Asia Tech Strategy)
From the Concept Library, concepts for this article are:
- Network Effects
- Data Advantages and Network Effects
- Bandwagon Effects
From the Company Library, companies for this article are:
- NFX / James Courrier
Episode 158 – NFX.1.transcribe
Fri, May 05, 2023 3:02PM • 49:53
network, effects, embedding, talk, companies, platform, data, users, marketplace, standard, point, people, scale, idea, asset, build, business model, language, phenomenon, increase
Jeffrey Towson 00:00
Welcome, welcome everybody. My name is Jeff Towson, and this is the tech strategy podcast where we analyze the best digital businesses of the US, China and Asia. And the topic for today NFX’s 16 network effects plus embedding in some other small digital stuff now, and effects is a venture capital sharp, I believe in San Francisco Bay Area for sure. I think San Francisco,
Jeffrey Towson 00:28
the they do a lot of content and NFX stream of their company literally stands for network effects. And their big thing is network effects. And one of the partners I believe, the founder, James courier, he writes quite a lot about this. He just put out some videos called like a master class and network effects. It’s a podcast, he’s got on the webpage, the network effects Bible, the network effects manual, and quite a lot of articles about network effects, some good thinking, and the sum, total, usable, actionable. Part of all of that would be a list they publish, which they update regularly, which they call 60 network effects. And they’ve you know, they basically break it down. It’s pretty good. I don’t agree with all of it. I mean, about half of it. But they have some good thinking. It’s definitely much more from sort of a venture capital, early stage perspective of the phenomenon. But I thought I would go through those 16, I’ll give you the link, if you want to go look at it, you can watch some videos about how he they walked through him on a podcast and stuff. So it’s, it’s worth your time. There are some subtleties there that I found helpful, but also to take you through it, the basics and where I think it’s valuable. And then within that there’s some smaller ideas, which like, embedding is one they talk about a lot, I don’t think it’s that big a deal. But to talk about that, that’ll be the topic for today. So hopefully, that will be helpful. Let’s see standard stuff that the
Jeffrey Towson 02:05
China tech tour coming up in June, probably looking for a Southeast Asia one later in the year, that should be fun. I’m heading back to China in about seven or eight days. Looking forward to that turns out, I’m going to China like literally every week in April. So back to old normal life, I suppose. Anyways, that’s there. If you’re interested in the China Tech Tour, five days, Beijing Hanzo, Shanghai, look up on tech, Mote consulting.com, or look in the show notes, you’ll see the link, it’s going to be cool. And what else, those of you who are subscribers, I’m going to send you, I’ll send you a more detailed version of the 16 network effects. Probably later today.
Jeffrey Towson 02:54
I kind of go back and forth. Because I have to get my grade, I have to get my brain in like theory mode versus company mode. So we’ll switch back into that next day. And let’s see what else standard disclaimer nothing in this podcast or in my writing website is investment advice in numbers and information from me and any guests may be incorrect. The views and opinions expressed may no longer be relevant or accurate. Overall, investing is risky. This is not investment, legal or tax advice, do your own research. And with that, let me get into the content.
Jeffrey Towson 03:29
Now, as always, we start with sort of concepts, lessons, whatever you want to call and there’s a couple for today. Obviously network effects. You know, if you go on my website, the concept library, I mean, there is a lot under network effects. If you’ve read my modes and marathons books, I mean, I’ve written a couple chapters on network effects. And I think the thinking on network effects overwhelmingly is so shallow.
Jeffrey Towson 04:42
One is the idea of data network effects versus data advantages. And if you’ve been listening to me for a while, you know, I don’t really like the idea of data network effects. It’s been floating around for a while. I think it’s a half baked idea. I don’t think it’s going to last and the idea is Oh, I get more customers.
Jeffrey Towson 05:00
on Netflix then a smaller rival. So I have more data that lets me personalize and improve the product. So my product will get better. So it’s a data network effect, the bigger you are, the better your service.
Jeffrey Towson 05:19
Now NFX talks about data network effects, I don’t think they really believe in me either. Most of the time, what people are actually trying to talk about is data advantages, which are mostly from scale. If you’re a bigger company, you have more scale, you have more scale in your operations, you have more scale in your supply chain, you have more scale in your retail stores. Oh, and guess what, you have more scale in your data. And there’s some advantage, sometimes that can turn into competitive advantage.
Jeffrey Towson 05:46
Oftentimes, it’s just an operating activity. It’s very rare that it tips over into something like a network effect. So data is critical. Operationally, data can sometimes become an advantage, a competitive edge, very rare. I can’t think of a single case where I view it as a network effects. And I’ll give you the case everyone points to which is ways. Whenever you say did in our effects, everyone’s like, Well, what about ways, and not really, it was all going to that, that’s the other idea data advantages versus data, network effects. And then two smaller ideas, which are not terribly important, but I’ll just touch on them. One is embedding,
Jeffrey Towson 06:25
which some people talk about, and effects talks about it. The idea that if I have YouTube, and then I let people embed their videos in various websites, and if lots of people put their little, you know, the videos in websites, as you know, links or whatever, or they embed them directly, it has benefits to that business.
Jeffrey Towson 06:46
Okay, I mean, there is something there, and I’ll talk about what that is, I don’t think it’s a network effect. I don’t think it’s a competitive advantage. But we do see embedding, like, you know, the fact that Amazon affiliates is in lots of links, and you can click on it make $1.
Jeffrey Towson 07:03
Open AI has API’s that you can embed into other apps.
Jeffrey Towson 07:09
It’s kind of a big, sprawling idea.
Jeffrey Towson 07:13
In the internet, everything’s kind of embedded in everything, really. And we’ll talk a little bit about that. And then the last one is bandwagon effects, which was used to hear about this a lot 2019 98 bandwagon effects this company is going to take off because it’s bigger and bandwagon and nobody really talks about it anymore. It’s basically, it’s basically fear of missing out. If everyone’s getting on WhatsApp, because it’s new this week. Oh, I should get on that too. Who tic TOCs the big new thing I don’t want to miss out, let’s all start using Tiktok. It’s more of a fear of missing out thing, but people call it get on the bandwagon. People try and say it’s a network effect, which NFX does. I don’t really buy it, as we’ll talk about that. So two big ideas, network effects, data advantages. And then two small ideas, embedding bandwidth are fake. So you should be kind of aware of those because you hear them every now and then. pretty fuzzy thinking I think. Okay, so those are the ideas for to date. Now, let’s start with, I’ll put a link in the show notes for the network effects manual, which is basically there’s 16 network effects. And they they explain them quite well and they have some graphics, and you can go through it. It’s worth
Jeffrey Towson 08:28
it’s worth reading, and I’ll talk through the important ones. Most of them I’ve now half of them I’ve talked about before in my own language,
Jeffrey Towson 08:43
you know, my standard example is you go to KFC, you have chicken, the other people’s chicken doesn’t taste better. You go on WhatsApp, because I’m using WhatsApp your whatsapp got better as a service, the more people that use it or increase the usage, the better the service becomes.
Jeffrey Towson 09:12
The idea that there are things outside of a company that can be positive or negative, so a negative externality would be pollution. If a lot of companies are operating and they dump all their stuff in a river. That would be a negative externality. It’s external to the firm, it’s a market externality and it’s largely negative. It can be negative for society, it can be negative for the market, it can be negative for the industry can be negative for the company.
Jeffrey Towson 09:39
They can also be positive. And when the externalities are positive or negative, but we usually talk positive, and they relate to a network. So it’s an externality, but it’s related to a network, not just a firm, then we call it a network externality is so then you can see
Jeffrey Towson 10:05
And, you know, the roads, bridges, all that stuff. Those are all kind of network externalities. And it was, it’s, I don’t think about it too much, because I don’t really look outside of companies too much. I’m mostly inwardly focused. Okay, so my, my sum of all this stuff, which I’ve written about, and I’ll put the link in there is
Jeffrey Towson 10:26
there are three types of networks, which are assets. There are physical networks, all the roads, that’s a physical, tangible asset. That’s a network. It’s a physical network. That’s one type of network. Second type of network would be a protocol network. That’s the software that helps computing devices, whether their phones, IoT, laptops, servers, the software and standards that help them connect creates a protocol network. So all the computers are now linked.
Jeffrey Towson 11:01
Okay, it’s a network, but it’s intangible. And it’s based on the protocol that helps them interact. So there’s physical networks, there’s Protocol networks. And then I put everything else into one bucket, which I just called people in companies, networks,
Jeffrey Towson 11:22
But it can also kind of be companies, you know, companies can connect with each other people, as consumers can connect with companies, the distinction is pretty fuzzy. So I just group it together. You know, we’re all connected by our smartphones, if I go online and buy something on Lazada, or Taobao, that is a network between consumers and merchants, which is kind of a mix of people and companies, depending how you decide to break it out. So three types of networks, all the networks are assets.
Jeffrey Towson 11:50
Facebook’s core asset is its people network. That’s what it’s got. That’s the core thing, just the same way. Walmart’s core asset is it stores, Facebook’s core asset is its network. That’s it. The phone company’s core asset for a long time was its physical wires, although then you put people on top of that. So it becomes a people network on top of a physical network.
Jeffrey Towson 12:16
And it was those are kind of three types of networks, I view those as assets. So we have three networks, five platforms, three network effects, then we get to five platforms, platforms are business models, you build on top of these assets. Right.
Jeffrey Towson 12:33
So you could build FedEx, which is kind of a business model for shipping packages back and forth. But it’s built on a physical network of trucks and planes and warehouses and roads. So that’s the asset. But the business model is different. One of the interesting things about web three is we are separating the asset, the network asset from the platform business model, you know, suddenly, the network is everything on the blockchain, and then the platform sits on top of that.
Jeffrey Towson 13:03
But typically platforms and networks, they kind of get bundled together as one thing, Facebook’s assets, its social network, its business models, connections on that social network. It’s kind of one thing. So people don’t always separate those two, NF x doesn’t really separate them I do. I think it’s helpful to think about platform business models differently than the assets they run upon. But you’ve heard me talk about my five platform business models, which are all based on describing the type of interaction you’re enabling. So marketplace platform transactions, innovation, and audience builder, you know, you’re building something on top of this platform, whether it’s videos, content, software, gaming, whatever.
Jeffrey Towson 13:48
Payment Platform, making payments, coordination and standardization platform, you know, Microsoft Teams, and then learning platform, which is, I’m not quite sure how I feel about that one. But I think it’s a big deal. I haven’t quite gotten my brain around that. But you know, those could all be built upon the same network asset, which would be people connected. So I find that it’s easier to separate the asset you’re building from the type of interaction, which is the platform and you know, my five. And then the third bit, which is what I’ll talk about today is three network effects, which are no direct network effect, indirect network effect, standardization and interoperability network effect. Those are my three, I’ll talk about those.
Jeffrey Towson 14:32
Okay, that’s just sort of my world. My frameworks. And my standard question, whenever you get confused about a network effect is always and I’ll put it in the notes. How does the marginal user or activity, increase the value and or utility to current and potential users?
Jeffrey Towson 15:00
incremental value from marginal users, I’ve got 100 million users on this service. Who knows what it is Etsy consumers. When we add another 10 consumers, does that add incremental value and or utility utility is little easier. It’s like people you can call the value can be really can be perceived.
Jeffrey Towson 15:25
And how that incremental value changes with more and more users is important. And in most cases, it declines. As you get more and more users on a platform. It can be users and or activity. If you got the same users, but they’re doing a lot more transactions, that’s also incremental activity.
Jeffrey Towson 15:44
Does that keep adding the same amount of incremental value? Or does the service not get any better at a certain point, which is almost always what happens. So the marginal user or activity tends to add a lot of incremental value in the early stages of a platform business model. When you go from 50,000 merchants selling on a marketplace to 100,000, it’s a tremendous increase in value to the users. But when you go from 10 million to 10.5, it’s not that big a deal.
Jeffrey Towson 16:55
Companies with the strongest types of network effects built into their core business model tend to win and win big this is from their thing. Our three year study, which we released shows that network effects are responsible for 70% of the value created by tech companies since the internet became a thing in 1994. Even though they are the only a minority of companies, companies with network effects, and Krim, end up creating the lion’s share of the value, unquote. Okay. Now, I would say the first thing to point out here is, they’re really combining two different things. They’re talking about defensibility, which is a competitive advantage, a barrier to entry, hence my old books, but they’re also talking about value creation, that’s a different thing.
Jeffrey Towson 17:45
In fact, I think network effects when people talk about them, they’re often confusing three different ideas. They’re confusing, competitive defensibility moats, my area. And network effects definitely have moats that come from both the economies of scale on the demand side and on barriers to entry.
Jeffrey Towson 18:09
As you get more and more activity, and you get growth, you get more and more value, which is kind of what I was talking about, right? I didn’t say anything about defensibility. And then third bit is they can accelerate growth dramatically in the early days and sort of help the market collapse to one or two players. So those that happens in the early stages, typically. So there’s really three things happening with network effects that I think people sort of lumped together, which I think they’re doing their little bit. Okay.
Jeffrey Towson 18:42
Now, they argue most of the value created by digital companies is in network effects. I also this is an area I have trouble with. People use the word value Metcalf reads law, which I think are nonsense. What do you mean by value? Do you mean economic value? Well, that would be more a reflection of unit economics and market power, competitive power, you know, certain companies throw off more economic value than others, capturing economics, some grow economic value more than others. Some businesses grow value and become, you know, throw off a lot of cash. Some don’t. But they preserve value, well, that’s economic value, or are we talking about value to the users, the perceived or real value to a user of WhatsApp is often what these folks are talking about the definition I gave you. For network effects. I didn’t mention anything about economic value. I talked about the perceived or real value to users with incremental activity that’s perceived and that’s where business starts, you know, you create value for your customer, or your other user group. And then that’s how you got that’s mostly what they’re talking about. Well, I mean, what he’s talking about here is x anomic value. And that has a lot to do with business model, not network effects, has a lot to do with global scalability not network effects. So I don’t really buy their study. I haven’t seen it, but I think they’re, they’re mixing terms there. Okay, that’s just me poking holes a little bit. None of those are huge issues, more semantics than anything else. Okay. Now, they do have a network effects map, which I will put in the notes, this is what you should look at. This is interesting. They basically list their 16 network effects in a big circle. And the ones at the center are more powerful in their opinion, and the ones going outward are weaker, that’s very helpful. Because that’s a lot of judgment. And I’m more or less agree with how they’ve staggered these that, you know, certain network effects are far more powerful, some are fairly weak. So take a look at that. And then if you look at the side, they have three little notes, they say brand, embed, and scale. And this is basically their plan, which is build a business model based on network effects. Because that’s how you win big in life. Once you’ve decided that, then your playbook is build your brand, do embedding and go for scale. So those three words on the side brand embed scale, that’s kind of the playbook once you’ve decided what you’re building. Interesting, and I’ll talk about that a little bit. I think that’s it’s not bad. It’s not how I view the world. But I’m probably 70% on board with what they’re saying here. Which is pretty rare for me, actually. Okay. So here’s what they put little comments on that graphic. The map we’ve laid out here isn’t meant to be taken as an incontrovertible truth. It’s the beginning point for discussion and understanding. It’s one of our evolving methods to help founders recognize and make use of powerful forces to build great companies. Yeah, right on. I mean, that’s exactly how I do things as well, which is, you use frameworks to get a better understanding of the phenomenon you’re trying to understand. But at best, they’re directional. At best, they help you make sense of some chaos, they’re rarely more than half the picture. So they say, Look, this is a starting point, then they make another point, network effects are not viral effects. I’ve made that point before, they are about creating defensibility viral effects are about getting new users for free. Pretty much every
Jeffrey Towson 22:28
last point, different network effects types are not mutually exclusive. They’re like colors, and your company’s going to have some true, okay, that’s basically their pitch, I’ll take a look at the graphic, it’s worth looking at. I think it’s useful a particularly the prioritization of strong versus weak ones. Alright, with that, let’s go into some of the specific ones that I think are important. Alright, so they put 16 in order, which are in their opinion, in order of strength. So this is sort of the strongest one. And they start with physical networks, or, actually, before that they talk about direct versus indirect network effects. So direct is what I’ve been calling one sided network effects. That’s where, you know, more users on WeChat are directly more valuable than other users, as opposed to indirect network effects, two sided network effects with, you know, merchants and consumers, you know, more consumers on a marketplace doesn’t increase value to the consumers increases value to the merchants and vice versa. Okay, so they basically say, look, direct network effects, one sided network effects are more powerful, which is usually true. It’s the strongest, it’s the simplest network effect. They see increased usage of a product leads to direct increases in value of that product to its users, right. It’s a direct linkage. The more people that use WhatsApp, the more valuable it is to everyone on use. There’s no indirect Well, it’s helps merchants now it’s very immediate. The other thing to think about which I don’t really point out enough, one of the big differences between direct and indirect network effects one sided and two sided is there’s no chicken in the egg problem for direct. You don’t have to get a bunch of merchants to get consumers and then get a bunch of consumers to get merchants No, no, you just get people to sign up for your social network. It goes immediately. So it has less of a barrier to entry in that sense. And it was said so they talk about physical network effects as an example of that, which they say is the strongest one. I don’t necessarily agree with that. I agree with the fact that direct network effects are stronger. I think when they’re talking about physical networks, and he gives the same exact answer everyone gives the example which is the chairman of AT and T back in 1908 1910. He started writing in the annual reports Theodore de Valle. About Basically network effects in the phone system that was being built. He’s probably the first CEO that ever talked about it. And it was a couple things. One, the more people that sign up for a TNT, the more directly valuable it is to the other users of a T as a phone service. But he also said, quote, to exchange systems in the same community cannot both have, well, let’s skip the handset, no one has used for two telephone connections, if you he can reach all with whom He desires through one. So it’s also pointing out that physical networks tend to collapse to monopolies. Nobody needs two different phone lines in their house. Usually, you might have two phone numbers, but you don’t really need two lines. You know, this is when you have a let’s say fiscal network or a social network. That’s a utility, which Facebook is and phones are, it really does tend to collapse to one player because there’s no ability to differentiate payment network, it’s the same thing. Now if you’re dealing with marketplaces, in E commerce, there’s a lot of ways you can differentiate your service. But if it’s a utility with a direct network effect, it almost always becomes a monopoly. Now physical networks, sorry, physical network effects. He talked about roads, transportation, water, natural gas, sewage systems, electricity, subways, trains, and then telecommunications, satellite broadband cable telephones the standard examples for this. Not bad. I think what he’s talking about is actually two things. The reason they’re so powerful is partly because of the network effect. And it’s partly because there’s a big barrier to entry with physical network effects that you don’t have with digital ones. If anyone can create an app, and create a marketplace, the barrier to entry is much lower than laying cables across the whole friggin city. So I think really, the difference is the barrier to entry and physical is much higher. But it also grows much slower takes you decades to build a phone network, but you can build a hot app and you know, six months. Okay, fine. I’m not gonna go through this because I basically agree. And he goes into Metcalfe’s law reads law, which I think are mostly bogus. I’m not sure if you’re curious about that. I’ve, I’ll put a link in the show notes. I’ve I’ve done talks and articles of I think Metcalfe’s law is stupid. not stupid, just wrong, mostly wrong. Okay. So he goes through a lot of these, I’m not going to go through them, I’ll just read them off to you, because most of them are pretty familiar. So physical networks, number network effects, number one, number two protocol network effects. Pretty much just what that that’s Ethernet. That’s, you know, that’s VPN, that’s all of that sort of connecting computers. You could say, That’s Bitcoin. He doesn’t, I would. Number three, personal utility network effect. And he cites WhatsApp WeChat. So that I’ve kind of already been saying those are all direct network effects. But he’s characterizing the network effect by the type of interactions happening where I just say it’s a different platform. So I message WhatsApp, it’s a personal direct network effect, but it’s for a utility, which is pretty much the point I just made. Number four, he says Facebook is a personal network effect, not personal utility, personal. So a little more, I guess, I guess Facebook is in a pure utility. It’s more about friends and entertainment. Okay. So less strong, more room for differentiation. Number five, a market network. This is when we start getting into two sided networks, indirect networks. And he breaks us into two marketplaces, which I’ve talked about a lot, and market networks. So a marketplace fine eBay Craigslist, Taobao Lazada, a market network, which is a pretty good concept, and I’m pretty sure he came up with it. That’s when it’s a marketplace. But it starts to look a lot like a personal network. If you’re going to create a marketplace platform, for legal services between companies and lawyers, it’s not like getting a ride to the airport where it’s very transactional and shallow you have your reputation is incredibly important for being a lawyer for a large corporation. So his argument he’s combined the words it’s a marketplace plus a professional network combined, hence market network. And this the behavior is very different. You have long standing relationships, your reputation is important. You refer you know, if you’re a lawyer, you refer to other lawyers first Certain things, the personal and professional network is as important as the marketplace. So it’s kind of halfway between LinkedIn. And I don’t know Upwork. So he calls it a market network. That’s number five marketplaces. Number six. I basically agree with that. I think that’s well thought out. Number seven is platform, which he’s basically describing an innovation platform, Android, iOS windows. So it’s worth looking at. But pretty much everything I’ve just said one through seven is stuff I’ve talked about just using different language. Okay, here’s where it starts to go a little different. Number eight is a simp, a symptomatic asymptotic, I kind of gotta learn how to pronounce that asymptotic marketplace. Which is interesting, because it’s kind of the stuff I’ve been talking about of, you know, marketplace, you know, network effects increase increase in them, they flatline happens to almost every network effect, not all of them, but most of them. And for some, it happens very quickly, like Uber, once you get 50 taxis in your neighborhood, there’s no value to having more taxis, you can get a ride in three minutes. That’s it. So some, you know, reached their asymptote very quickly. Others take you know, go on forever, like Airbnb. Airbnb keeps adding hotels and places to stay in city by city all over the planet. So it’s it keeps going up and up and up as a network effect. Uber Lyft. They flatlined pretty quick. So he calls those ASPNET todich marketplaces where the value curve flatlines. Okay, I think that’s, I don’t think that’s a type of network effect. I think that is happening in all of them. And if you look at the article I wrote on this stuff, which the link is below is, and we were always looking for at what point a network effect reaches a threshold of viability where it’s a reasonable service, you’ve got enough taxis in a neighborhood to offer a viable service. At what point does more taxis flatline. She needed the asymptotic level, you need the threshold level. And then you look at sort of the scale differential between you and your next competitor in terms of how much bigger Am I than my competitor, you need to know all three of those numbers for any network effect.
Jeffrey Towson 32:27
I don’t care what type it is. So I think that’s a little bit strange. I don’t really buy that one. Not a bad point, though. Okay, I’m going to start bouncing around for the rest because I think the order of the last eight or nine is not terribly important. We’ll call them all in his opinion, weaker. Expertise, network effect. Basically says products that can develop expertise. Network effects are typically tools used by professionals to do their job, the instruments on which they apply their craft. So accounting software, QuickBooks, analytics, coolant, Google Analytics, Mixpanel, computer languages, Python, react, spreadsheets, Microsoft Excel. I’ve put this all in my third category, which I call standardization, and interoperability, network effects. This is all about creating a standard, everybody’s using, you know, if everyone who’s coding is using Python, it’s become a standard language. So it’s easier for people to talk and work together. Because we have the same standard. It’s easy for this, in this case, programming language to interact with other languages. Because it’s interoperable. Because we have a standard people can build an interoperate with it. We all train on the same tools, things like that, when people are looking to hire Python programmers. They look for the same credentials, and they tell them these are the tools we use. Oh, those are the tools. I know. I think that’s all standard standardization and interoperability network effects a lot of professional tools but you can also say a lot of the stuff Adobe does Final Cut you know, WordPress, I use WordPress. So that’s how I describe it, but that’s fine. Data Network effects. Let’s see. Okay, so here’s sort of the other one of the concepts for today, data network effects. And I think you already know my opinion on this, but let me let me tell you how, how they describe it. Quote, data network effects tend to be weaker than many people particularly venture capitalists often want to believe having more data doesn’t necessarily translate to value and gathering more useful data isn’t always easy even if data is central to the product on quote. I think they make a good point. They say quote, data can increase product value in different ways. If data is really central to the way the product benefits users, then data network of Next up, that product has the potential to be very powerful. If data is only marginal to the product, the data network effect won’t matter much. I think Buffett does actually kind of believe in data network effects, in some cases, although it could be a scale effect, he does look at insurance companies that do risk analysis, and that the longer you’ve been doing insurance and processing claims, the better you get at assessing the risk of long tail events. So you could call that a network effect, I would probably call it just a scale advantage based on we have more data because we’ve been doing this longer, and we’re bigger. So therefore, our risk assessments were using, and therefore our pricing of long tail events, like catastrophic risk is better. I think that’s mostly scale. But I suppose you could call it a little bit of a data network. And so they talk about Yelp, they talk about the standard, you know, more data makes you able to make a better product, therefore, it’s better, I don’t buy that. Okay, here, then we get to the ways example, it’s always the Waze example, a good example of a service with a strong data network effect is ways not only does it nearly everyone consuming data on ways also contribute useful data. Because the data is consumed in real time, the data set needs to be continually updated. Now, I wrote about this in my book, because it’s the only example anyone ever gives, and I don’t buy it. I ways for those who aren’t familiar, it’s Israeli now, global ish. It gives you real time traffic information, because they have all the people using Waze, there’s a certain percentage that will post things like oh, that traffic is bad today, oh, there’s a cop over there. So it’s continual real time data being fed in by a certain percentage of users that gives you that data is the value that creates the map, the real time useful map. And yesterday’s map is of no value. So it’s real time continuous data coming in, that creates value in real time. And they have it and others don’t. I don’t think it’s about the data. I think it’s about the users. I think that’s a standard platform business model with a lot of users who are contributing content the same way a lot of people leave reviews on TripAdvisor and hotels, I think it’s the same thing. And okay, it’s data is that different than, you know, people leaving reviews for hotels on sea trip or Expedia? No, it’s the same business model. So I don’t really even think it’s about the data. I think the key asset is not the data. I think the key asset is the Network of Users who are participating or giving, you know, providing information and consuming information. That’s the asset. So I don’t buy it. But you’ll hear that one all the time. Okay, let’s finish up here. Tech Performance Network effects, I’m not going to talk about that one, because I’ve been going on for a while. Okay, now we’re going to sort of finish up with embedding, and other small digital stuff. And these are sort of the last things on their list, which they describe as the least powerful. And they call them social network effects. And they point to three network effects that are social in nature. One is a language network effect. One is a belief network effect. And one is what’s the last one? Oh, they say bandwagon. Oh, and tribal. So for tribal bandwagon belief, and social. And I don’t really buy it. But I think I think they’re accurate in the sense that these are real phenomenon that you should watch for, but I think they’re relatively small. And I don’t think they’re network effects. So the first one is basically language. I’ve talked about that before that this one okay, I’ll argue this is a decent network effect. This is a standardization network effect. Everyone in China speaks Chinese. That saves you a lot of cost, it makes things interoperable makes things much better. Most countries collapse to one language, usually and globally. Most people speak English, Spanish or Chinese. So that is definitely network effect. They point to things about the fact that if you brand your company strong enough people say things like Let’s google it, or let’s bring it but no one ever said that. I don’t really think that’s a language network effect. I think that’s just customer capture and share of the consumer mind. Second, one is belief. The idea that you know, religion. Bitcoin, to some degree is powered by belief that As beliefs become more valuable to believers, the more people that believe them. That’s the network effect in their argument. I think there is truth in that. I’m not sure it’s a network effect, I think it’s an important phenomenon. What is the value of gold? It has no actual economic value, you can buy it and sell it. But it’s mostly in the belief that it stores value, therefore, you can sit on it and sell it and get your money at if you need it. And bitcoin is kind of the same. Bitcoin is a protocol and network effect. But you could also argue it’s a belief network effect, as long as people believe it, it becomes valuable and the more people that believe it, it matters. So you could say currencies are like that. Some religions are like that. Ideologies are like that. That’s basically their argument. I wouldn’t put any of that under the idea of network effects. I think that’s a pretty far stretch from what we’ve been talking about. I think that is more about share of the consumer mind. Everybody likes I know Coca Cola. Why? I don’t know, they just do. Is it because more people drink it? And we see it probably. So I think trying to separate that out is? I don’t know. So belief, I’m not that big of a believer. And the other one they have, which is similar as tribal, which is schools, regions, languages, sororities, fraternities, religions, you know, we’re all we’re all alumni of this school, we’re more likely to hire that person, because they went to that school. We’re all from Northern Beijing, or let’s say, northern China, we’re more likely to hire someone, you get this in China all the time. You know, where are you from? Needs, I nearly ran? Oh, I’m doing better. And I’m, you know, everyone always mentioned their village or their hometown. Okay, so this is sort of tribe for nation, I would. I think that’s another idea that’s valuable. But I don’t think it’s a network effect. I think it’s community building, which we’ve talked about, which is, you know, one of the most powerful assets you can have as a brand is to build a community around whatever your product or services,
Jeffrey Towson 42:21
they and to build the community, they have to kind of love your thing. But they also have to share and do interactions with others. So we’re a running club, Nike Running Club, China, the key activity is not the content that Nike gives them, here’s some tips on how to run better know, it’s creating activities that people can do together. It’s the interactions between people and the sharing of content between people in a group that creates your community. I think that’s a very powerful thing. I don’t really view it as a network effect. And then the last one we’ll finish up is embedding, which I kind of mentioned about which is about, you know, the more you can get people to embed YouTube videos into other websites. Well, that increases the scale of YouTube, you could argue that embedding strengthens the network effect of YouTube, because you’re basically bringing on more viewers. So you’re increasing one side of the platform by embedding tick tock is the same. You could say Amazon affiliate links also increase the network effect, they definitely increase scale. If everyone’s putting your stuff into other web pages, okay, you’re increasing your scale, and they’re doing the work for you. So it’s a growth mechanism. But you could also argue that it’s a type of network effect, it strengthens that. Okay, fine. So there’s a couple of things. Everything is a growth mechanism. I think it can be a network effect. I think it can be a switching cost. Zoom, I looked at a couple years ago, and I wasn’t I never thought zoom had any real competitive strengths. I thought it was a cool app, and a great service that got out quickly. But I didn’t see any network effects. I didn’t, I thought it was going to be a commoditized technology that was going to be free, a feature, not a platform. But I did argue back then the one thing that Zoom could do is embed itself in as many other enterprise apps as possible, because embedding can be a type of switching cost. You know, if you integrate your product or service into another company’s operations, or customers operations, it’s very hard to rip it out. So if they embedded zoom in to every other enterprise app out there, it will be very hard to for everyone to rip it out. So my argument was zoom should embed itself into everything and lock itself in before those companies create their own version because At the end of the day video conferencing, it’s going to be a pretty standard tech. I mean, it’s a commodity technology. That was kind of my argument. So I think it’s a cool idea. And you can look up if you want to read about embedding, it’s a whole idea. People talk about it in language. Machine learning, people talk a lot about embedding, because it’s the idea of taking complicated data and making it simpler, which is important for machine learning. It pops up all over the place as an idea. You could say what open AI is doing with their API’s is they are now embedding intelligence into everybody else’s apps. That’s definitely happening. You know, every app now is becoming intelligent. They used to be kind of dumb. Now they’re becoming smart. How well, you, you embed open AI in it, that’s how you do it. Word documents, everything is getting that. So that’s a type of embedded but so it’s a cool idea. I just don’t I find it too fuzzy to be helpful. Like, it’s kind of like, okay, in a connected digitized world. Isn’t everything kind of embedded or connected into everything else? Anyways? I mean, what’s the point of trying to draw the distinction? You want to be connected to everything else? Okay, fine. Got it. I’m not sure that helps. But anyways, that is kind of what I wanted to go through content for. This was a bit of theory, we’ll call it theory day. I think the network effects the 16th. They have listed, I think it’s definitely worth your time to go through and read it and look at the prioritization they put, I think there’s a lot of there’s a lot of knowledge and expertise there. It’s different language than I use. But it’s, it’s pretty good. I agree with a lot of it. The smaller ideas, embedding tribal network effects, they say social network effects, belief network effects. I think those are those are all important phenomenon. I don’t think they’re really network effects. There were thinking about as well, the one that I’m thinking about a lot within those smaller ideas is the idea of community building. I think that’s a very powerful phenomenon in digital, and I don’t quite know how to get my brain around it yet. community building and composability are sort of the two candidates I have in the back of my brain as a really powerful digital superpower. Those two, and I’m still kind of thinking about him. Anyways, that’s where I am. So bit of theory for you today. Hopefully, that’s helpful. And what else bandwidth Oh, I didn’t even talk. I skipped over bandwagon effects. You know what that is? I don’t think bandwagon is a network effect. But I’m sure they would disagree with me. But yeah, it’s it’s worth doing. And they have a podcast, I’ll put the links and it’s worth listening to. And that is the content for today. Let’s see any fun stuff I’ve been doing? I’ve just been working and planning trips and all that. I did. Oh, yeah. This is a terrible bit of advice. I was watching too hot to handle which is this Netflix show? It’s so bad. Like, it’s so bad. It’s good. For those who aren’t familiar, it’s this the show where these? I don’t know, I guess attractive, super popular Instagram types all go to an island and you know, they’re all hooked up creatures, and they’re not allowed to hook up. And you know, it’s, it’s literally reminds me of like eating a box of doughnuts. Like it’s pretty good. And then you feel really sick about the whole experience afterwards. That’s how I feel watching the show. Anyways, they have a couple more like too hot to handle Brazil, which I watched some of that. I got about three episodes, and I couldn’t take it anymore. And then I watched too hot to handle Germany, which was basically like too hot to handle but people are freakier I don’t know what’s going on in Germany. But there was a lot of freaky stuff. I didn’t get past episode two. So it was it was too weird for me. And there’s another one too hot to handle Latin. I think it’s too hot to handle Latin which is like Mexico or someone I may give in and watch that at some point. Anyways, it’s really awful. But I’ve now watched three different versions of the series. So I don’t know if that’s advice enough but is the first episode is worth watching just because you like. Yeah, and then probably after the first one you get it? That’s like eating the first donut. Yeah, watch the first episode and then just turn it off. Don’t eat the second donut. You’ll regret it later. I always that was my week. Okay, let’s see. I guess that’s it. Hope everyone is doing well and I will talk to you next week. Bye bye.
I write, speak and consult about how to win (and not lose) in digital strategy and transformation.
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