- Platform business models and network effects
- Competitive advantage = network effects
- The power of network effects
- The era of platform business models
- Types of network effects
- Direct or same-side network effects
- Indirect or cross-side network effects
- Virality vs. network effects
- Beware of negative network effects
- Key takeaways on network effects
Platform business models and network effects
Network effects have become an essential element of a successful digital business, for several reasons. First, the Internet itself has become a facilitator for network effects.
As it becomes less and less expensive to connect users on platforms, those able to attract them in mass become extremely valuable over time.
Also, network effects facilitate scale. As digital businesses and platforms scale, they gain a competitive advantage, as they control more of the total shares of a market.
Last but not least, as we will see, network effects are considered among the defendable, or what confers to digital business, a competitive advantage.
Where in the past linear businesses gained a competitive advantage by buying assets and controlling supply chains. Digital companies gain competitive advantages by building network effects.
As we’ll see there are different kinds of network effects. And network effects can also be reverse or negative.
Competitive advantage = network effects
If you think about something like Instagram, the software is great but could fairly easily be replicated. But the network of users and the content they create is impossible to replicate. That is where the value is created. Or think about Reddit where the community creates the content. Or think about Waze where the users generate the data about which way has the least traffic.
In the era of platform business models in most cases, technology can bring an initial advantage. However, over time technology might become a commodity as it can be easily copied and replicated as it becomes wider adopted.
What can’t be easily copied is the community comprised of the network of users part of the platform. That is because users interacting produce several positive network effects.
Positive network effects
As more users join the platform the more it becomes valuable. Think of the case of a dating app with a few users in your town. How many chances there are the app would be able to match you up quickly? A few, thus the app won’t be much valuable to you
The interactions between users also generate data that the platforms can control, analyze, and own, that can be leveraged on to create a lasting advantage. Therefore, the value of the network isn’t necessarily in the technology but in the data produced by the interactions
From transactions to interactions
As network effects become a primary advantage of the platform business, which can’t be easily replicated. The company needs to shift its mindset and manage the interactions in the platform. This is a key step to take. Think of the case of a company like Amazon, which over the years passed from being e-commerce to a platform business.
A platform business model implies that the company in charge of the ecosystem that generates those network effects learns how to keep those interactions happening. This implies a shift in mindset to think in terms of product sales to interactions happening on the platform.
To understand this concept read the full interview on digital platform businesses.
The power of network effects
Image credit: Ray Stern, CMO of Intuit.
Network Effects enable digital businesses to gain value quickly. That is because they have built-in asymmetries between the costs and value of the network. Where costs might increase linearly, the value of the network increases exponentially as the network grows.
The era of platform business models
Image Credit: Applico, Inc.
That’s because, in theory, platform business models manage to scale efficiently. Thus, where a traditional business, at a particular scale, it reaches a point of inefficiency where diseconomies of scale pick up.
A digital, platform business, might scale so efficiently, to be able to grow close to the total size of the market. This enables the formation of monopolies.
Thus, network effects become the real “assets” in the digital era. However, those “assets” won’t be seen on the company’s balance sheets.
Quite the opposite, platform business models enable exchanges among a large number of people within a network, but in most cases, they don’t control any of the assets owned by the people in the network.
Instead, those platform businesses only facilitate exchanges. And as a facilitator, they collect a “tax” as a transaction fee. That’s why modern platform business models might look and act more like nations, rather than corporations.
Types of network effects
Examples of network effects
Source and Image Credit: nfx.com
NFX points out thirteen main types of network effects:
- 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)
As James Currier, from NFX, points out, “Network effects have emerged as the native defense in the digital world.” Within network effects as a defensible NFX points out three key elements: scale, brand, and embedding.
It is essential to highlight that the types of networks above are not exhaustive, neither set in the stone. But the framework offered by NFX is a great starting point to understand how network effects work.
In this guide, I want to focus on two main kinds of network effects:
- Direct or same-side.
- And indirect or cross-side.
Direct or same-side network effects
Direct or same-side network effects happen when an increasing number of users or customers also increases the value of the product or service for the same kind of user.
Direct network effects usually follow Metcalfe’s law (one of the laws on the basis of network effects).
In short, Metcalfe’s law, developed in communications theory, states that, as users of a network grow, this enables the exponential growth in the number of potential connections, thus also an exponential increase in utility of the platform.
Indirect or cross-side network effects
Indirect network effects aren’t necessarily symmetric. In other words, in some cases, increasing one side of a platform might have more profound effects, than increasing the other side.
For instance, in Uber’s case, as a two-sided platform, driven by the exchanges between drivers and riders, the former plays a more critical role.
Indeed, Uber uses dynamic pricing strategies that make the service less convenient for riders, but it keeps drivers going back to the platform.
Also, indirect network effects might not necessarily be reciprocal. Thus, increasing the one side of the network might improve the service for the other side. But the same might not apply if the other side of the network is increased.
Virality vs. network effects
I want to clarify the critical difference between virality and network effects. Often (too often) those terms are used, or thought of as the same thing.
Thus, a network effect is a way to create a lasting competitive advantage. And to offer more value to users. A viral effect is primarily a marketing tactic to gain traction and visibility for your product.
Network effects and virality can work together. For instance, as more users join through viral effects, if the platform is taking advantage of network effects, the more also it will become prone to improve its virality.
As highlighted in the interview with Sangeet Paul Choudary, best selling author of Platform Scale and Platform Revolution:
And he continued:
So network effects, an example is the more users who are on Airbnb. The more hosts are setting up listings on Airbnb, the more choice there is for travelers. Now that’s a network effect.
Or take the example of YouTube, the more videos that are being set up on YouTube, the more choice I have as a viewer to view things on YouTube.
Instead, virality happens when:
Now, if I take a video from YouTube and embed it on Facebook, that’s not a network effect, that’s a viral effect.
So a viral effect is a growth tool that brings external users back to the platform. Whereas a network effect increases the value on the platform, just like adding more than more and more videos onto YouTube.
Beware of negative network effects
As highlighted in the interview with Sangeet Paul Choudary, author of Platform Scale and Platform Revolution:
The more people using the highway system, the more traffic jams you end up in. Or the more people in a room, the less likely it is to have good decent conversation just because it gets crowded, but also because everybody is talking too loudly and so you can’t hear and you can’t meet the right person within that room.
So we understand congestion in traditional terms because in the traditional world we have networks that were limited by scale.
When it comes to the digital world, instead, where there are less scale limitations. Or at least those those can be initially overcome.
Thus, at least on the congestion side it’s very hard to reach a point of negative network effects (for instance, if the platform crashes for usage).
Congestion, therefore, is primarily about usage of the network.
In the bits world, it is possible not only to overcome congestion but also to build a more solid engineering infrastructure as usage increases. Of course, network congestions can also be bad for platforms (poor network design, over-subscription, security attach due to over used network parts).
Another form, of negative network effect, can take place for platform business models.
Where network congestion is primarily about the size of the platform.
As the platform scales, it gains network effects, as it becomes more valuable for an increasing number of users.
Yet, also for digital platforms scale might create situations of diseconomies.
What happens is the more users come on board, the more difficult it becomes to manage quality of the interactions.
Thus this makes the digital platform to make sure to have a mechanism to manage the quality of those interactions to avoid that those negative network effects pick up.
If we think of social media, or publishing platforms at scale, among the most difficult task, that requires dozens if not hundreds of engineers and humans (Google might have thousands of human quality raters) to fix spam and low quality user-generated content.
Examples of negative network effects
Google case study
In a platform that leverages direct side network effects after a certain number of users, it might also result in increased spam on the platform which can’t be easily managed through automated processes, or human curation, thus diluting the value of the platform.
Take the case of how Google, back in the days, it was offering an index of the web with its core algorithm called PageRank. At a certain point had to figure out also how to manage the spam on its index.
Practitioners understood how to trick Google’s core algorithm into showing up spammy results on top of that. This would have jeopardized the value of the overall platform, thus resulting in a diluted value of that.
Thus Google had to start to build up a solid team dedicated to spam and update its algorithms to avoid spam in search results in order to keep its platform valuable.
Airbnb case study
Take Airbnb where, for instance, more hosts improve value for users on the platform. On the two-sided more value is created by more hosts (travelers have more selection)? On the other hand, the value of the platform is diluted on the hosts’ side of the platform.
They will find themselves competing for the same users.
Thus it becomes crucial to understand what’s the proper ratio between travelers and hosts on the platform to make sure it keeps being valuable on both sides.
Tinder case study
Take the case of a dating app that draws value from having people encounter locally. If more users join but from locations spread across the world, no many local network effects are picking up.
Quite the opposite. If a critical mass is not reached at each local hub, the platform might lose value quickly. Imagine the case of a woman looking for a date. The faster she will be able to meet the best match.
The more the platform will be valuable. However, to be very valuable, the service has to make sure those people can meet in a place nearby. And it there are no matches available locally, the dating platform would lose value quickly.
Key take on negative network effects
Platform business models can leverage network effects to enable the core platform to become more valuable over time. However, they need to factor in negative network effects, which if picking up might not only prevent the success of the business but also destroy it.
Key takeaways on network effects
- The internet has become a facilitator for network effects.
- Digital businesses work on a set of premises and principles that are different from traditional or linear businesses.
- Network effects have become the “assets” for digital organizations.
- Those network effects don’t sit on companies’ balance sheets. Rather digital businesses can trigger and build them up to create a strong competitive advantage.
- Network effects enable digital businesses to scale efficiency and to get close to the total size of the market.
- Network effects can be direct (when they when an increased size of the network improves the value of the platform for the same kind of users) and indirect (where the increased size of one side of the network improves the service for the other side).
- Network effects are not the same thing as virality. Virality is a marketing tactic to acquire users or customers at a lower cost. Network effects represent a business strategy aimed at creating a long-term competitive advantage for digital businesses.
- Platform Business Models In A Nutshell
- Linear Vs. Platform Business Models In A Nutshell
- What Are Diseconomies Of Scale And Why They Matter
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