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by
Andrew Chen
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January 6 - December 31, 2022
The entire ecosystem stays on because the value is in bringing everyone together. That’s the magic.
The “effect” part of the network effect describes how value increases as more people start using the product.
First, does the product have a network? Does it connect people with each other, whether for commerce, collaboration, communication, or something else at the core of the experience?
And second, does the ability to attract new users, or to become stickier, or to monetize, become even stronger as its network grows larger?
Most products these days are low technical risk—meaning they won’t fail because the teams can’t execute on the engineering side to build the products—but they are generally also low defensibility. When something works, others can follow—and fast.
Network effects are one of the only protective barriers in an industry where competition is fierce, and defensive barriers are weak.
Look at the reality: there are weak advantages to being first, since the winning startup is usually a later entrant. And the winner usually doesn’t take all, and instead has to battle a number of other networked products over control of different geographies and customer segments.
Said plainly, each time a user joins an app with a network behind it, the value of the app is increased to n^2. That means if a network has 100 nodes and then doubles to 200, its value more than doubles—it quadruples.
The network effect version of this in the technology industry happens when there is “overcrowding” from too many users. For communication apps, you might start to get too many messages. For social products, there might be too much content in feeds, or for marketplaces, too many listings so that finding the right thing becomes a chore. If you don’t apply spam detection, algorithmic feeds, and other ideas, quickly the network becomes unusable. But add the right features to aid discovery, combat spam, and increase relevance within the UI, and you can increase the carrying capacity for users.
Cold Start Theory lays out a series of stages that every product team must traverse to fully harness the power of network effects. The curve represents the value of the network as it builds over time, and is shaped as an S-curve with a droop at the end. There are five primary stages: The Cold Start Problem Tipping Point Escape Velocity Hitting the Ceiling The Moat Figure 8: The stages of the Cold Start framework
I describe an approach that focuses on building an “atomic network”—that is, the smallest possible network that is stable and can grow on its own.
Imagine a network launch as tipping over a row of dominos. Each launch makes the next set of adjacent networks easier, and easier, and easier, until the momentum becomes unstoppable—but it all radiates from a small win at the very start. This is why we so often see the most successful network effects grow city by city, company by company, or campus by campus as rideshare, workplace apps, and social networks have done.
This is where the classical definition of a “network effect” is wrong. I redefine it so that it’s not one singular effect, but rather, three distinct, underlying forces: the Acquisition Effect, which lets products tap into the network to drive low-cost, highly efficient user acquisition via viral growth; the Engagement Effect, which increases interaction between users as networks fill in; and finally, the Economic Effect, which improves monetization levels and conversion rates as the network grows.
Solving the Cold Start Problem requires a team to launch a network and quickly create enough density and breadth such that the user experience can improve in leaps and bounds.
The solution to the Cold Start Problem starts by understanding how to add a small group of the right people, at the same time, using the product in the right way. Getting this initial network off the ground is the key, and the key is the “atomic network”—the smallest, stable network from which all other networks can be built.
There was a certain brilliance behind the 60,000-person drop: On day 1, cardholders simply existed. This permitted Bank of America to sign up all merchants who didn’t already have proprietary credit card programs.
The networked product should be launched in its simplest possible form—not fully featured—so that it has a dead simple value proposition. The target should be on building a tiny, atomic network—the smallest that could possibly make sense—and focus on building density, ignoring the objection of “market size.” And finally, the attitude in executing the launch should be “do whatever it takes”—even if it’s unscalable or unprofitable—to get momentum, without worrying about how to scale.
My advice: Your product’s first atomic network is probably smaller and more specific than you think.
Contrast that to when you peanut-butter your efforts across a whole industry or geography—the active parts of the network rapidly dissipate as anti-network effects kick in, because a network of 1,000 random users of Slack will have less retention than 1,000 users all inside the same company.
This the “hard side” of your network. They do more work and contribute more to your network, but are that much harder to acquire and retain. For social networks, these are often the content creators that generate the media everyone consumes. For app stores, these are the developers that actually create the products. For workplace apps, these are the managers that author and create documents and projects, and who invite coworkers to participate. For marketplaces, these are usually the sellers and providers who spend their entire day attracting users with their products and services.
You might look at a product and think its network doesn’t have sides. Sometimes this is referred to in the industry as one-sided networks, like messaging apps and social networks. But even in these cases, there are active, extroverted users who initiate conversations and organize get-togethers, and there are those who don’t. Nearly every network has them, and the hard side must all be happy for the network to function.
It may surprise you to know that all of Wikipedia—with more than 55 million articles—was written by a small group of users. Not just small, actually, but tiny. Even though there are hundreds of millions of users, there are only about 100,000 active contributors per month, and when you look at the small group of writers who make more than 100+ edits in a month, it’s about 4,000 people.
There are nearly 100 million riders on Uber, but just a few million drivers. There are two billion active users on YouTube, but just a few million upload videos. Even think about all the people who write documents and make presentations versus those who just view or make small edits. This relationship exists everywhere.
Because the hard side is so critical, it is imperative to have hypotheses about how a product will cater to these users from day one. A successful new product should be able to answer detailed questions: Who is the hard side of your network, and how will they use the product? What is the unique value proposition to the hard side? (And in turn, the easy side of the network.) How do they first hear about the app, and in what context? For users on the hard side, as the network grows, why will they come back more frequently and become more engaged? What makes them sticky to your network such that
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In a widely read essay called “Creators, Synthesizers, and Consumers,” Bradley Horowitz, now a vice president of product at Google, described the 1 percent of users who create versus everyone else: 1% of the user population might start a group (or a thread within a group) 10% of the user population might participate actively, and actually author content whether starting a thread or responding to a thread-in-progress 100% of the user population benefits from the activities of the above groups (lurkers)19
Within these platforms, just ask yourself, “If a piece of content was created, and no one saw it, would the creator be disappointed?” If the answer is yes, then social feedback is a key value.
Tinder did this by integrating with Facebook, and Sean also explained how the app was able to build trust: Tinder started by making everyone connect their Facebook, so that we could show the number of mutual friends you had, which built trust. We also made it so that you could only be matched with people who lived around you—we used the GPS location from your phone, which was new.
The Hard Side for Marketplaces Is Usually the Supply Side
Thus the order of operations, at least for most consumer-facing marketplaces, is “supply, demand, supply, supply, supply.”
The key insight in the stories of Homobiles or Tinder is—how do you find a problem where the hard side of a network is engaged, but their needs are unaddressed? The answer is to look at hobbies and side hustles.
However, the trick is to look closer—to segment the hard side of the network and figure out who is being underserved. Sometimes this is a niche, like a passionate subcommunity of content creators for makeup or unboxing that might be better served with additional commerce features.
Networked products are fundamentally different from the typical product experience—they facilitate experiences that users have with each other, whereas traditional products emphasize how users interact with the software itself.
They grow and succeed by adding more users, which create network effects, whereas traditional products grow by building better features and supporting more use cases. It’s why products like Twitter and Zoom and others often seem so simple, and are critiqued as “features not products” that seem trivial at first.
The idea seems to be really basic, as it allows you to take one or two main actions. The entire product experience exists on just a handful of screens, with a small set of focused features. For example, Snapchat lets you send photos to friends. Dropbox is a magical folder that syncs your files. Uber lets you hit a button to get a ride. Slack is a chat product for your coworkers. YouTube lets you watch videos. They’re very simple to use, but also easy to describe to your friends and coworkers as well.
It’s hard enough to build an atomic network; why make it even harder by erecting barriers?
When the network is fully filled out, active, and people are connected in the right way, then the product experience can really shine. This is the Magic Moment, when a product can deliver its core value—whether that’s connecting people for work, entertainment, dating, games, or otherwise. A product that hasn’t yet solved its Cold Start Problem will fail to deliver any magic in its early days. Often, the network will seem empty, like a ghost town. But once the network forms, the Magic Moments start to happen all the time—that’s when the product is ready to expand.
Talkshow was too heavyweight for the creators. You’d say, “Come to my Talkshow” and people ended up treating it like a podcast. The resulting content felt super scripted, and the recordings ended up sounding like a low quality podcast. The content never felt unique enough to consume. The app was too targeted at hosts, and it never felt like it could become a place to just listen to podcasts.24
After working for months on Talkshow, the duo realized that they needed to radically simplify. To make sure creators had a lightweight experience, it would be ideal to easily create content with people already hanging out in the app—that
But it was the next fifty thousand or so people that brought Clubhouse into mainstream culture. The Black creative community—centered on entertainment and media hotspots like Atlanta, Chicago, New York, and Los Angeles—started to join the network in a major way in mid-2020. This was propelled by musicians, comedians, influencers, and creators hosting shows on a regular basis. Some of this activity was directly catalyzed by a16z, but much of it also happened organically. This unlocked the next set of users by late 2020 growing to millions of people globally.
Thinking about zeroes and unfulfilled requests was such a useful concept at Uber that we baked it into many of our more common dashboards, split by city and region so we could understand how often it was happening. I encourage product teams to develop their own form of this metric, laid out as a dashboard of networks—whether that’s divided by geography, product category, or whatever else makes sense. Within each, it can be useful to track the percentage of consumers that are seeing zeroes.
I would take this description and infuse it with network goodness—users are inviting other users, and sharing content from your product across the internet. You search on Twitter, Reddit, and other social media and it’s chock full of your loyal users talking about how good your product is. Engagement goes up as people find more utility from it, and as more users join.
Another method to tip over a market is with a “Come for the Tool, Stay for the Network” strategy.
This is the copy-and-paste mechanism in motion—take LinkedIn’s curated initial network, give them invites to join a killer product, and watch the network scale with more like-minded individuals. This is superior to a centralized PR-based launch, which can fizzle out and become diluted by different geographies, industries, and demographics. Invite-only mechanics amplify a networked product that is already useful for the first few dozen users.
Invite-only mechanics provide a better “welcome experience” for new users as well. To explain why, imagine arriving at a large dinner party. A good friend welcomes you at the door, and as you step in, you see acquaintances, close friends, and a number of new people who’ve been curated to be absolutely fascinating. If that’s the ideal experience for a dinner guest, it’s also an apt metaphor for the best possible entry into a new product experience. Invite-only products can facilitate this, because every new user that signs up is already connected to at least one person—their inviter.
A good product designer wouldn’t allow a random set of feature ideas to be added to the final version of a new app, and in the same way, a mindful designer of networks wouldn’t allow a random set of users to initially join.
For networked products, the curation of the network—who’s on it, why they’re there, and how they interact with each other—is as important as its product design. Starting with a deliberate point of view on who’s best for your network will define its magnetism, culture, and ultimate trajectory.
in its inaugural “Apps of the Year,” Apple selected Hipstamatic as one of four apps—alongside Flipboard, Plants vs. Zombies, and Osmos.34
Importantly, Instagram was built with a network from day one. It had user profiles, a feed, friend requests, invitations, and many other features of a modern social product.
The team took the goodness that Hipstamatic had proven, and added network effects—and the result was spectacular.
While Hipstamatic built a great tool, it was Instagram that used network effects to win the market. The Instagram versus Hipstamatic story is perhaps the canonical example of a strategy made famous by Chris Dixon’s 2015 essay “Come for the tool, stay for the network.” Chris writes: A popular strategy for bootstrapping networks is what I like to call “come for the tool, stay for the network.” The idea is to initially attract users with a single-player tool and then, over time, get them to participate in a network. The tool helps get to initial critical mass. The network creates the long term
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