Each year a batch of entrepreneurs set out to build the next great online community. Some attempt to build large horizontal platforms where users engage on topics ranging from immunotherapy to the Boston Celtics. Reddit would fit that description. Others seek to create vertical communities tailored to a particular subject and audience, such as Wheelwell for car enthusiasts.
There are many reasons to be on the prowl for the next great online community, either as an investor or operator. A leading reason is that the winners tend to be massive. Another reason is that successful online communities seem to grow perpetually through organic growth, which is the holy grail in startup land.
The unstoppable momentum of organic growth, driven by users creating new content on the platform, is what is often referred to as the “flywheel”. In technical terms, a flywheel is a device that stores energy. The more it’s revved up, the more energy it stores and the longer it can spin unaided. It sounds like magic, but there’s a simple explanation for it—at least as simple as physics goes.
What a flywheel does is it converts kinetic energy into potential energy. Kinetic energy is the energy that an object possesses due to its movement. Potential energy is the energy stored by the object due to its position. Archery provides a basic example. When you pull the bowstring back, you can say that the arrow has potential energy. And when it is released the arrow has kinetic energy.
Another key point about flywheels is that the bigger it is and the faster it spins, the more energy it stores and the longer it takes to slow down. Online communities that have established a “content flywheel” behave similarly.
Let’s take Reddit as an example. The stockpile of registered users is Reddit’s version of potential energy. When those users create content and the content is discovered in Google, shared via social media, or distributed online through other means, then the “arrow has been shot” so-to-speak. In this analogy, the user-generated content is kinetic energy. When new content is created it fetches new traffic and users into the platform, increasing the size of the flywheel and accelerating its rotational energy. It becomes self-propagating. And once that kicks in, good luck stopping it.
To put the power of a content flywheel in perspective, Reddit recently claimed 430M monthly active users. It’s 15 years old and still spreading its wings.
But how does one create such a platform driven by perpetual organic growth? Clearly, it can’t all be distilled down into a simple formula and bottled up in cans to be sold next to ketchup and mustard. It’s no commodity. There is no “secret sauce” that only Italian grandmothers and a few exceptional founders figure out. However, I do believe some of the ingredients are knowable and repeatable. This playbook will describe what those ingredients are, how they work, and what you can do about them in pursuit of building your own startup fueled by a flywheel.
I believe there are seven primary ingredients when it comes to building flywheels in software. Six of them are knowable and I’ll go into detail on each below. One ingredient is something only you, the founder, can figure out. It’s the “secret sauce” that makes your community stand out relative to the rest and is your unique innovation.
Here’s the full set of seven ingredients:
Let’s jump into each, how they work, and what you can do about them.
Let’s assume at this point that you, the founder, have already decided on the type of content community you want to build. It could be for scientists, sports enthusiasts, Chief Information Officers, or be the world’s next horizontal platform to compete with Reddit, Youtube, and so on. It doesn’t matter which option you’ve selected. What matters is you’ve vowed to create a dent in the content universe.
You begin toiling away in your preferred design tool with product prototypes, first starting with low-resolution concepts. After a bit of user testing, you’ve identified a variety of UX snafus, shuffled around the deck chairs a bit, and arrive at a prototype that’s ready for development.
The designs turn into an alpha. You test it with more users. The alpha becomes a beta. You test it with more users. Finally, you’re ready to launch it. You turn on the TV and play the iconic scene from Field of Dreams where the spirit of Shoeless Joe Jackson whispers, “If you build it, he will come.” And like ghosts emerging from a cornfield, users show up and engage with each other like long lost friends. Hours and hours of lively conversations are created and your community is flush with chatter.
Except, that’s not what happens. Conversations don’t spontaneously ignite and engagement is at a whisper. You’ve built it, but no one has come.
This is where your journey to creating the flywheel begins.Kevin Costner’s journey began with designing a field, but yours begins with designing your flywheel and hand-picking your early adopters.
Don’t get fancy. Start with 2,000-year-old technology and 500-year-old technology; paper and pencil. You don’t need modern software to design your first flywheel, so shut your laptop.
I believe there are four atomic units of a 1.0 flywheel:
Those elements represent the common building blocks of a content flywheel.
It begins with a visitor signing up to use the product. After a user has signed up, the user will gain access to the stockpile of content that exists in the application, which they may start consuming. Note that the stockpile of content won’t exist at first. I’ll get to that in the section about solving the cold start problem.
After consuming enough content, some users evolve into creators of content. The content the user creates leads to new traffic headed your way. A common example would be content indexed in a search engine or shared on social media, which fetches more traffic back to your community. Lastly, some of the newly harvested traffic will convert into newly acquired users that sign up to be a part of the community.
With a sketch similar to this, you can begin with a simple conceptual understanding of the content flywheel for your application. Assuming your product has launched and has at least a few hundred users, you can then measure the baseline conversion rates (CVR) at each step in the flywheel.
In the above example, the conversion rate (CVR) for the initial signup is 1.5%. Of the users that sign up, 20% of them go on to consume content in the application and 5% of consumers go on to become creators of content. The new content that is created then leads to new traffic generated for the application.
In this example, I chose the metric of visits per piece of content per month. A practical example would be a question answered on Quora or a thread posted on Reddit. In this case, each question on Quora or thread on Reddit would receive an average of 2 visits per month. Finally, the new traffic generated from the content created by new users leads to brand new users signing up for the product at a rate of 0.2%, which is a fairly common conversion rate for long-tail traffic coming from SEO.
The conversion rate to signup from this traffic is typically lower than traffic that goes directly to an application’s homepage, such as someone opting to go directly to Reddit.com and sign up. Visitors navigating directly to an app’s homepage have relatively high intent, likely because someone told them about the product, which is why the conversion rate is highest for direct homepage traffic.
And just like that, you have your first content flywheel designed and instrumented with empirical metrics. But your homework isn’t done yet. You’ve only completed the first of three assignments. And this one was the easiest since most online communities have a nearly identical 1.0 flywheel. In fact, you can just copy this flywheel and you’re off to a good start.
Now that you’ve warmed up a bit with the 1.0 flywheel, it’s time to tackle the next obstacle, which is to craft another flywheel that’s specific to the consumption piece of the community experience.
Users of your community won’t Kobayashi content without some provocation. You’ll most likely have to coax them into consuming a lot of content in your community through clever product design, a buffet of high-quality content, and other mechanisms that you, the founder, must figure out.
Online communities that have low flywheel momentum are those that begin with very poor information discovery. Take a look at eBay’s community product. I’m not sure it’s changed much over the last 10 years. It looks much like the original forums and message boards dating back to the golden age of Yahoo Groups.
You’ll notice that a modern artifact of today’s online communities is missing—a newsfeed. Every major online community or social network is now oriented around a feed. Why? Because it gets people to engage as a consumer of information at an order of magnitude greater than alternatives. It makes us all Kobayashi’s of content. The momentum in eBay’s flywheel is minuscule compared to the momentum in TikTok’s flywheel because TikTok has a much more enticing consumption flywheel due to a few brilliant product design choices, such as allowing you to consume a feed of highly entertaining videos prior to registering for the product.
Yet there are nuanced decisions that need to be made as to how your product will drive a consumption loop where users come back to consume over and over again. It’s time to pick up your paper and pencil again.
Just like there are a few “atomic units” that make up a 1.0 flywheel, I believe there are a few building blocks to a consumption flywheel as well, which include:
In the below example, I’ve diagramed what a consumption loop might look like for a product like Quora. A newsfeed and weekly digest emails are the primary consumption drivers. The user is then given a selection of product verbs as the core content interaction paradigm, such as upvote, downvote, comment, or share. That data is used to enhance personalization back into the newsfeed, weekly digest emails, and other one-off email notifications.
What’s important is that you map out what the consumption flywheel might look like for your product and that you ponder the following questions while designing it.
Assuming you’ve done a quality job at designing and implementing the consumption flywheel, user engagement should increase. That may reveal itself in an uptick in weekly active users (WAUs) or daily active users (DAUs).
To go back to the flywheel physics, the potential energy within your community increases as a byproduct of enhancing the consumption loop. And with higher potential energy comes another wonderful side effect: high-frequency consumers become content creators. Don’t put the pencil and paper down yet as that’s the next flywheel to design.
The third flywheel is the most important. A thriving online community can’t be built without a healthy consumption flywheel. However, a stellar consumption flywheel can’t be built without a high rate of quality content being created. That’s why it’s the most important flywheel—yet, it is also the most difficult to create as it requires more secret sauce (i.e. innovative thinking) than a consumption flywheel.
Similar to the other flywheels, I believe that this flywheel has a few common building blocks worth understanding.
The below diagram captures what this content creation flywheel might look like. Just as you would with a consumption flywheel, you have to take a step back and ask yourself a few key questions when designing a creation flywheel:
Once the creation flywheel kicks in, you can expect to have momentum as potential energy (consuming users) is converted into kinetic energy (creating users). As lots of new content is generated, acquisition channels accelerate, such as SEO, social sharing, and so on.
With the flywheel designs in place, you can instrument each step in the flywheel to understand where your flywheel might not be performing. In the example below, I may label certain parts of the flywheel with conversion metrics to benchmark how it’s performing. This approach would allow me to diagnose where I perceive there to be weaknesses in my flywheel(s) and come up with a plan of attack for improving each sequence.
The green items would indicate which rates I feel are performing well, whereas the yellow and red items likely require some attention and could be slowing the entire system down.
In the above example, the product has only a 13% open rate for the digest email. I should revisit the content I’m putting in that email and the frequency that I’m sending it. Something is clearly wrong since that’s a very low open rate. Consequently, the digest email isn’t contributing meaningfully to the consumption flywheel, so I may need to find alternatives to doing so.
I would also note the very low conversion rate to becoming a content creator. If only 3% of users that read content also create content, there must be something catastrophically wrong with the user experience or the core product value. Or, maybe that’s okay? Youtube is powered mostly by super-creators. They don’t have a high proportion of users that create videos—most users are consumers. But if I’m Reddit and only 3% of users comment on threads or create new threads, that could be cause for concern. That low of a rate may lead me to believe that most new threads are starting off with a low-quality prompt.
Similarly, I would be concerned with the low rate of visits per piece of content per month. Maybe I haven’t optimized for SEO or social sharing? Maybe I have a huge long-tail of content that isn’t interesting enough to warrant any traffic? That’s certainly the case with Yahoo Answers.
Now that you have the flywheels designed and metrics implemented, you’ll want to convert this into a basic model that captures how your product grows. Translate each conversion rate into a variable in a growth equation. Here’s a very simple example based on the above flywheel and one that we tinkered with at Quora in 2011:
To keep it simple for now, let’s use three variables in the flywheel:
Work with your local friendly data scientist, and they’ll produce a growth equation for you. Here’s a basic example based on the flywheel model:
From a model like this, you can project a rate of growth. It may look something like the graph below, which projects the weekly growth rate of total users:
What’s great about using this flywheel design and measuring approach is that you can “pull levers” in the model and find where the model is most sensitive in the long run or at a given point in time.
For example, if you were to increase the average number of visits per month per piece of content from 2 to 2.5 viaSEO improvements for example, you can project the impact on overall growth. And if you modeled that effect against increasing the conversion rate to signup from 0.2% to 1.%, you may find that one lever implies a greater net effect on growth than another. Or, that optimization in one part of the flywheel may create a larger near-term bump, but have a smaller long-term effect.
That’s how you go about designing a content flywheel, instrumenting measurement, and developing crude growth models to understand what the drivers in your flywheel may be. It’s not a perfect science, but it isn’t meant to be. However, it is a very effective approach to systematically architecting and manipulating your growth flywheel to give your online community the best chance to thrive.
Next, we’ll dive into the classic chicken-and-egg problem that online communities face. How do you get people to signup for—‚and engage in your community— when it currently has little-to-no users and engagement? A flywheel doesn’t start on its own. It needs an initial thrust, which is what the next section is all about.
The hardest stage of a community and content-driven application is day one. How do you compel people to create content within the community when very few users and very little content exists?
It has to start with what I call the “white-hot coal” approach to establishing early adoption. You don't want to "get rich quick" with 1 million users because you pulled strings at TechCrunch and hacked together a waiting list, etc. Instead, aspire to the "white-hot coal" launch.
A big top-of-funnel doesn't mean you have product-market fit and people love your online community. You create your own false narrative with the big bang launch. Think Viddy with their Facebook open graph integration or Jelly when it launched to compete with Quora. Both were big bangs, but didn't have product-market fit. The "white-hot coal" approach advises the opposite: intentionally constrain growth until PMF is clear and the only thing holding it back is more oxygen, i.e. public launch. Quora and Instagram spent 1-2 years iterating on the product and hand-selecting the first few thousand users.
Taking this slow—but steady approach—gives you time to understand WHY it works, and for WHOM it works, before opening up adoption. It requires an uncomfortable level of patience. In return, you gain the insights necessary to make quality decisions when scaling it from 1 to N. Marketplaces commonly make this mistake when launching in more cities before they establish repeatable playbooks for supply and demand acquisition. Online communities make this mistake by opening up for broad adoption before understanding the engagement mechanisms and establishing an initial pattern of high-quality, repeated usage.
Once you've established the white-hot coal of a small but deeply engaged customer base, opening it up must also be done at the "right" pace. Too broad/quick of a launch can create a backdraft i.e. quick inflow of oxygen leading to a superheated fire that burns out quickly. The startup equivalent of backdraft is rapid expansion followed by contraction. It's incredibly difficult to know what the "right" growth rate (i.e. "oxygen") is. It's case-dependent, but I do know that all else is futile without that white-hot coal.
Think small at first. Very, very small. In the words of @paulg: "Do things that don't scale" for as long as possible and only consider a big bang launch after the white-hot coal is established. Hand-pick your first users. Know all of them by name and listen to them daily.
To make things more concrete, here are the broad strokes to follow when solving the cold start problem:
Let’s take it from the top.
You won’t find high-quality early adopters for a new content-driven application by running Facebook ads. If your startup is already doing this, stop immediately. Buying early adopters is the path to burning money and learning very little about who the community is ideal for.
Another issue with paying to acquire early adopters is the lack of a personal relationship with them, which means you have no influence over how they use the product. You want your early adopters to be fully bought into your vision for how it should be used and you’ll want to guide them down that path. What you want from early adopters of your community is high-quality participation and you’re more likely to get that with hand-holding.
I commonly meet founders who want to take their product to market with paid marketing. I don’t know where this method came from, but it is disastrous for startups. When you first launch your product, you’re still in hypothesis mode. Do I have the right product and have I built it for the right person? Answering those questions requires proximity to your users. You need to be so close to them that you can tell what kind of deodorant they use. How else can you validate if you’ve built a product that people care about and if you’ve delivered it to the right type of customer? This is Product Market Fit 101. It can’t be done from a distance. It must be intimate.
Establishing early traction starts with manual labor. Get out an excel spreadsheet. Write down the names of people that you know the best and can lean on to be your earliest testers. Or, if you’re building a product for a user type that you don’t have direct access to via your personal network, hop on Reddit, Facebook Groups, and any other niche network you can find and start building relationships with the people that may eventually become your early adopters. This approach has worked for LinkedIn, as well as for WhatsApp. Don’t avoid doing this work simply because it’s tedious and doesn’t scale.
In the early days at Quora, each beta user of the product was a close friend, family member, or former colleague of the original employees. By appealing to them as a close connection, we could provide structured guidance (and subtle pressure) to ask them to act as role models in the app. For example, we did not want Quora to be like Yahoo Answers because the content was terrible. The information shared was very low quality. It was a mile wide and an inch deep, so-to-speak. We wanted Quora to be about finding the most interesting and relevant information that couldn’t be found elsewhere. If we were successful at that, then people would come to Quora because of its unique basket of human knowledge.
To that end, we set a very high content quality bar. If you were an early user of the product, we expected you to contribute unique questions and write thoughtful answers. Did Einstein’s descendants inherit his level of intelligence? Well, you can find a fascinating answer to that. For history buffs, you can find an incredible collection of WWII photos. I even wrote a detailed answer about what it’s like to go to Mount Everest. Nearly all early employees acted as prolific creators on the platform to demonstrate the expected behavior.
Quora was a block of clay and we all had our hands on it to ensure we shaped it in a particular direction. Several of the early employees, friends, family, and colleagues we brought into the alpha and beta versions remain as some of Quora’s all-time best contributors.
And, because of our personal connection with all of the earliest users, they felt a sense of responsibility to use our new application in the way that we were using it ourselves. For Quora, that meant exceptionally high-quality questions and answers based on someone’s experiential knowledge. In other words, we wanted them to write about what they knew best. That also explains why Quora became known in the early days as one of the best repositories of Silicon Valley knowledge— thist was intentional.
Jason Lemkin has become a central figure in SaaS venture investing and company building at least in part because of his use of Quora. He has well over 3,000 answers and 45,000,000 views and growing. He was an early adopter and continues to share his expert insights.
Every startup wants to storm Paris. But the question is, what is your Normandy? You have to have a precise and almost comically constrained beachhead of early adopters and early content creators.
For us, it was our Silicon Valley connections who wrote excessively about Silicon Valley insider knowledge. What we did with Silicon Valley content on Quora is the software equivalent to what Tesla did when they came to market with their first car, the Roadster. It was intentionally designed for a small, but exceptionally engaged and enthusiastic audience.
Assuming that you’ve kept your focus narrow and managed to ignite a flame with a paltry, yet passionate base of early adopters, you’ll eventually want to expand adoption. But how should you do it? Honesty, there isn’t a perfect playbook for this. But one option to consider, especially if maintaining content and engagement quality is important (which it commonly is), is to allow your early adopters to invite and onboard other users into the community.
Superhuman has taken an extreme view of this approach and it has worked out incredibly well for them. An alternative is to enable invitations, but with frequency caps. For example, each early adopter can invite a maximum of 3-5 new users. The scarcity forces the user to think through who they believe would be a great addition to the content network. In my early days at Quora, I invited a few of the best company builders I knew because I wanted them to provide answers on topics I was interested in.
A seed-stage startup I invested in is taking this approach right now. Each early adopter will be able to invite a few people to join, but not more than that. It will allow them to grow by 3x - 5x organically based entirely off of invitations. You may ask why they would intentionally limit their growth? The reason is they want to maintain a high engagement and quality bar, which I’ll discuss in more detail in the next section.
Thanks to Youtube, Reddit, Twitter, Facebook and so on, most of us are familiar with the important and complex role that moderation plays in massive online communities. There is no such thing as “perfect” community moderation so an ideal solution does not exist. But there are guideposts that can be followed when it comes to thinking through the role of moderation within your content-driven application.
The key thing to consider at the outset is why moderation is essential. To put it simply, it’s because people can be jerks and most people don’t want to be around a lot of jerks. Would you want to go to a town hall discussion about an election topic where any citizen could spout off at the mouth at another, saying vile and disruptive things, without recourse? Nope, me neither. In the analog world, we have policies and procedures to enforce decorum. If you shout down the judge, you’re held in contempt of court and carried away. Online communities require policies that enforce a code of conduct as well.
Here’s a user review left in the app store for the anonymous social app Whisper. It only took a few seconds to find it and is a great example of the downsides of an anonymous identity model and how difficult it is to moderate such platforms.
“A friend of mine recommended this app to me and it’s been great and all — minus all the incredibly narrow minded people on it and the men all older than 25 who really only use this app to send pictures of their body to other people. it’s a great way to spread peoples’ thoughts but without an identity. i think it’s a great idea, but really it’s not being used in the way it should...”
This commenter loves the idea of the app, but it falls apart in practice. Without a moderation model that requires people to use their real identity, it’s hard to hold people accountable for their actions. As a result, the quality of participation erodes and most people opt out of anonymous communities because they inevitably turn ugly. It’s the same reason that most major online publications have turned off comments on their articles.
As the creator of a content community, the question you must answer is “What does quality mean for my product, and how do I enforce it?” I can’t give you that answer since it’s unique to each online community. But I can talk about the various levers at your disposal when it comes to stitching moderation into your product from inception to scale.
From my perspective, there are three methods for moderating behavior within a content application:
Let’s talk about each.
An official company policy on moderation is a common approach. The company determines what is and is not okay to say or do based on their worldview and the vision for the company. These moderation policies, meant to enforce some minimum bar of quality participation by its users, are crafted by euphemistically named teams such as the “Trust and Safety” team.
I say it’s euphemistic because they are censorship teams. They determine what you can say and do based on their collective preferences and beliefs. Some of the restrictions are enforced by law—such as child pornography—which is a great thing. But many policies are selected due to their preferences.
For example, Twitter has a policy that doesn’t allow users to display pornographic or violent content in profile pictures or header images. However, a user can tweet pornographic content. It will be obscured with a “sensitive content” label, which then puts the control in the hands of the user if the user chooses to click a button that then reveals the obfuscated material.
This approach is not governed explicitly by state or federal law. It is a moderation preference that reflects Twitter’s worldview and vision for the company. Similarly, if you choose to build an online community, you’ll have to start by designing the moderation policies to censor what can and can’t be said or done on your platform.
At Quora, our quality definition was aligned with the substance of questions and answers. We wanted a community that represented the best of human experiential knowledge. That meant that we were happy to remove questions that were antagonistic towards an individual, such as one user asking another user a very personal or accusatory question. Our policies also meant that we would remove answers with similar characteristics. We did not accept abusive answers such as people using f-bombs or attacking other users of our service. Civility was paramount, so we had company-created policies in place to preserve courtesy.
As your community begins to scale and evolve, you may need to enlist the help of others to help you identify and draft moderation policies to keep up with the changing nature of the community.
Several examples can be referenced. One version of community moderation that enforces quality participation is the Yelp Elite. Another version would be the now-defunct Quora moderators. An often-criticized example would be Wikipedia moderators.
Community moderation is tough. It’s like managing a growing classroom of students that all begin to think that they should be the teacher. Be careful when enlisting community moderation from people that aren’t official representatives of your company. If the community gets large enough and is left unchecked, they may come to believe that the content platform you’ve created is theirs, not yours. Wikipedia preferred this fully decentralized approach. It’s led to broad access to a lot of great content, but a long history of conflict and complaints as well. At one point, the moderators in charge of the Spanish version of the site went rogue in response to Wikipedia considering selling ads on the website. Proceed with caution when creating community moderation programs.
A superior alternative to community moderation is feature-based moderation. This approach is increasingly enabled by advancements in machine learning and produces better outcomes at scale than a team of human moderators.
You use products all the time that rely on UI features + machine learning to enhance the experience and maintain quality controls. If an answer on Quora receives enough downvotes then the answer will be “collapsed”, i.e. hidden. The ratio of likes to dislikes and the volume and velocity of likes helps Youtube determine which videos to highlight on their home screen versus eject into the ether.
Obviously, it takes a lot of data before these mechanisms can kick in and productively manage the quality of your user experience. When first getting started, you will have to rely mostly on human moderation. Thankfully, machine learning tools are becoming increasingly available so more startups will have access to these scalable moderation tools than in the past. What they may mean for your content platform is you can more quickly (or completely) bypass the community moderation step and move towards a machine learning-driven model compared to startups before you. Consider yourself lucky!
As you might have observed by now, building an online community is strenuous. If you want to make it even more difficult than it already is, you’ll try to boil the ocean by encouraging users to create content and engage in a wide range of topics. This is a mistake. As I mentioned above, you can’t try to sack Paris right out of the gates. You must first find your Normandy/your beachhead. That’s not only true with the specific type of early adopter you pursue, but it’s often true with the category of content you want the early adopter to create and engage with.
Many online communities need to grow like Amazon. Pick one product line, make it exceptional, and then use the momentum from that product line to expand into adjacencies. Amazon started with books and eventually moved into jewelry, DVDs, and so on. What content will you have your users focus on at the birth of your community?
At Quora, we started with content that was familiar to us: technology. After we grew to the low tens of thousands of users, we picked the next content verticals to go after. Thankfully, the playbook for expanding into new categories of content closely resembles the playbook for solving the cold start problem. It entails hand-picking your early adopters, building a personal relationship with them that allows you to exert pressure on them such that they engage in your community in a productive way, and then giving them distribution to encourage them to create more great content and help build out the new category of content.
The most common mistake I see made when attempting vertical expansion is skipping the part where you hand-select early adopters. Not all categories will require this approach. A bit of good luck and serendipity sometimes drops vertical expansion on your doorstep. That’s especially true once the platform is large and established.
How is it that YouTube’s content library continues to expand into an increasingly large long-tail of content categories? Well, it helps that YouTube is a household name and that it offers the potential for enormous distribution to any new creator that shows up with something special. For example, there are tens of millions of views for standup reaction videos. That’s right. People post videos of themselves reacting to stand up comedians. YouTube certainly didn’t have this as part of their planned vertical expansion.
These anomalous behaviors happen without YouTube’s orchestration. But you’re not YouTube, so you can’t rely purely on serendipity. In the early days of an online community, vertical expansion may need to be driven through the good ol’ process of handpicking early adopters, rolling up your sleeves, and nurturing the first creators for a new content category until it’s clear that the seeds have started to sprout. That’s what we did in the early days of Quora and that’s what I see fascinating new startups like Golden attempting to do within various technical fields.
Creating an online community that thrives is brutally difficult. But, when you get it right, they’re a juggernaut.
Doing so requires the artful construction of a core flywheel, a consumption flywheel, and a creation flywheel. It also requires masterful selection and execution on an early-adopter effort to crack the chicken-and-egg problem, not only for the initial beachhead, but also for subsequent content categories you may want to expand into.
Along the way, you can’t sacrifice user experience. Content and engagement quality has to be maintained despite the community growing. It’s like stuffing your thumb into the dam wall only to find that each hole you plug reveals a new crack in the foundation.
To top it all off, you have to figure out what your “hook” is going to be. What is it that people will come to your community for that they can’t find at others? Is it innovations like AMAs (Ask Me Anything) that platforms like Reddit and Quora helped popularize? Is it an incredible database of content that you can’t find elsewhere? If so, how do you compel people to share with you what they haven’t shared with others? That requires innovation as well. In the early days of Quora, several employees built relationships with inmates at San Quentin Prison to give them a voice and megaphone. Beautiful prose came out of the cellblock and made its way onto Quora’s pages.
The above strategies are fruitless without a hook. That’s why most online communities never take flight. They simply don’t offer a 10x better experience relative to the alternatives. Of all of the questions I outlined in this essay, this question remains the most important: What unique value am I going to provide that other communities do not?
You must begin with a strong hook. Then you can follow the playbook outlined in this essay to help it grow. For inspiration, here are examples of product hooks that helped establish some of the world’s most successful online communities.
Without a hook, you won’t have a carrot you can dangle in front of early users to entice them away from a myriad of other online communities that they have at their disposal. This is the “secret sauce” that only you, the founder, can be responsible for.