Deep Dive: Valuing a Web3 Community
Deep Dive: Valuing a Web3 Community
Exploring a framework to financially value the most important web3 growth engine - communities
Gm!
Today we’re going to explore the question of how to financially value a web3 community.
This post is structured into the following sections:
Motivation - Why is valuing a web3 community important?
Landscape - What are the different types of web3 communities?
Benchmarking - What are some metrics for valuing other collective entities like companies & countries?
Understanding the types of metrics
Approach - A framework of questions to ask for effectively valuing a web3 community
Before we begin, we want to clarify that we’re not going to propose a single universal metric to value a community. In fact, we’d go as far as saying we don’t think such a metric exists. Even for companies and countries, there is a buffet of metrics to pick from depending on the context and the application.
In this essay, we’re going to pursue a set of questions that we think are the critical first step to assigning a monetary value to web3 communities.
So, let’s get started…
Why is financially valuing a web3 community important?
Web3 is a broad term for a paradigm of software development where consumer data is owned by consumers and secured through private keys on a blockchain. A lot of application code is open source which means projects can build on top of each other in a really fast and frictionless manner. All of this combined enables human coordination at a scale we’ve never seen before.
For web2 products, user data and network effects are the moats - but in web3 these are abstracted out to the blockchain(s). This is powerful because it distributes the compounding effect of a growing network across participants. So yes, early adopters still benefit relatively more and rightly so (they demonstrated good judgement and took the risk) - but it is much more evenly spread out than the typical web2 companies where a few thousand employees and investors keep the majority of the upside.
This post on data composability really captures this sentiment well, here’s an excerpt,
If Medium were built on open data, Substack wouldn't have to build an editor, interface, and CMS from scratch. They'd build a subscription module that operates on top of the Medium editor and content. You could continue writing in Medium (or elsewhere) and publishing there while using Substack's subscription feature to build an audience and deliver directly to them. (This is what we’re beginning to see with Mirror’s ecosystem with apps for curation, discovery and more.). [source]
The author calls this the unbundling of the data, service and interface stack, visualised below
Another important consequence of code and data being open source is forking. It is a web3 manifestation of the concept of voice & exit. Basically, at any point of time if sufficient network participants feel that the quality of the network is diminishing and they are unable to exercise change, not only can they leave - but they can take their data with them.
One of the more famous examples of this is Sushiswap forking Uniswap, as per this article, apparently, a group of users were unhappy that uniswap didn’t have community governance. So, not only did they fork it but they setup staking incentives to drain out the liquidity from uniswap. Did all of this while being pseudonymous. The best part - 2 months later both exchanges had way higher TVL aaaand(!!) Uniswap eventually implemented community governance.
Something similar is happening with an internet group airdropping the $SOS token to Opensea users. They’ve basically identified a group of users who have some level of affinity towards NFTs (demonstrated by their transactions on OpenSea) and offered to reward them in ways that Opensea refused to. The only reason this is possible is because these transactions happened on a public blockchain via a web wallet (metamask). Now, they can leverage this community to do amazing things in the NFT space or rug pull or just fizzle out - only time will tell. The point is that this is now possible and going to happen more often.
It feels like forking will replace “outrage” & “petitions” because it is simply a way more effective way. Of course, billions of users won’t be writing code and deploying smart contracts - there will be a suite of tools that abstract out the process. The catalyst here is that within a few clicks a competitor can be spun up & users can take their data and relationships (basically the network, or parts of it) with them.
Finally, since a lot of web3 projects have a core team and then rely on their community to build future iterations of the product, there will be some groups that are just way better at this than others. Because the flip side of this argument is that so web2 UX is good and addictive that most of us have gotten used to “free” access to products and content built for us. Most of us aren’t adding value to these platforms beyond watching ads - woohoo.
I hate to break it to you but owning the web might be harder work than you thought - at-least initially. People will need to often pay upfront to use services, groups will need to co-ordinate and make hard product and business decisions etc. This is non-trivial and being able to identify and price communities that do this much better than others will be a skill.
Different types of communities
We think that communities can broadly be classified into the following three categories:
Project communities: These are organised around products like DeFi protocols, consumer apps, layer 1 blockchains, games etc. These help the creators of these products keep engaging with their community for driving adoption, getting feedback on the roadmap, hiring and customer support. This is especially critical because being a contributor or consumer of these protocols is a fluid spectrum. If you’ve used any of the top DeFi DApps on ethereum, they most likely are organised as DAOs & you’ve most likely received their governance tokens for using them - you can find a list here. The ENS airdrop is probably the most notable recent one.
Social communities: These are organised around any culturally relevant theme - e.g. curating the best moments of history, blue-chip NFTs, memes, movies, literature. They could be as chilled out as a country club where you just drop by to find out what’s trending or produce content of their own. My bet is that in the next decade there will be a few that become cultural power-houses producing million dollar moves and literature & challenging some of the largest media brands today. FWB is currently one of the most notable social communities.
Service communities: Similar to consulting firms of today, these will be focused on providing a range of services from design, writing, development for bounties or project work. Contributors can get paid in project tokens, thus enjoy the benefits of freelance contribution while sharing in the equity upside of projects that do well. Superteam is one such service DAO that is currently focused on the Solana ecosystem.
Investment communities: These are groups that pool together capital to invest in projects, similar to venture or hedge funds. They could be sector focused, like YGG which is focused on play2earn games or have a broader thesis. All community members are basically like LPs and can participate in early-stage investing in ways that weren’t possible (or allowed?) before.
It is worth noting that there will be overlap across these categories, so a community could, for e.g, do both investment and services. But we think this broad categorisation is useful down the road as we try to answer the key question - what value do these different types of communities produce.
Also, you may be thrown off by the sudden flurry of “DAO” thrown at you. Did we just bait and switch a community piece into a DAO shill? Not really - think of DAOs as one manifestation of a community. The simplest way I’ve heard this explained is - “a DAO is a community with a bank account” We may use these words interchangeably going forward. Learn more about DAOs here courtesy Kash Dhanda.
Framework for valuing other collective entities
Before we look at how to value a community let’s examine some parallels both in their methodology and applications. Loosely speaking, the two entities valued the most are countries and companies.
It is worth noting that there is no single universal metric for valuing a country, company or community, it depends on the context of the goals laid out by the entity. . In most cases you end up looking at a variety of metrics over varying time horizons and layer that with the context of reality to arrive at a conclusion.
Countries
Here are a few key metrics for valuing a country,
This is a measure of consumable goods and services produced by a nation over a given time period. When normalised for population, inflation and cost of living it can be used as a metric to compare economic prosperity across nations.
(Source)
One of the most common criticisms of GDP is that, like any average metric, it doesn’t capture the extremes. In this context it means that a small group of wealthy people could, in theory, massively inflate the value of a nation’s GDP - so a lot of people would be below the “average” purchasing power of a country and it would not be representative of the true standard of living or economic prosperity of a country
Enter, Gini coefficient. It measures the dispersion of income and wealth levels of a country, so the lower the value the lower the “wealth gap” in a nation.
The obvious downside of this metric is that it measures outcome inequality without capturing the cause, i.e. if a small group of people work hard and achieve wealth - they would be hurting the gini coefficient of their nation. This is not desirable if you believe in capitalism.
(Source)
Pioneered by Bhutan, this measures collective happiness as stated in response to a survey. It is limiting in that it is really hard to compare across nations or tie to output but captures the mission the Bhutanese government has set out to achieve.
A movement called social progress imperative is attempting to objectively measure how well a nation provides for the well being of its citizens. This could well be more actionable and thus the natural evolution of the happiness index.
There are many more metrics designed to measure specific areas, like scoring high on the ease of doing business metric is a great way to attract foreign capital or environmental performance index is a way to measure progress towards climate change.
Here’s an interesting question - based on the two infographics above, which is the best country to live in? If you were behind a veil of ignorance, would you want to go to one with higher GDP or higher Gini?
Most likely, neither. You’d want a balance. Because,
A very high GDP but a poor Gini means there is progress but it is not distributed sufficiently - most likely due to lack of opportunity or violence.
A perfect Gini but low GDP means everyone is equal but has nothing, there is no progress at all
So, you’d want to find a balance where this is sufficient economic growth but it is also accessible to more people. To be clear - we are not advocating socialism. And neither of the two metrics captures input metrics around opportunities to participate in economic growth.
Reenforcing our original point, there is no single magic metric. There is a combination of metrics when taken in context with reality can help answer specific questions.
Companies
Valuing countries is something all of us will most likely have interacted more closely with. The last 2 years have been filled with unicorn fundraises and massive IPOs after all. This post from HBS captures 6 common ways of valuing a company.
A key difference you’ll observe while looking at most of these metrics is that they are more forward-looking than those for valuing a country. This means that they factor in, one way or another, possible future growth. Whereas metrics to value a country factor in past performance over a given time period.
Two methods we’d like to specifically call out as useful,
Discounted Cashflows: This method basically forecasts future income that the company will generate based on all the awesome things it is going to do & then apply the time value of money to figure out how much that is worth today. The operating word here is forecasts, unlike GDP where you look back and measure performance - here you are projecting forward. This allows for excessive optimism or pessimism depending on the circumstances.
Market capitalisation: If a company is publicly listed then you can simply calculate its market determined value based on the number of shares x share price. The assumption of course is that the market price is accurate, which obviously may not always be the case but is the real world approximation of how much people think a company is worth, i.e. you can literally trade at that price. So if you think it is too high, short it; if you think it is too low - buy more. If you want to rant, umm…. :) .
The reason company valuation metrics are forward-looking is because they are mostly applied to forward-looking decisions, e.g. M&As, retail investing etc. More importantly, until now, a company was the most effective way to pool together resources and work towards a vision - this required a forward-looking approach to valuations. For the most part, we haven’t had nation-building happen this way - yet.
Apart from this consumer tech companies track product metrics like retention, usage and NPS to gauge traction & how happy their customers are with their service. This is relevant because these companies are often creating new markets & it takes a while (decade?) before they generate revenue commensurate to the real opportunity.
Types of Metrics
This brings us to an interesting question, what are the different types of metrics and why should we care? We specifically want to focus on the distinctions between input (leading) & output (lagging) metrics
Input metrics are not sufficient for your business to be financially viable. If defined well, they help you measure if you are on track to meet your output metrics. For e.g. for a company like Facebook, you would care about page views or user count because that feeds into ad revenue, and it gives you a sense of how much ad revenue will be well before it is booked.
Well-defined input metrics are important because output metrics can only be measured retrospectively when it is too late to do anything about them. When investing in a company you are essentially betting that they’ve picked the right input metrics & they can achieve them.
Output metrics are great because they are more objective and therefore more universally applicable. Input metrics are more specific to the context they are being applied in.
Approach to Valuing a community
We think there are two questions to answer while trying to value a community:
What is the possible monetary value of the fully realised vision of the community? If the community did what it says it will, how much will that be worth. This is similar to the DCF method for valuing a company or GDP of a country.
What is the level of censorship resistance or decentralisation? How resilient is it to a few key members leaving or hijacking it? The best communities will be those which have sufficiently empowered their members such that it can withstand both internal and external attacks & setbacks. Here we’ll apply the Nakamoto coefficient to all value generating activities of the community. The Nakamoto coefficient basically breaks down a blockchain into sub-systems & captures the % of actors required to take control of enough to overpower the blockchain (e.g. if all miners use the same mining client owned by one entity then taking over that is enough to hack the blockchain - hence level of decentralisation is low). The nuance here is that we’re not particularly concerned with “51%” - that is relevant for blockchain voting because that is what it takes to “hack” a blockchain - the threshold, each project could define that critical threshold for itself.
We’re going to focus on forward looking metrics in this section because in general Needless to say, the way these three questions manifest for each of the 4 different types of communities will be different. So, let’s take a deeper look at exactly that..
A quick overview of this table,
Project DAOs
The destiny of the community pretty much depends on the success of the project. Because the whole purpose of the community is to operate that project. So the first step is to articulate what the value of the project can be & how much of that accrues to the community.
Complement this with the level of decentralisation, i.e. what would it take for a small group of members to hijack, say, the governance process of the project (this applies more broadly across DAOs too).
Or, if despite there being a “community” only the original core team is really building the product then the community isn’t really empowered enough.
Social DAOs
The value generated can be a function of,
Cost of membership: Intangible value of the community recognised by the market via the token price, which is tied to membership cost.
Value of output generated: Market value of anything produced by the community - music, videos, writing, code, projects etc
Value of curation: If a group is curating, for e.g. blue chip NFTs, something then the net value of their inventory (current - purchased) over time is indicative of the value they created
The level of decentralisation can be measured by,
How many members really consumed or engaged with the community and its output
How many members really contributed to generating this output
If either of these numbers is low then the DAO is subject to attacks from small groups of creators leaving or power consumers holding the DAO hostage.
Service DAOs
The value generated is revenue generated from products and services provided.
The level of decentralisation is measured by,
Is there a small % of members servicing a large % of the revenue?
Is there a small % of members generating a large % of the revenue?
The answer to either of these questions determines how resilient the DAO can be to exit from contributors.
Investment DAOs
The value generated is measured through IRR similar to an investment fund, and needs to be normalised for AUM (size of the fund)
The level of decentralisation is measured by,
Is there a small % of investors providing a large % of the capital
Is there a small % of members sourcing a large % of the deals
Other Metrics
A few other notes,
Member onboarding, growth & NPS is a leading indicator of community quality, we’ll probably do a separate post on this in the future.
For any project with a token, you can of course value it based on the token price * supply, but it is unlikely this will be accurate for early-stage projects.
Conclusion
Valuation is a mix of art and science designed to help with decision making. We don’t think there is a single universal way to value communities right now. Broadly speaking a combination of output generated normalised for % of the community that contributed towards that output is the best approximation for how valuable a community is.
Because of the fact that any project can be forked, the original project has the pressure and incentive to be the best version. As a result of this dynamic, the users have a lot to gain.