TL;DR
Tokenization and open source nature of Web3 projects make for a new investing framework. I outline the absolute minimum like Team, Tokenomics and Ecosystem, that I look for in projects. Then, I provide other factors that go deeper by looking at Technology, Market Information, Narratives, Field Research, and UX. These are not all applicable depending on the stage of a project but understanding these can help you collaborate with teams to help with their success!
Note: I will publish investment reports for projects based on this framework soon.
Lean Machine
The Team
The Team is at the core of all ventures. This could be their skills, similar past projects, vision, knowledge of the industry, etc. But most importantly, and especially in this web3, their hearts - are they building a long term product for the ecosystem or a quick cash grab? Teams that are crypto natives enjoy contributing and working in the ecosystem regardless of the money they make. I try to get to know the team on a personal level through communication instead of spreadsheets.
Tokenomics
Tokenomics can make or break a project if it’s not designed for long term growth. The main question is how are the tokens, and therefore the project’s ownership going to be distributed to holders. I find the token unlock schedule and it’s holders from blogs, white papers, and/or smart contracts to determine value growth in the first 2 years. Will seeing if selling pressure is going to be great than the traded token supply (liquidity)? If there is a >50% allocation to institutions or >25% allocation to one wallet I look at their reputation to see if they are valuable partners who aim to hold and support the token long term. Finally, the token itself should have a logical use-case for the users of the protocol and it if value accrues to holders and supporters. More detail in the Rabbit hole section!
Ecosystem and community
Web3 is naturally decentralised so the communities are transparent and span across social media channels such as Twitter, Discord, Github, and Telegram. I look to see if these communities are organic or fuelled by paid shills on YouTube, TikTok, or Discord Server invitooors. Can you see reputable crypto natives talking about it on crypto twitter and what are the saying? If there is a DAO I look at the governance forums (proposals and votes) to understand the activity and quality of the operation.
These should at least stop you from getting rugged when you ape into a token. But if you want to go deeper and spend a few days then the rabbit hole framework is for you.
Rabbit hole
Architecture and technology
I will share some high level thoughts on this topic but will write a separate post that goes into more depth soon! But this is essentially understanding the technical papers (white and/or yellow) to think about the product design. Is it even feasible given the current state of the ecosystem. For example, a lot of the utility token ICOs in 2017-2018 were simply not feasible since they couldn’t integrate with real world data channels. Other feasibility factors to considers are available ERC standards that can be used, available Layer 1 functionality (consensus, security, data availability) and ability to transition or operate on L2s. More on this in Token Design Overview!
Market information and more Tokenomics
I think of allocations as multiple snapshots including private sales rounds, token listing, 6-12 months after listing, 2-3yrs after listing while considering mechanisms (staking and reward with given token rights, unlocks, strategic sales) that change those snapshot.
Private sales are similar to previous frameworks of venture funding with token price and % allocation determining cap tables. Then going deeper into the holder behaviour I want to see the OTC market activity which can show how much the tokens have changed hands. Some investors lock in a 10x from their investment at a $20m valuations, by selling to new investors in OTC markets who are more likely to hold after listing. Although, this can be a noisy dataset by itself as OTC trades are required for utility tokens e.g. if you have to stake to start a node. But, on-chain analytics helps find the holding wallets and the individuals it is associated with, to better understand the OTC market.
Upon token listing there two main factors that come into play; Market Cap (MC) based on open market price discovery and Fully Diluted Value (FDV) which is token price x supply - current or total supply. Short hand model is considering MC as demand and FDV as supply, where product demand has to keep up with supply to maintain a healthy growth in token value. If early investors are looking to sell their unlocks (from FDV) into an illiquid market (small and not growing MC) then token value may not increase even if product usage is increasing.
An additional layer is the staking and rewards based on token permissions. This is a case by case consideration for each token, but generally the tokens that can be staked to earn unlocks through rewards dilute other holders, change distributions and add sell pressure. For example the LooksRare token at a glance had 80% distribution to the community, which is a great signal, but due to the staking permissions, rewards, unlocks, the team had close to 70% of liquid supply which they sold, reducing the token value. There can be positives and negative effects from this and doesn’t fully determine long term growth, but it is important to understand it when investing in projects.
Narratives
The financial market accessibility and high speed of information flow in web3 makes for a very narrative driven industry. All these narratives tend to be exciting because they are a new experiments for decentralised technologies. But the lifecycle happens very fast as they are hyped for a short period of time and may die soon after. We saw this with a lot of ICOs and ETH killers in 2017, even DeFi protocols in 2020-2021 where genuine innovative occurred but the limitation and weak fundamentals (from previous sections) became obvious after the experiment was done. Remembering the history of narratives and their evolution can help understand the projects approach to a problem, naturally leading to the reason they succeeded or failed, which teams can learn from - I have written a 2021 summary and 2022 outlook which will be an ongoing series at metacollab.
Field research
Web3 projects are open and transparent by design, taking after the decentralised principles of Bitcoin. Access to team members, their actions (through wallets), and their opinions are open for the public to see. Thus it’s possible to gather insights from core members to inform your view of a project. This transparency also leads to others forming an opinion which they share online. I look for core and contributor proposals on forums or discord, and read the opinions of other investors/trader on medium/ substack/ twitter/ blogs to get a big picture view.
Using the product
Finally, the most informative research can simply be using the product. This may also lead to finding bugs that you can report to the team. Talking to the team and getting to know them on a person level is also an important aspect of investing and contributing.
Example questions
Team:
Do their hard skills match the technicals of the project?
Have they done a similar projects in the past?
Is the vision of the product clear or is it just a copy pasta of another one?
Do they know the ‘startup idea maze’ of crypto? If so what are they doing differently?
Are they in it for a pump and dump?
Tokenomics:
Distribution at sale, token listing, 6 month after list, 1-2 years after list?
Token holders and their backgrounds?
Dilution and redistribution mechanism like staking and rewarding?
Permission right of token holders (voting, staking, etc)?
Is the token inline with the technology feasibility?
Ecosystem:
Developer and DAO activities?
Who are the supporters of the ecosystem?
Growth of the ecosystem participants overtime?
What are the narrative driving the ecosystem?