Detailed explanation of Web3 product fit and operation suggestions

In our last article discussing Web3 go-to-market strategies, we briefly outlined the concept of “product-market fit”. However, this is a very delicate concept and thus requires a lot of writing. Often discussions revolve around how to achieve product-market fit, without clearly defining the criteria for product-market fit and how to adjust product strategy for this.

As a continuation of the previous discussion, this article will focus on the following questions:

– What is the product-market fit of Web3?

– What are the criteria for judging product-market fit?

– How to measure Web3 product-market fit?

– Who will be responsible for tracking product-market fit?

– What should be the next step after product-market fit?

What is product-market fit?

The term “product-market fit” was first coined by Marc Andreessen to describe a product that fully meets market needs. Initially, Andreessen did not explicitly define the criteria for judging product-market fit. Achieving product-market fit is an objective milestone, he said, and once that milestone is reached, the startup will experience a surge in customer volume and nearly outstrip supply.

But Sean Ellis, author of Hacking Growth, has his own unique definition. Ellis believes that Andreessen sees product-market fit as an end goal rather than an ongoing process, which is not in line with his own actual experience. Ellis said that when he was vice president of marketing at Uporaor and LogMeln, “it was often a matter of iterating and improving a product.” Ellis believes that product-market fit is achieved in iterations and requires specific metrics. Hence, he invented what is now widely known as the “Sean Ellis Test” to assess product-market fit.

How to track product-market fit for Web3?

Tracking product-market fit is not as straightforward in the Web3 industry as it is in the Web2 industry. For one, Web3 is characterized by decentralization and often anonymity. Therefore, it is difficult to use traditional product analysis tools such as Google Analytics, Mixpanel or Amplitude. Also, there is no third-party cookie tracking to provide specific customer insights, although many people think that’s not a bad thing.

Having said that, Web3 founders still need some quantifiable indicators to judge whether the product meets the market demand. These metrics include User Feedback Score, TVL (Total Locked Volume), Number of Transactions, Number of Unique Wallets, NFT Floor Price, and more.

Beware of misleading metrics

Different Web3 products require different metrics. We’ll discuss these metrics in detail later, but first let’s be clear about which metrics can be misleading.

One of the major features of Web3 is that it is easy to quickly form a huge network effect, which is an advantage, but at the same time there are hidden dangers. On the one hand, network effects allow projects to scale rapidly. On the other hand, network effects can obscure the true utility of a project. And usability, which tends to be the traditional metric for product-market fit, can raise some questions.

For example, some startups use subsidies and liquidity incentives to stimulate growth without actually achieving product-market fit. This growth is often achieved through marketing and incentives, rather than based on the real utility value of the product.

Granted, practicality is not a requirement for all Web3 projects. Many NFT projects have no clear utility value, but buyers are often drawn to the quality of the artwork and the project’s brand and community. But even so, it’s hard to tell whether the purchase is due to product-market fit or pure short-term market speculation.

So which metrics are reliable? The answer contains many elements. First of all, it depends on what kind of market the Web3 product covers.

Blue Ocean Market vs Red Ocean Market

To learn how to evaluate product-market fit, you must first determine whether the product covers a “blue ocean market” or a “red ocean market”. This mental model was first mentioned by W. Chan Kim and Renée Mauborgne in their 2004 book Blue Ocean Strategy.

Detailed explanation of Web3 product fit and operation suggestions

This concept is important because it helps us develop our product strategy and decide which metrics to use to assess product-market fit. This is especially valuable for Web3 because there are many untapped markets in the Web3 industry.

Red Sea

A “red ocean” refers to a known and quantifiable market where user needs have been formed and where many products and brands are already competing.

In the Web3 industry, the DeFi and NFT collectibles market can be classified as a “red ocean” because the market demand is already established.

For example, the market share of DeFi projects is relatively easy to quantify. It is only necessary to count the TVL of the project and compare it with the total TVL of all DeFi protocols. At the time of writing, the TVL of all DeFi protocols on Defi Llama is $88.53 billion. Among them, MakerDAO has the highest share at 9.5% and is worth $8.56 billion.

Due to the huge demand in the DeFi market and the emergence of many DeFi protocols that can be used as benchmarks, the market share can be easily calculated.

blue ocean

A “blue ocean” market refers to an unknown market that has not yet been exploited. That is, startups need to create market demand as well as entirely new markets for their products.

The blue ocean market is essentially an unformed market, so it is difficult to give an example of Web3. However, we can refer to some Web2 industries that are just beginning to transition to Web3, such as parametric insurance and real estate.

We can also recall the case of the rise of stablecoins in 2014. BitUSD was the first stablecoin that emerged at that time, but it was difficult to measure the market share of BitUSD at that time, because the stablecoin market was in a blue ocean at that time, and almost no other stablecoin products competed with it. So, we need to look at other metrics, such as user feedback or product engagement.

Customer-centric metrics are critical because blockchain technology is innovative and has historically driven projects to solve problems that haven’t yet arisen. In some cases, there is no very clear reason for building a product or service on the blockchain. That’s because these founders didn’t take the time to consider whether their solution would actually solve the problem. This speaks volumes about how critical user research is for projects looking to tap into the blue ocean market.

The case for product-market fit through constant iteration

DeFi protocol Compound is a typical case, which fully reflects what Sean Ellis calls “product-market fit through iteration”. Founded in 2018, Compound is a decentralized cryptoasset yield platform that runs on Ethereum’s smart contracts.

Compound’s founder, Robert Leshner, mentioned in a conversation with a16z’s Jesse Walden that Compound has iterated over three versions, combining feedback from community users to continuously improve the product.

Leshner said that the iterative process of Compound is as follows:

1. Beta – This is an early unpublished version of the Compound smart contract, open only to a small group of early users who have a personal relationship with the founder. The main purpose of this release is to allow users to test privately and in a closed environment the core functionality of Compound, namely: earning money using crypto assets.

2. Initial release on mainnet – In 2018, Compound released its first release on mainnet, which gave founders the opportunity to get feedback from early users to a greater extent. The interactive experience of smart contracts was less smooth at first and was more aimed at tech-savvy users, but the Compound team has since gotten a lot of feedback on how to improve the product.

Detailed explanation of Web3 product fit and operation suggestions

User interface for earlier versions of Compound

3. The final version released on the mainnet – The Compound team has made significant improvements based on user and developer feedback, such as introducing risk parameters for each asset, and streamlining the codebase to make it easier for developers to develop. This version is considered the “final version,” and it can be said that this version allows Compound to truly achieve product-market fit.

Detailed explanation of Web3 product fit and operation suggestions

Compound’s current user interface

How to measure product-market fit for Web3?

As mentioned above, product-market fit depends on the type of product you are developing. That is, different products need to be tracked with different metrics.

Go-to-market metrics that reflect product-market fit

Several metrics can measure the success of Web3’s go-to-market strategy and thus reflect product-market fit. In “Go-to-Market in Web3: New Mindsets, Tactics, Metrics”, a16z’s Maggie Hsu proposes the following metrics for key Web3 verticals:

Detailed explanation of Web3 product fit and operation suggestions

However, these metrics must be benchmarked to make sense. In the Red Sea market, benchmarking is relatively easy to find: you can benchmark with competitors already in the market or with the entire market.

If you are in the blue ocean market, then you can only compare with your previous data. In other words, you measure your own growth rate.

But there is a better measure, and that is asking users for their opinions.

User Metrics

A common measure is the “Sean Ellis Test” (note: Sean Ellis was Dropbox’s first head of marketing and the inventor of the test). This metric is ideal for early-stage startups, where users need to answer simple multiple-choice questions.

How would you feel if you could no longer use [the product]?

Very disappointed

a little disappointed

No feeling (this product doesn’t work for me)

Unknown – I no longer use [product]

Ellis said that once more than 40% of users choose to be “very disappointed”, it means that the product may be a market fit. Ellis compared the findings of hundreds of startups he has worked with, and ultimately set the threshold at 40%. He found that companies with test results in the 40 percentile were generally able to continue to scale, while those well below 40 percent were struggling.

Of course, this metric is not suitable for projects with no clear utility, such as NFT art collections. But that doesn’t mean user research can’t provide any insight. For example, in early 2022, a group of Berlin-based art market experts began assessing the motivations of NFT art buyers. Finally they released a report called ART+TECH Report for NFT collections. The report details the buying motivations of NFT art buyers. Of course, the original purpose of this report was to assess the current state of the overall market. But we can also use the same research method to assess the purchasing motivation of a certain NFT community.

Community and Social Metrics

It’s worth mentioning that community and social metrics are often also present in Hsu’s go-to-market metrics. This is because the community tends to make or break most Web3 startups. Especially for NFT and game projects, community participation can reflect the product-market fit at an early stage.

When choosing specific metrics, start with the “Exhaustive Checklist of Community Success Metrics” published by community tools provider Commonroom. The list includes metrics including the percentage of active contributors to the community and the percentage of posts and messages with at least one reply.

Community-focused Web3 projects should also track discussions outside of native community platforms, such as those on other social media platforms. Here, it’s important to track metrics that measure social media engagement, such as reach, impressions, replies, and brand mentions.

For many Web3 startups, these are not core metrics that determine success or failure, but they are a measure of how far the project is from achieving product-market fit.

Who will be responsible for tracking Web3’s product-market fit?

This issue is rarely discussed because the Web3 industry is still in its infancy and job responsibilities are not standardized. However, this is a very important question because in such a fast-moving industry, building a sense of responsibility is crucial.

For very early stage startups, it’s often “the founders take care of everything”. But in traditional Web2 startups, product managers are responsible for tracking product metrics. Product managers often have the time and ability to conduct proper research and produce professional reports.

In the Web3 world, however, product managers are not a norm. This is because many Web3 teams do not understand what the role of a product manager is. In fact, many Web3 teams don’t need a product manager to be successful.

Jason Shah, head of product at Alchemy, pointed out that in the process of building a DeFi protocol or airdropping NFT, the team most needs to have a developer, a community manager, a protocol designer (for DeFi) or an artist (for NFT). He also said that the Web3 team will only hire a product manager when there is a need to focus on user experience or when the complexity of the task exceeds the team’s current capabilities (such as marketing, growth, business development, community management, and product analysis, etc.).

Generally speaking, it is not necessary to have a dedicated product manager to track product-market fit, but the Web3 team should really understand the role of the product manager better and assign a product manager to the team.

What should the Web3 team do once they have achieved product-market fit?

Product-market fit reflects whether your startup is on the right track, but it doesn’t mean you have to stick to the same strategy all the time. Instead, achieving product-market fit means you should switch runways and focus on other goals.

We continue to use Compound as an example, and the Compound team changed their strategy after achieving product-market fit. They took the following two approaches:

– Pay more attention to the development of the developer community

– Greater emphasis on decentralization of ownership

Increase investment in community building

Although the Compound team has also released native dApps, the Compound protocol has always been their core product. Therefore, Compound requires developers to develop on the protocol and expand the scope of application. Once the team determined that their product met the market demand, they began to invest more time in building the developer community. According to Leshner, “We spend a lot of time doing things that most people find boring,” specifically:

– Improve and expand technical documentation

– Write use cases and full tutorials

– Respond to developer community questions and messages on Discord and Github

– Upgrade the website to showcase products developed by other developers based on the protocol

Preparing for Decentralized Ownership

Decentralization is not a good idea, Leshner argues, if you’re still iterating on an MVP. If you want to design a mechanism with the input of a committee, you can’t iterate quickly. The initial goal should be “maximum efficiency”. Therefore, the Compound team was initially solely responsible for making decisions to move development quickly.

However, once product-market fit is achieved, the perspective becomes completely different. They started to implement community governance through iteration. This includes several key milestones:

Issue Governance Tokens – In April 2020, Compound issued COMP tokens to users based on their on-chain activity. Users can issue governance proposals and vote on proposals by holding tokens. The content of the proposal includes user incentive mechanism, platform assets and Compound’s governance mechanism.

Hand over admin keys – Many projects use admin keys to authorize breaking changes to the codebase and upgrade network protocols. Usually this key is kept by a centralized team, which means that outside developers cannot perform breaking changes. Compound also adopted a centralized governance mechanism before, but in June 2020, the team handed over the management keys to the community for safekeeping. This means that the community can implement voted changes.

Of course, not all Web3 projects have to be decentralized. For example, Web3 teams developing trading platforms, NFT marketplaces, and infrastructure platforms tend to prefer centralized governance. For such teams, once product-market fit has been achieved, it is time to start looking for new Web3 markets.

Finding New Web3 Markets

For most dApps and technology providers, each blockchain is a unique marketplace. As such, these products typically have to achieve product-market fit on one chain before scaling to a new chain. For example, Chainlink initially only supported Ethereum, but has since been upgraded to integrate into EVM-compatible chains such as Avalanche and Polygon, as well as non-EVM-compatible chains such as Solana. Once you have achieved product-market fit on one chain, you need to expand to new blockchains.

New markets can also refer to verticals such as GameFi and NFTs. For example, in February 2022, blockchain infrastructure provider Alchemy released an NFT API to simplify the development process of NFT projects. Alchemy’s previous core product, Supernode, has achieved product-market fit and thus has the ability to expand the product suite into the emerging NFT market. Allocating resources to new markets doesn’t make sense if Supernode doesn’t achieve product-market fit first.

Product-market fit is an iterative process, not once and for all

Many people assume that once product-market fit is achieved, they can sit back and relax. But in reality, product-market fit is fleeting. Therefore, product-market fit needs to be constantly re-evaluated. Especially when the external environment changes, readjustment is particularly necessary. For example, market sentiment has changed, or market competition has become saturated. Additionally, product-market fit must also be reassessed when new goals are set internally, such as entering a new market or integrating into a new technology ecosystem.

In either case, you need to assess whether the product still meets user needs or provides sufficient value to users. Products that are favored by users at the beginning may not meet market demand later, or the same product may not achieve the same effect after entering a new market.

Therefore, it is necessary to continuously track metrics that reflect product-market fit, especially assessing market and community attitudes toward the product.

Posted by:CoinYuppie,Reprinted with attribution to:
Coinyuppie is an open information publishing platform, all information provided is not related to the views and positions of coinyuppie, and does not constitute any investment and financial advice. Users are expected to carefully screen and prevent risks.

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