Original title: Why Blockchain Valuation Models Are Still Up for Debate
Original author: William Mougayar
Original source: https://www.coindesk.com/
Translated by: Daisy, Mars Finance.
How to assess the value of a decentralized network? William Mougayar suggests: every new era of the internet requires new ways of thinking about value measurement.
Current blockchain network valuations evoke memories of the early internet era—traditional financial models then also struggled to adapt to new technologies.
Despite its increasing application, blockchain networks still lack standardized valuation methods, and existing models are either incomplete or flawed.
An emerging valuation framework focuses on 'velocity of circulation and capital flow,' measuring value by tracking the movement of money and assets in the blockchain economy (similar to economic cycles).
The current valuation of blockchain networks evokes a sense of déjà vu for those who experienced the early internet era. In the 1990s, analysts, investors, and entrepreneurs strived to apply familiar financial models to a completely unfamiliar technology. At that time, companies with just a website and a business plan could achieve valuations in the hundreds of millions or even billions of dollars based on intangible metrics like 'user traffic.'
The outcome is not pleasant. However, looking back, those chaotic early years left valuable experiences: technological evolution always outpaces financial regulations, and valuation models must ultimately adapt to the forms of innovation.
Today, we face a similar predicament in the blockchain space. Despite increasing application, maturing infrastructure, and undeniable cultural and economic momentum, there is still a lack of widely accepted standardized blockchain network valuation methods. The existing few models, while directional, still have flaws or are not fully developed.
To explore future directions, it is necessary to first review the past.
The first wave of internet valuation: attention economy, not actual profits (mid-1990s-2000).
In the late 1990s, the internet was still a wild frontier. Investors did not know what the 'success' of a digital company should look like, so they relied on all measurable metrics: page views, banner ad impressions, unique visitors, or monthly active users (MAU). These crude metrics for measuring user attention became the de facto standard of value. The logic was simple: if millions of people visit your website, monetization will naturally follow.
Valuations soared as a result. Startups like Pets.com (see image), Webvan, and eToys raised hundreds of millions in funding based on promises of becoming industry leaders. But revenue was only an afterthought, and profitability became a joke. When the internet bubble burst in 2000, people finally understood: user attention without monetization potential is ultimately a fragile foundation for corporate value.
The adjustment period after the bubble burst: revenue and profit margins became key (2001-2005).
After the first wave of the internet bubble burst, investors' mindsets underwent a massive shift. The market demanded tangible proof, not just beautiful visions. Starting in 2001, companies needed to demonstrate meaningful revenue, gross margins, and gradually achieve profitability.
During this period, unsustainable business models were ruthlessly eliminated. Only companies with real products, real customers, and reasonable financial conditions survived. For example, Amazon shifted investor focus from abstract future potential to actual operational performance. Its sustained total revenue growth and continuously improving profit margin management helped rebuild market confidence.
eBay became a model of a clear business model: a scalable, transaction-based profitable enterprise. These survivors taught investors to assess internet companies in a manner closer to traditional businesses—income statements became crucial.
The rise of SaaS and unit economics (2005-2015).
By the mid-2000s, a new model—Software as a Service (SaaS)—emerged, along with a brand new valuation language. Unlike traditional reliance on unpredictable advertising revenue or retail profit margins, SaaS businesses provided predictable recurring revenue streams, which was a revolutionary change for both entrepreneurs and investors.
This era spawned the following key metrics:
Annual Recurring Revenue (ARR) and Monthly Recurring Revenue (MRR).
Customer Acquisition Cost (CAC) and Customer Lifetime Value (LTV).
Customer churn rate, net retention rate, and the 40 rule (growth rate + profit margin ≥ 40%).
These unit economics indicators enable investors to assess a company's operational health and scalability more accurately. The market has begun to value growth efficiency and recurring revenue, rewarding companies with sustainable, high-margin models and strong customer stickiness.
SaaS companies can temporarily operate at a loss, provided that their key metrics tell a clear story: acquiring customers at a low cost, retaining customers in the long term, and gradually increasing customer wallet share. This approach has become the core framework of modern technology valuation and remains a mainstream perspective today.
Platform era: Network effects and ecosystem value (2015 to present).
By the 2010s, companies like Facebook, Google, Uber, and Airbnb redefined online value. They were not just companies but platforms. Their power lies in aggregation capability, data control, and the ever-strengthening network effects as they scale.
Valuation models have also evolved. Analysts have begun to measure:
Network effects (the value increase brought by each additional user).
Ecosystem depth (third-party developer activity, market platforms, plugin ecosystems).
User engagement and data lock-in effects.
Companies are no longer favored solely for their revenue but for building infrastructure that others rely on. This marks a qualitative leap—valuation has begun to focus on strategic position rather than just cash flow.
Contemporary internet giants: profitability, efficiency, and AI moats.
In the 2020s, technology valuation has matured. Public market investors now focus on operational efficiency, profitability, and free cash flow. 'Growth at all costs' has become a thing of the past, and the '40 rule' is now the new standard (i.e., the sum of company growth rate and free cash flow rate should be ≥ 40%).
Enterprise valuation is based on the characteristics of specific sectors: SaaS has its own metrics, e-commerce has another set, and fintech is yet different. Meanwhile, intangible assets such as proprietary AI models, data ownership, and infrastructure moats are increasingly becoming core factors in the pricing of tech giants.
In short, the valuation system has become both more specialized and more rational, fully aligning with the true value drivers of each digital domain.
What this means for blockchain.
Despite the sophistication of internet valuation, blockchain is still trapped in a valuation dilemma. While some attempt to apply traditional metrics—such as discounted cash flow (DCF), validator income, or protocol fees—these often miss the point. It's like trying to assess Amazon's value in 1998 based on shipping costs.
Blockchain is public infrastructure, not private enterprise. Many chains rely on subsidies or token issuance to inflate revenues, which does not reflect real demand. More importantly, as decentralized systems, their original design intention is not to extract profits but to achieve permissionless collaboration and trustless economic activities.
Other emerging valuation methods have their limitations:
The MSOV (Monetary Stored Value) model values through the amount of tokens staked/deposited in DeFi—it's of reference value but too static.
On-chain GDP attempts to measure cross-application/cross-chain economic output—it's theoretically clever but difficult to standardize and easily distorted.
None of these models has become a dominant, comprehensive, and widely recognized solution. Moreover, the characteristics of blockchain as a data layer have yet to be incorporated into any valuation framework.
New perspective: Measuring velocity of circulation and capital flow.
To make breakthroughs, we need valuation models that reflect the essence of blockchain. To that end, I propose a framework based on 'velocity of circulation and capital flow' to track the movement of funds and assets in the blockchain economy. It focuses on usage patterns, transaction cycles, and capital reuse, which is closer to the dynamic nature of economic cycles rather than static metrics—this resonates with the mature methodologies of the internet platform era (the last frontier of digital economy valuation).
This model examines:
Stablecoin turnover and velocity of circulation.
DeFi lending/trading/collateral activities.
NFT trading dynamics (purchase volume, royalty flows).
Cross-layer bidirectional asset flow.
Real-world asset tokenization scale (purchase volume, equity yield, appreciation).
Cross-application paid-in capital formation and reuse rate.
Asset collateralization, settlement, cross-chain, and other exchange medium fees.
This method provides a native and robust blockchain value measurement system. It focuses not only on the stock within the system but also tracks the flow—liquidity is the clearest signal of trust, utility, and relevance, just as the velocity of money is a recognized indicator of economic vitality.
Conclusion: Building the models needed for the future.
The development of the internet teaches us: every technological revolution requires a new financial perspective. Early models were inevitably crude, but the gravest error was to cling to outdated frameworks.
Blockchain is still searching for its own valuation narrative.
Future valuation frameworks will be built through innovation, not inherited. Just as early internet investors had to invent new tools to understand the new phenomena before them, the blockchain world now faces the same challenge.
If successful, we can not only assess blockchain value more accurately but also unlock its economic and social potential in depth.
