From Transaction Fees to Stablecoins: The Revenue Drivers and Moats Behind Web3 Business Models

Author: Eric SJ

Web3 is transitioning from the "user growth era" to the "business model validation era." In my previous article, I discussed five validated Web3 business models:

• Transaction Fees

• Stablecoin Reserve Earnings

• Funding Spread

• Block Space Sales

• Protocol-Level Service Fees

These models answer the question: How do they make money? However, there are two more important questions:

• Some revenues may seem "sexy," but may not be sustainable in the long term.

• Some revenues may appear slow, but are actually more commercially valuable.

A formula explains: Revenue = User Demand × Usage Scale × Pricing Power × Market Environment.

For example, if a protocol earns $100 million in a year, it may represent a real business loop or just a result of hitting a market cycle, but the question is the sustainability of that cycle (e.g., the past Pump).

The money earned during a casino peak season and the money earned from infrastructure rentals both appear as revenue, but future expectations differ.

This article will dissect these five validated Web3 business models from the perspectives of revenue drivers and long-term moats.

1. Transaction Fee Revenue: Focus on Trading Volume and User Activity

Transaction fees are the easiest type of business model to understand in Web3. The logic is simple: Transaction Revenue = Trading Volume × Fee Rate.

Thus, the factors affecting revenue are easy to break down.

Trading volume is positively correlated with market activity, which is the most obvious variable in the transaction fee model.

In a bull market, asset prices rise, user trading willingness increases, and leverage demand grows, so trading volume naturally increases, leading to rapid revenue growth for CEXs, DEXs, and Perp DEXs.

However, in a bear market, user trading and leverage demand both decline, and fee revenue will also significantly drop.

• This is why transaction fee model revenues are the most cyclical.

At the same time, an increase in trading volume does not necessarily mean that the business model and loop are strengthening; more importantly, whether your trading volume comes from real user growth or just short-term incentives attracting traffic.

Taking Hyperliquid @HyperliquidX as an example, its future revenue growth depends not only on the overall perpetual contract market size but also on its ability to continue attracting on-chain traders and market makers, which is the foundation of liquidity.

Because what trading platforms are truly competing for is not the product, but the liquidity network.

Next is the fee rate.

Trading platforms cannot infinitely raise fee rates because fees themselves are a competitive tool. As competition intensifies, lowering fees, refunding fees, and increasing user incentives will all affect final revenue.

Therefore, for the transaction fee model to grow in the long term, it needs to satisfy: market expansion, market share increase, and stable rates.

Early Dexs and current Perp DEXs attract funds into protocols for trading through 0-fee rates to increase their market share, but this raises a thought-provoking question: Once rates return to normal levels, will funds still be willing to stay in this protocol?

The OI indicator is a good parameter. The chart below shows the OI data I collected last month, which reflects, to some extent, whether funds are willing to keep their risk exposure in one place.

2. Stablecoin Revenue: Core Focus on Scale and Interest Rate Environment

The stablecoin reserve earnings model essentially is: Revenue = Stablecoin Scale × Reserve Asset Yield, so the influencing factors are these two.

First, scale is the most critical variable. The revenue of USDT and USDC comes from how many dollar assets are deposited on-chain.

If the supply of stablecoins increases and the reserve scale expands, revenue naturally increases; conversely, if the scale decreases, revenue will also be affected.

• The chart below shows Tether's scale in the first quarter of 2026, achieving approximately $1.04 billion in net profit at such a scale.

Therefore, the core of stablecoin competition is not just issuing more tokens, but who can become the dollar infrastructure on-chain. In other words, under the current compliance context, which stablecoin can become the issuance entry point determines its future moat thickness.

The second factor is the interest rate environment.

Stablecoin issuers typically allocate: U.S. Treasury bonds, money market funds, and cash equivalents. Therefore, its revenue is highly dependent on risk-free interest rates. In a high-interest rate environment, reserve earnings increase; in a low-interest rate environment, earnings decrease.

So even if the scale of stablecoins continues to grow, the issuer's revenue may still be affected by the interest rate cycle. However, this model has a strong point: it does not experience significant volatility, and growth is predictable (the downside is the lack of imaginative space), and once funds enter, they are not easily moved in the short term.

Moreover, large funds tend to gravitate towards "brands" that have been validated over time, meaning the longer something exists, the thicker its moat becomes. This is also why new stablecoins find it increasingly difficult to capture market share.

Additionally, this market is slowly opening new channels for growth. Once a project is established as a traditional entry point onto the chain, it becomes a stable cash cow.

3. Funding Spread Revenue: Focus on Funding Demand and Risk Management

The funding spread model I previously illustrated with two examples: Aave lending and Ethena funding rate arbitrage.

They essentially make money by utilizing the supply-demand difference in funds.

Taking Aave as an example, revenue comes from borrowing demand. In an upward cycle, users' risk appetite increases, using borrowing to further amplify leverage, which is the source of demand, driving up fund utilization rates and thus driving protocol revenue growth. The logic is the same as the transaction fee cycle, both stemming from risk appetite.

4. Block Space Revenue: Mainly Focus on On-Chain Activity

The block space sale model is also clear: Revenue = Block Demand × Gas Unit Price.

Although the structure is simple, it is worth discussing because this model actually has certain revenue expectation issues (in my opinion).

Theoretically, the more on-chain users, transactions, and applications, the higher the demand for block space, and revenue naturally increases because a highway that no one uses has no toll value.

However, the Gas unit price is a hard constraint; Gas has been on a downward trend in the industry, which is actually affecting revenue.

Additionally, competition between different chains, such as Ethereum, Solana, L2, and DA layers, has formed competitive relationships, making Gas fees even more competitive. Many chains occasionally launch 0 Gas activities to attract liquidity and increase on-chain activity.

This involves the game between demand growth and unit price decline.

Taking Ethereum as an example, two cycles ago, the logic was simple: limited block space → user competition for transaction ordering → demand increases → Gas rises → network revenue increases;

However, with the emergence of more chains and improved transaction execution efficiency, the market's available alternatives have increased, causing Gas to be driven down. This creates a commercial contradiction:

• On one hand: more users and applications need block space;

• On the other hand: technological advancements continually reduce block space costs.

For users, this is good news because transactions are becoming cheaper. But for chains as "block space suppliers": unit revenue declines.

This is somewhat similar to the development of internet infrastructure; early bandwidth was scarce and expensive; later, as bandwidth expanded, prices decreased, and ultimately, market value did not solely belong to the party providing the underlying resources but concentrated more on those with users, ecosystems, and platform capabilities.

Therefore, the core issue of the future block space business model is not just: "Is there demand?"

But rather: Can demand growth offset unit price declines?

5. Protocol-Level Service Fees: Focus on Usage Scale and Position

Infrastructure service fees resemble the SaaS version of Web3. For example, oracles are a typical case.

Its revenue mainly comes from B-end: continuous use by project parties.

The more projects using the protocol, the larger the revenue scale, and the migration costs will also be high; once integrated, the replacement cost is significant.

However, there is a prerequisite: it must become an industry standard. For instance, Chainlink currently occupies more than half of the oracle market, making it difficult for other projects to compete in this space, resulting in a thick moat. Even if cheaper products emerge, it is hard to easily shake the existing B-end interfaces.

This type of infrastructure does not sell one-time products; it sells: ecological positioning. Therefore, long-term value depends on whether more and more projects are built around it.

Conclusion

If we put these five business models together:

1. Transaction fees and funding spreads both have strong cyclicality, driven by the risk appetite of on-chain funds.

2. Stablecoin reserve earnings and protocol-level service fees both have thick moats, rooted in the high migration costs on the supply side.

3. The block space sale model faces the issue of continuously decreasing unit prices, requiring consideration of the game between scale and unit price. It is unreasonable to think about valuation purely based on revenue (at least for now).

This content is provided for general informational purposes only and doesn't constitute financial, investment, legal, or tax advice. Any events, rewards, online promotions, or related information mentioned herein should not be considered a recommendation, solicitation, or invitation to purchase, sell, trade, or otherwise deal in any crypto assets. Crypto assets are highly volatile and may result in loss. The availability of WEEX services, products, and related events may vary by region. You are responsible for ensuring that your participation is in accordance with applicable local laws and regulations.