Lifetime Value in Crypto: Detailed Revenue Models for Blockchain, DEXs, Lending, Stablecoins, and Yield Aggregators
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Lifetime Value in Crypto: Detailed Revenue Models for Blockchain, DEXs, Lending, Stablecoins, and Yield Aggregators
Each cryptographic primitive provides business functionalities very similar to those seen in the real world, but with slightly different mechanisms due to the nature of their environment.
Navigating Web3 tides with focused insightsWritten by KERMAN KOHLI, Founder of ARCx
Compiled by TechFlow
Around this time last year, I began writing about crypto businesses and how their unit economics were broken in a way that made most industries look like a joke. It wasn't until FTX collapsed that people truly started paying attention.
Since then, I've moved beyond just thinking about these issues—I've been building the necessary components to solve them. But before that, I’ll share some additional conceptual frameworks I’ve developed while working through these problems.
Lifetime Value (LTV)
One of the most important metrics for any business. It represents the total fee value a customer generates for a business over their lifetime. The key here is that every business earns fees differently, so you need to deeply understand its mechanics to grasp how value is created and captured. Below is a rough conceptual framework for thinking through different categories.
These are all per-user based, so of course, more users mean more revenue—all else being equal—but the critical factor here is the quality of those users.
Chains
Although networks aren't technically enterprises in the purest sense, knowing how much fee revenue each user brings on average can tell you a lot about a chain’s health. This poses a challenge for high-throughput L1s and L2s, as they generate significantly lower fees compared to Ethereum. They must either demonstrate much higher activity levels or add supplementary services that capture most of the revenue (e.g., movie theaters, where ticket prices are low but real profits come from concessions).
For chains/general-purpose computing platforms, our formula is: Fees Paid = Transaction Complexity (Gas) × Computation Price (Gas Price).
This means there are two dimensions that computing platforms (chains and L1s) should consider:
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How do we increase transaction complexity? DeFi is one example; blockchain gaming is another—as long as gameplay occurs on-chain.
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How can we sustainably increase the average price of computation (gas price)? Ethereum sees massive spikes in transaction fees when gas prices become extremely volatile. Beyond that, sustained activity is another dimension for increasing fees paid per user.
This isn’t an exhaustive framework, but rather the levers worth studying.
DEXs
Decentralized exchanges (DEXs) have a simpler framework for understanding customer lifetime value because they really only need to focus on two factors: Fees Paid = Trading Volume × Trading Fee Rate (%).
The two dimensions DEXs need to optimize are:
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How do we increase the average trading volume occurring on my DEX? This can be achieved by focusing on specific verticals—such as stablecoins (Curve's strategy)—or long-tail speculative tokens (Uniswap). Though both are increasingly competing for each other's market share.
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How do we raise the average trading fee we can charge per trade? This is where NFT markets have suffered heavily, engaging in a “race to the bottom” where trading fees are not only 0%, but unit economics become negative due to paid incentives.
Lending
All lending protocols share the same unit economics—their challenge lies in how they address them. From a fundamental perspective, their equation is: Fees Paid = Lender Yield (%) × Protocol Fee Share (%).
For both dimensions, you need massive scale to achieve meaningful operations:
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How do we increase the yield lenders can earn? This may be the least optimizable variable, as in a market where underlying assets can 10x within a year, borrowers tend to be relatively price-insensitive (though stablecoins are an exception). However, few borrowers are willing to pay above double-digit rates, meaning best-case scenarios hover around 10% (already considered high).
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How do we capture a portion of the yield earned by lenders? This is where it gets tricky, because yields are already razor-thin, and taking a cut makes it even harder. For example, Aave takes 10% of lender yield. If lenders earn 5% on stablecoin deposits, Aave captures just 50 basis points as pure profit—and thus the value of that customer.
Stablecoins
Stablecoins are everyone’s favorite business because they effectively function as printing presses. Typically, however, you must spend heavily on liquidity incentives to attract customers and drive adoption. To see why these businesses are so profitable, examine their fee structure: Fees Paid = Interest Rate Charged × Value of Borrowed Assets.
That’s it. You set an interest rate and encourage borrowers to draw down as much capital as possible. When evaluating your two main levers, you only need to consider:
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How do I charge the highest possible rate while remaining competitive? This depends largely on what competitors (money markets) are doing and what I’m paying for liquidity.
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How do I get borrowers to draw down as much capital as possible? This is challenging because the quality of collateral determines platform risk and your ability to remain solvent.
Any money you earn is your profit. The only catch is that your costs go toward ensuring your stablecoin remains pegged or has built-in strong demand support.
Yield Aggregators
This category covers any service that claims, “Give me your money, and I’ll maximize your returns.” These businesses perform exceptionally well at launch, but face major challenges around defensibility and negative network effects. Their fee structure resembles that of lending, but their core business mechanism differs.
Fees Paid = Deposit Size × Depositor Yield × Performance Fee (%).
I include deposit size here because the more funds a yield aggregator manages, the less return it generates for other users. In effect, it suffers from negative network effects!
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As a yield aggregator, you naturally want large inflows to increase profits and capture performance fees. The problem is, too much capital makes it difficult to generate growing returns for all depositors, which erodes your performance fee.
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Increasing depositor yield faces the biggest hurdle: any on-chain strategy you deploy can be copied—quickly and exactly—by anyone else. You’re squeezed from both sides.
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Performance fees are also hard to optimize, because any percentage you charge, depositors could technically bypass by going directly to the source. It’s akin to limited partners investing directly into the startups discovered by their venture fund.
Conclusion
As you can see, each crypto primitive mirrors traditional real-world businesses, but with slightly different mechanics due to the unique nature of their environment. Moreover, the relationship between costs and profits involves a delicate balance, incorporating an element of "incentive elasticity."
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@kermankohli
