Market Research / Fees & Revenue

What a chain actually earns.

Fees paid and revenue kept, per chain and per protocol, with the take rate between them. Activity and value capture are different things, and only one of them is a business.

Fees and revenue are not the same number

Fees are what users paid. Revenue is what was kept. A network can process enormous fee volume and retain almost none of it, and the take rate between the two is the figure that says which case you are looking at.

  • Both figures, always

    Paid by users and kept by protocols

  • Take rate

    The ratio that separates volume from value

  • Reconciled

    The totals are the sum of their own rows

Split by the protocols earning it

A chain whose fees come from one protocol is a different asset from one whose fees come from twenty. Break any network down by contributor and see how concentrated its economics actually are.

  • By protocol

    Who generates the fees, and who keeps them

  • Concentration

    One protocol or a broad base

  • Per-protocol take rate

    A DEX and a lending market keep very different shares

Compare networks on economics

TVL says how much sits on a chain. Fees say how much it is used, and revenue says how much that use is worth. Rank networks on all three rather than on the one that flatters them.

  • Chain against chain

    On fees, revenue, and take rate

  • Beside TVL and volume

    The full picture, not one metric

  • Any window

    Daily through multi-year history

Economics across every chain and protocol

Reported separately, always
Fees + revenue
The ratio between them
Take rate
Who earns it, chain by chain
Per protocol

Fees and revenue reported as two separate figures with the take rate between them, per network and per protocol, on a consistent basis across all of them.

Every tool takes a fee earner as an input.

The research tools are not a separate product. Point any of them at a fee earner and it works the way it does everywhere else, on the same data this page is built from.

Compare

Any fee earner against any other, on shared axes

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Correlation

What a fee earner actually moves with, measured

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Relationships

Every record a fee earner connects to, in one graph

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Indicators

Sentiment, dominance, and volatility, read together

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