Liquidity providers deposit funds into Notional and receive trading fees from borrowers & lenders (supply-side fees).

Notional is a non-custodial fixed-rate, fixed-term lending protocol built on Ethereum. Notional was founded by Jeff Wu & Teddy Woodward and launched in 2020.

NOTE holders own and govern the protocol. They currently take a cut of the total trading fees paid by borrowers & lenders and all of the COMP incentives from funds deposited to Compound (revenue). Notional’s investors include Coinbase Ventures, Nascent Ventures, 1Confirmation, etc.

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Notional Finance

# Notional Finance Average fees per user (AFPU) Methodology

## 1. Overview

AFPU (Average Fees Per User) measures the average daily fee revenue generated per unique user on the Notional lending protocol. This metric answers the question: "How much fee revenue does each active user generate for the protocol on average?" The calculation divides total daily fees (including reserve fees and COMP incentives) by the daily active user count, providing insight into user monetization effectiveness and protocol revenue efficiency.

## 2. Data sources

The AFPU calculation relies on several key data sources:

- **Notional V2 contract events**: Parsed Ethereum event logs from Notional's Router contract, specifically `LendBorrowTrade` events for trading activity and `nTokenSupplyChange` events for liquidity provision
- **Compound V2 contract events**: Parsed `DistributedBorrowerComp` and `DistributedSupplierComp` events from Compound's Comptroller contract to capture COMP token incentive distributions
- **Notional fee events**: Parsed `ReserveFeeAccrued` events from Notional's Router contract containing protocol fee accruals
- **End-of-day token price feeds**: Daily price data for USD conversion of fee amounts across different tokens
- **Token metadata**: Decimal precision and address mapping data for Compound LP tokens (cETH, cDAI, cUSDC, cWBTC)
- **Ethereum transaction records**: Block timestamps and transaction context for daily aggregation boundaries

## 3. Step-by-step calculation

### Component A: Daily active user identification

- **Purpose**: Identify and count unique users who interact with Notional's lending protocol daily
- **Logic**: Extract user addresses from two types of Notional V2 Router contract events. From `LendBorrowTrade` events, capture the `account` parameter and classify users as 'Trader' type. From `nTokenSupplyChange` events, capture the `account` parameter and classify users as 'LP' (liquidity provider) type. All interactions are classified under the 'lending' market sector and business segment. Aggregate users by day using timestamp truncation to daily boundaries. Apply HyperLogLog (HLL) counting algorithm to efficiently handle unique user counting across multiple dimensional breakdowns including project-level, chain-level, user-type-level, and product-level aggregations.
- **Key fields**: `account` addresses from contract events, `block_timestamp` for daily grouping, `user_type` classification as 'Trader' or 'LP'

### Component B: Fee revenue collection

- **Purpose**: Calculate total daily fee revenue from protocol operations and external incentives
- **Logic**: Collect fees from two primary sources. First, gather reserve fees from Notional's `ReserveFeeAccrued` events, which contain the `fee` amount and `currencyId` for different token types. Apply a fee adjustment by dividing amounts by 0.8, indicating an 80% revenue sharing mechanism. Second, collect COMP token incentive rewards from Compound V2's borrower and supplier distribution events, filtering specifically for distributions to Notional's distributor address `0x1344a36a1b56144c3bc62e7757377d288fde0369`. Map currency IDs to specific token addresses using an allowlist of Compound LP tokens (cETH at `0x4ddc2d193948926d02f9b1fe9e1daa0718270ed5`, cDAI at `0x5d3a536e4d6dbd6114cc1ead35777bab948e3643`, cUSDC at `0x39aa39c021dfbae8fac545936693ac917d5e7563`, cWBTC at `0xccf4429db6322d5c611ee964527d42e5d685dd6a`).
- **Key fields**: `fee` amounts from accrual events, `currencyId` for token mapping, `compDelta` amounts from COMP distribution events, `token_address` after currency mapping

### Final aggregation

- **Combining components**: Join the daily active user counts with daily fee totals by matching on the same daily timestamp boundaries
- **Currency conversion**: Convert all fee amounts to USD using end-of-day token price feeds, applying appropriate decimal corrections based on each token's precision specifications
- **Time aggregation**: Aggregate all data to daily boundaries using timestamp truncation, ensuring consistent daily periods across both user and fee calculations
- **Final calculation**: Apply the ARPU formula by dividing the total daily USD fee amount by the daily active user count. Handle missing days using a zero-filling strategy to maintain continuous time series data. The result represents the average USD fee revenue generated per active user on each day.

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Notional FinanceNOTE

Average fees per user (AFPU)

Average fees per user (AFPU)

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