Traders exchange funds through request for quotation system built on 0x protocol and aggregated AMMs. Tokenlon collects a trading fee (revenue) from trades.

Tokenlon is a non-custodial exchange protocol built on Ethereum. Tokenlon was founded by imToken team and launched in 2018.

LON tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue). Tokelon's investors include IDG Capital, Qiming Venture Partners, Breyer Capital, etc.

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# Tokenlon Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average fee revenue generated per daily active user on the Tokenlon protocol. This metric provides insights into user value and revenue efficiency by dividing total daily fees by the number of unique users who traded that day. The calculation covers multiple Tokenlon contract versions across Ethereum and Arbitrum chains, incorporating different fee structures and trading mechanisms.

## 2. Data sources

- **Blockchain transaction records**: Ethereum and Arbitrum transaction data to identify user addresses and link them to contract interactions
- **Parsed Tokenlon contract events**: Multiple event types across different protocol versions including `Fill`, `Swapped`, `FillOrder`, and `LimitOrderFilledByProtocol` events
- **Multi-version contract data**: Events from Tokenlon v1 contracts on both Ethereum and Arbitrum, covering different trading mechanisms (ZeroExchange, AMMWrapper, AMMWrapperWithPath, PMM, RFQ, LimitOrder)
- **End-of-day token price feeds**: USD price data for converting token amounts to standardized currency values
- **Token metadata**: Decimal precision information for proper amount calculations

## 3. Step-by-step calculation

### Component A: Daily active users calculation

- **Purpose**: Identify and count unique users who executed trades on Tokenlon each day
- **Logic**: Extract all trade events from Tokenlon contracts across Ethereum and Arbitrum chains. Filter events to include only those involving the Tokenlon protocol address `0xb9e29984fe50602e7a619662ebed4f90d93824c7`. Link each contract event to its corresponding blockchain transaction to identify the `from_address` as the user. Group transactions by daily boundaries and count distinct user addresses using HyperLogLog aggregation for computational efficiency. Users are classified as 'Trader' type for business categorization.
- **Key fields**: `user_address` from transaction records, `block_timestamp` for daily grouping, `transaction_hash` for event-to-transaction linking

### Component B: Fee collection calculation  

- **Purpose**: Calculate total fees collected by the protocol from trading activities
- **Logic**: Process fee collection through different mechanisms based on contract version. For ZeroExchange `Fill` events, calculate fees as 0.3% of the `takerAssetFilledAmount`. For other contract events (`AMMWrapper_Swapped`, `AMMWrapperWithPath_Swapped`, `PMM_FillOrder`, `RFQ_FillOrder`), calculate fees as the difference between `receivedAmount` and `settleAmount`, representing the protocol's profit margin. For Arbitrum `LimitOrderFilledByProtocol` events, use the `takerTokenProfit` field directly. Apply the same protocol address filter to ensure consistency with user calculations. Handle native token addresses by converting them to wrapped equivalents (WETH on Ethereum, WETH on Arbitrum).
- **Key fields**: `takerAssetFilledAmount`, `receivedAmount`, `settleAmount`, `takerTokenProfit` for different fee calculation methods, `token_address` for fee denomination

### Component C: Currency conversion and standardization

- **Purpose**: Convert all fee amounts to USD for consistent aggregation across different tokens
- **Logic**: Join fee collection data with end-of-day token price feeds to get USD exchange rates. Apply token-specific decimal corrections to ensure proper amount scaling (e.g., adjusting for 18-decimal tokens like WETH vs 6-decimal tokens like USDC). Calculate USD value by multiplying token amounts by their respective prices and decimal adjustment factors. Aggregate converted amounts by day, chain, and other dimensional attributes.
- **Key fields**: `amount` (token quantity), `token_address` (for price lookup), daily `timestamp` for price matching

### Final aggregation

- **Combining components**: Join daily active user counts with daily fee totals using matching time boundaries and dimensional attributes (chain, product version, etc.)
- **Currency conversion**: All fees are converted to USD using end-of-day price feeds and proper decimal adjustments applied during the fee calculation stage
- **Time aggregation**: Both components use daily timestamp truncation to ensure consistent time boundaries for the division calculation
- **Final calculation**: Apply the ARPU formula by dividing total daily fees (in USD) by the count of daily active users. Handle edge cases where user count is zero by filling with zeros rather than null values. Apply data quality measures including filling missing days with zeros and filtering based on chain data availability windows.

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

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Average fees per user (AFPU)

Average fees per user (AFPU)

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