Liquidity providers deposit funds into Everclear and receive transfer fees from users (supply-side fees).

Everclear is a cross-chain liquidity network that enables fully non-custodial transfers between EVM-compatible chains and L2 systems. Everclear was co-founded by  Arjun Bhuptani, Rahul Sethuram, and Layne Haber and launched in 2021.

Everclear team & investors own and govern the protocol. They do not currently take a cut of the total transfer fees paid by users (revenue).

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# Everclear Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average daily fee revenue generated per unique user on the Connext protocol. This metric is calculated by dividing the total daily fees collected across all Connext services (bridge transactions and AMM swaps) by the number of unique daily active users. It provides insight into the revenue efficiency per user and helps assess the protocol's monetization effectiveness across its multi-chain bridge and automated market maker operations.

## 2. Data sources

The calculation draws from multiple raw blockchain data sources across supported networks:

- **Bridge transaction events**: Parsed `TransactionManager_TransactionFulfilled_event` logs from Connext V1 across Ethereum, Arbitrum, BSC, Avalanche, Fantom, Gnosis, Optimism, and Polygon chains
- **Cross-chain call events**: Parsed `ConnextDiamond_XCalled_event` logs from Connext V2/Amarok across Ethereum, Arbitrum, BSC, Gnosis, Optimism, and Polygon chains  
- **Bridge preparation events**: Parsed `TransactionManager_TransactionPrepared_event` logs containing transfer amount and routing information
- **AMM swap events**: Parsed `ConnextDiamond_TokenSwap_event` logs from automated market maker operations
- **Fee configuration events**: Parsed `ConnextDiamondSwapAdminFacet_SwapInitialized_event` logs containing swap and admin fee tier settings
- **End-of-day price feeds**: Token price data for USD conversion of fee amounts
- **Token metadata**: Contract addresses, symbols, and decimal configurations for supported tokens
- **Chain metadata**: Chain ID mappings for cross-chain transaction routing

## 3. Step-by-step calculation

### Component A: Daily active user identification
- **Purpose**: Identifies unique users who performed bridge transactions on any given day
- **Logic**: Extracts user addresses from both Connext V1 fulfilled bridge transactions and V2 cross-chain call events. For V1 events, users are identified from the `user` field in `TransactionManager_TransactionFulfilled_event` logs. For V2 events, users are identified from the `params.originSender` field in `ConnextDiamond_XCalled_event` logs. All users are classified as 'Trader' type under the 'bridges' market sector. The process aggregates across all supported chains and applies HyperLogLog counting for efficient distinct user counting across multiple dimensional breakdowns including chain-level, user-type, and product-level groupings
- **Key fields**: `user_address` from transaction events, `block_timestamp` for daily aggregation, `chain` for network identification

### Component B: V1 bridge fee calculation  
- **Purpose**: Calculates fees generated from Connext V1 bridge transactions
- **Logic**: Processes `TransactionManager_TransactionPrepared_event` logs filtered through an allowlist of successfully fulfilled transactions. Applies a fixed 0.05% fee tier to the `transfer_amount` from each transaction. Handles null token addresses by mapping them to their corresponding wrapped asset equivalents on each chain. Uses destination chain data since that's where fee collection occurs. Aggregates daily by destination chain and token address
- **Key fields**: `transfer_amount` for fee basis calculation, `destination_chain_token_address` for token identification, `fee_tier` set at 0.0005

### Component C: V2/Amarok bridge fee calculation
- **Purpose**: Calculates fees generated from Connext V2/Amarok bridge transactions  
- **Logic**: Processes `ConnextDiamond_XCalled_event` logs from cross-chain bridge operations. Applies a fixed 0.05% fee tier to the `params.bridgedAmt` field representing the bridged amount after any AMM swaps. Uses origin chain data for fee attribution. Handles nextToken addresses by mapping them to their underlying asset alternatives for proper price resolution. Aggregates daily by origin chain and token address
- **Key fields**: `bridgedAmt` for fee basis calculation, `origin_chain_token_address` for token identification, `fee_tier` set at 0.0005

### Component D: AMM swap fee calculation
- **Purpose**: Calculates fees generated from automated market maker token swaps
- **Logic**: Processes `ConnextDiamond_TokenSwap_event` logs and matches them with fee tier configurations from `ConnextDiamondSwapAdminFacet_SwapInitialized_event` logs. Combines both swap fees and admin fees by applying their respective tiers to the `tokensSold` amount. Fee tiers are corrected for 10-decimal precision and forward-filled across dates to handle missing configurations. Matches events by pool key ID and timestamp
- **Key fields**: `tokensSold` for swap amount, `swap_fee_tier` and `admin_fee_tier` for fee calculations, `key` for pool identification

### Component E: USD conversion and aggregation
- **Purpose**: Converts all fees to USD and corrects for token decimals
- **Logic**: Applies end-of-day token price feeds to convert fee amounts from native token units to USD values. Corrects for token decimal places to ensure proper unit conversion. Aggregates fees across all three sources (V1 bridge, V2 bridge, AMM swaps) by day, chain, and market classification. Forward-fills missing days with zero values to maintain continuous time series
- **Key fields**: Token prices from price feeds, decimal-corrected fee amounts, daily timestamp aggregation

### Final aggregation
- **Combining components**: Daily fees from all three sources (V1 bridge fees, V2/Amarok bridge fees, AMM swap fees) are summed together after USD conversion. Daily active users are counted distinctly across all bridge transaction types using HyperLogLog aggregation to handle overlapping users efficiently
- **Currency conversion**: All fees are converted to USD using end-of-day token price feeds applied to decimal-corrected token amounts
- **Time aggregation**: Both fees and user counts are aggregated to daily boundaries using `timestamp_trunc` to the day level
- **Final calculation**: The AFPU metric is calculated by dividing the total daily fees (in USD) by the count of unique daily active users, producing the average fee revenue per user for each day

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

EverclearCLEAR

Average fees per user (AFPU)

Average fees per user (AFPU)

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