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 revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the average daily revenue generated per active user on the Connext bridge protocol. The metric is calculated by dividing daily protocol revenue by daily active users. For Connext, this metric consistently results in $0 ARPU because the protocol operates as a fee-free bridge where users don't pay direct revenue to the protocol, despite underlying fee structures for operational costs.

## 2. Data sources

The calculation relies on several blockchain data sources:

- **Connext V1 transaction events**: Parsed `TransactionManager_TransactionFulfilled_event` logs from Arbitrum, Avalanche, BSC, Ethereum, Fantom, Gnosis, Optimism, and Polygon networks representing completed bridge transactions
- **Connext V2 transaction events**: Parsed `ConnextDiamond_XCalled_event` logs from Arbitrum, BSC, Ethereum, Gnosis, Optimism, and Polygon networks representing cross-chain calls
- **Bridge transaction data**: Additional `TransactionManager_TransactionPrepared_event` logs for trade volume calculations
- **AMM swap data**: `ConnextDiamond_TokenSwap_event` logs for automated market maker fee calculations  
- **AMM configuration data**: `SwapAdminFacet_SwapInitialized_event` logs for fee tier configurations
- **End-of-day price feeds**: Token price data for USD conversion calculations
- **Token metadata**: Decimal precision and addressing information for accurate amount calculations

## 3. Step-by-step calculation

### Component A: Daily active user identification
- **Purpose**: Identify and count unique users who completed bridge transactions each day
- **Logic**: Extract user addresses from completed Connext bridge transactions across both V1 and V2 protocols. For V1 transactions, user addresses are extracted from the `user` field in `TransactionFulfilled` events. For V2 transactions, user addresses are extracted from the `originSender` field within transaction parameters of `XCalled` events. All identified users are classified as 'Trader' type users within the bridges market sector and AMM business segment
- **Key fields**: User addresses (`user` for V1, `originSender` for V2), block timestamps for daily grouping, chain identifiers for multi-chain aggregation

### Component B: Daily active user aggregation  
- **Purpose**: Efficiently count distinct users across multiple dimensions using probabilistic data structures
- **Logic**: Create HyperLogLog sketches for each daily user set to enable efficient distinct counting and aggregation. Generate separate user counts across four dimensional breakdowns: project-wide totals, per-chain breakdowns, per-user-type breakdowns, and per-product breakdowns. Use HyperLogLog merge operations to combine sketches while maintaining accuracy for distinct user counts
- **Key fields**: HyperLogLog sketches (`hll`), dimensional identifiers (`chain_id`, `user_type`, `product_id`), extracted distinct user counts (`user_dau`)

### Component C: Revenue calculation
- **Purpose**: Calculate daily protocol revenue (which equals zero for Connext)
- **Logic**: Set revenue to zero across all time periods, chains, and products, reflecting Connext's business model as a fee-free bridge protocol. While the underlying fee calculation system tracks bridge fees from V1 trades, Amarok cross-chain fees, and AMM swap fees with various fee tiers and USD conversions, the final protocol revenue is explicitly set to zero because these fees cover operational costs rather than generate protocol revenue
- **Key fields**: Revenue amounts (always 0), timestamps for daily grouping, chain and product identifiers for dimensional consistency

### Final aggregation
- **Combining components**: Join daily active user counts with daily revenue amounts by timestamp and dimensional attributes (chain, product). Both metrics use the same dimensional structure to ensure proper alignment
- **Currency conversion**: All revenue values are already in USD (though zero), maintaining consistency with other protocol metrics
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation, with forward-filling applied to ensure no gaps in the time series
- **Final calculation**: Divide daily revenue by daily active users using the standard ARPU formula (Revenue ÷ DAU). Since revenue is always zero, the result is consistently $0 ARPU across all time periods and dimensional breakdowns

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

EverclearCLEAR

Average revenue per user (ARPU)

Average revenue per user (ARPU)

Competitive landscape