AVSs (Autonomous Verifiable Services) reward stakers and operators in exchange for security for third party services (supply-side fees).

EigenCloud is a marketplace connecting stakers and operators with applications that need active security. EigenCloud was founded by Sreeram Kannan and launched in 2023.

EigenCloud team and investors own and govern the protocol. They do not currently take a cut of the total rewards paid by AVSs (revenue). EigenCloud's investors include Blockchain Capital, Polychain Capital, Coinbase Ventures, etc.

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EigenCloud

# EigenCloud Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the daily average revenue generated per active user on the EigenLayer protocol. This metric answers the business question: "How much fee revenue does EigenLayer generate per user on a daily basis?" The calculation divides daily total fees (in USD) by the count of daily active users, where users are identified through their interactions with core EigenLayer contracts for staking, delegation, and reward claiming activities.

## 2. Data sources

The AFPU calculation relies on the following raw data sources:

- **Blockchain events**: Parsed Ethereum event logs from EigenLayer v1 protocol smart contracts, specifically capturing deposit, withdrawal, delegation, and reward claim activities
- **Smart contract events**: Four specific event types from EigenLayer contracts - `StrategyManager_Deposit_event`, `StrategyManager_WithdrawalCompleted_event`, `DelegationManager_OperatorSharesDecreased_event`, `DelegationManager_OperatorSharesIncreased_event`, and `RewardsCoordinator_RewardsClaimed_event`
- **External data**: End-of-day token price feeds for USD conversion across all supported tokens
- **Token metadata**: Token decimal configurations for proper amount normalization

## 3. Step-by-step calculation

### Component A: Daily active user identification

- **Purpose**: Identify and count unique users who interact with EigenLayer protocol daily
- **Logic**: Extract user addresses from four types of EigenLayer smart contract events on Ethereum. The `StrategyManager_Deposit_event` captures users making deposits (classified as "Depositor" type), `StrategyManager_WithdrawalCompleted_event` captures users completing withdrawals ("Withdrawer" type), `DelegationManager_OperatorSharesDecreased_event` captures stakers reducing their delegation ("Withdrawer" type), and `DelegationManager_OperatorSharesIncreased_event` captures stakers increasing delegation ("Depositor" type). User addresses are extracted from the `depositor`, `withdrawer`, and `staker` fields respectively. All interactions are truncated to daily timestamps and deduplicated to count each user only once per day, regardless of how many transactions they performed
- **Key fields**: `block_timestamp` for daily aggregation, `depositor`/`withdrawer`/`staker` fields for user address extraction, `user_type` classification, and `chain` identifier (always "ethereum")

### Component B: Fee aggregation using HyperLogLog

- **Purpose**: Efficiently aggregate unique user counts across different dimensional breakdowns while maintaining accuracy
- **Logic**: Apply HyperLogLog (HLL) sketching algorithm to the daily user addresses to enable efficient aggregation across multiple dimensions. Create separate aggregations for project-level totals, chain-level breakdowns, user type breakdowns, and product-level breakdowns. Each aggregation maintains the ability to count distinct users accurately even when combining data across different groupings. The HLL approach prevents double-counting users who appear in multiple categories while enabling flexible dimensional analysis
- **Key fields**: `hll` sketches for user counting, `dimensions` field for breakdown type, `chain_id`, `user_type`, and `product_id` for dimensional analysis

### Component C: Fee revenue calculation

- **Purpose**: Calculate daily total fee revenue in USD from EigenLayer reward claims  
- **Logic**: Extract reward claim data from `RewardsCoordinator_RewardsClaimed_event` which captures when users claim their staking rewards. Each event contains the `claimedAmount` (the fee/reward amount), `token` address (the token being claimed), and relevant user addresses (`earner`, `claimer`, `recipient`). Aggregate all claimed amounts by day and token address to get daily totals per token. Apply decimal correction using token metadata to normalize amounts to their proper decimal representation. Convert each token amount to USD using end-of-day price feeds, then sum across all tokens to get total daily fee revenue in USD
- **Key fields**: `claimedAmount` for raw fee amounts, `token` address for price lookup, `block_timestamp` for daily aggregation, and USD-converted amounts after price application

### Final aggregation

- **Combining components**: Join the daily active user counts with daily fee revenue totals on the timestamp field. Both components are aggregated to the same daily grain, enabling direct division
- **Currency conversion**: All fee amounts are converted to USD using end-of-day price feeds applied to each token type, ensuring consistent currency representation across different reward tokens
- **Time aggregation**: Both user counts and fee totals use daily timestamp truncation (start of day) as the aggregation boundary, ensuring alignment between numerator and denominator
- **Final calculation**: Calculate AFPU by dividing total daily fees (in USD) by the daily active user count. Handle edge cases where user count is zero by applying a fill strategy that populates missing days with zero values rather than null, maintaining time series continuity for downstream analysis

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

EigenCloudEIGEN

Average fees per user (AFPU)

Average fees per user (AFPU)

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