website

twitter

github

Stablecoin issuers

Fathom

# Fathom Average fees per user (AFPU) Methodology

## 1. Overview

The Fathom AFPU (Average Fees Per User) metric measures the average amount of fees generated per unique daily active user across the Fathom ecosystem. This metric provides insight into user monetization and protocol efficiency by dividing total daily fees by the count of distinct daily active users. The calculation encompasses both DEX trading fees from Fathom DEX and lending protocol fees from Fathom Lending, providing a comprehensive view of revenue per user across all Fathom products.

## 2. Data sources

- **XDC blockchain swap events**: Parsed `Swap` events from Fathom DEX v2 trading pairs containing token amounts and trading activity
- **XDC blockchain transaction records**: Transaction data providing user addresses and transaction context for DEX trades  
- **XDC blockchain lending events**: Parsed events from Fathom Lending v3 including `Supply`, `Withdraw`, `Borrow`, `Repay`, and `FlashLoan` events
- **XDC blockchain treasury events**: `MintedToTreasury` events from Fathom Lending representing protocol revenue from interest
- **XDC blockchain pool creation events**: `PairCreated` events from Fathom DEX Factory defining trading pairs and fee tiers
- **XDC blockchain lending configuration events**: `ReserveFactorChanged` and `ReserveInitialized` events from Fathom Lending Configurator
- **End-of-day token price feeds**: Daily USD prices for all tokens involved in trading and lending operations
- **Token metadata**: Token symbols, decimal places, and contract addresses for proper amount calculations
- **Fathom treasury accruals**: State data tracking cumulative treasury interest accruals over time

## 3. Step-by-step calculation

### Component A: DEX fees calculation
- **Purpose**: Calculate fees generated from Fathom DEX trading activities
- **Logic**: Extract `Swap` events from Fathom DEX v2 pairs on XDC blockchain and join with transaction data to identify user addresses. Calculate token amounts exchanged by taking the difference between input and output amounts for both tokens in each pair. Join with trading pair metadata to get token decimals and fee tiers. Apply decimal corrections to convert raw token amounts to human-readable values. Convert trading volumes to USD using end-of-day price feeds, prioritizing the bought token's price and falling back to the sold token's price if unavailable. Calculate fees by multiplying trading volume by the fee tier (0.3% for all Fathom DEX pairs). Aggregate fees daily across all trading pairs.
- **Key fields**: `token0_amount`, `token1_amount` from swap events, `fee_tier` (0.003), `trading_volume` in USD, calculated `fees`

### Component B: Lending fees calculation  
- **Purpose**: Calculate fees generated from Fathom Lending protocol operations
- **Logic**: Combine two types of lending fees. First, calculate interest-based fees by extracting `MintedToTreasury` events representing protocol's share of borrower interest payments, combining with treasury accrual state data to get total cumulative interest, calculating daily interest amounts by taking differences between consecutive days, and applying reserve factor calculations to determine protocol vs. supplier fee splits. Second, extract flash loan fees from `FlashLoan` events using the `premium` field which represents the fee charged for flash loans. Join all lending data with market metadata to get token addresses and pool information. Convert all amounts to USD using end-of-day price feeds after applying proper decimal corrections. Aggregate fees daily across all lending markets and fee types.
- **Key fields**: `amount` from treasury mints, `premium` from flash loans, `reserve_factor` for fee splits, `daily_revenue` calculations

### Component C: Daily active users calculation
- **Purpose**: Count distinct users active across all Fathom products each day  
- **Logic**: Combine user addresses from DEX trading activity and lending protocol interactions. For DEX users, extract the `user_address` field from transaction records linked to swap events, classifying them as "Trader" user type. For lending users, extract user addresses from multiple event types: `user` from `Supply` and `Withdraw` events (Depositor/Withdrawer), `user` from `Borrow` events and `initiator` from `FlashLoan` events (Borrower), and `repayer` from `Repay` events (Repayer). Aggregate all user addresses by day and count distinct users using `approx_count_distinct` to handle large datasets efficiently. Apply dimensional breakdowns by chain, product, and user type while maintaining overall totals.
- **Key fields**: `user_address` from various events, `user_type` classifications, `user_dau` counts

### Final aggregation  
- **Combining components**: Total daily fees are calculated by summing DEX fees and lending fees for each day. Daily active users are counted as distinct addresses across all product interactions on the same day, avoiding double-counting users who engage with multiple products.
- **Currency conversion**: All fee amounts are converted to USD using end-of-day token price feeds with proper decimal adjustments based on token metadata. Conversion prioritizes available price data and handles missing prices gracefully.
- **Time aggregation**: Data is aggregated to daily boundaries using `timestamp_trunc(block_timestamp, day)` with all events within a 24-hour period contributing to that day's metrics.
- **Final calculation**: AFPU is calculated using the `calculate_arpu` macro which divides total daily fees by total daily active users. The result represents the average fee contribution per unique user per day. Missing days are filled with zeros using the `fill_zeros` strategy, and the final metric is validated through the `finalize_metric_afpu` macro which ensures proper schema compliance and data quality.

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

Fathom

Average fees per user (AFPU)

Average fees per user (AFPU)

Competitive landscape