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Fathom

# Fathom Active users (daily) Methodology

## 1. Overview

The Fathom user daily active users (DAU) metric measures the number of unique users who interact with Fathom protocol products on any given day. This metric combines activity from two main business lines: decentralized exchange (DEX) trading through Fathom DEX and lending activities through Fathom Lending. The calculation aggregates unique user addresses across multiple dimensional breakdowns to provide comprehensive insights into daily user engagement across the Fathom ecosystem.

## 2. Data sources

The methodology relies on several categories of raw blockchain data from the XDC network:

- **DEX swap events**: Parsed `Pair_Swap` events from Fathom DEX V2 contracts containing swap transaction details, token amounts, and participant addresses
- **Transaction records**: XDC transaction data used to resolve actual user addresses from contract interactions
- **Lending events**: Multiple types of parsed events from Fathom Lending V3 contracts:
  - `LendingPool_Supply` events for deposit activities
  - `LendingPool_Withdraw` events for withdrawal activities  
  - `LendingPool_Borrow` events for borrowing activities
  - `LendingPool_FlashLoan` events for flash loan activities
  - `LendingPool_Repay` events for loan repayment activities

All data sources originate from XDC blockchain event logs and transaction records, capturing on-chain interactions with Fathom protocol contracts.

## 3. Step-by-step calculation

### Component A: DEX user identification
- **Purpose**: Identifies unique users who performed trading activities on Fathom DEX
- **Logic**: Processes `Pair_Swap` events from Fathom DEX V2 contracts on XDC network. Extracts the contract caller address from swap events and joins with XDC transaction records to resolve the actual transaction sender address, ensuring accurate user identification rather than just contract addresses. Calculates token amount changes by computing the difference between inflow and outflow amounts for both tokens in each swap. Truncates timestamps to daily boundaries and classifies all users as 'Trader' type
- **Key fields**: Block timestamp for daily aggregation, user address from transaction sender, `amount0In/Out` and `amount1In/Out` for trade validation, chain identifier set to 'xdc', and product identifier set to 'Fathom DEX'

### Component B: Lending user identification  
- **Purpose**: Identifies unique users who performed lending-related activities on Fathom Lending
- **Logic**: Aggregates user addresses from five different lending event types, each mapped to specific user classifications. Supply events identify 'Depositor' users using the `user` field. Withdraw events identify 'Withdrawer' users using the `user` field. Borrow events identify 'Borrower' users using the `user` field. FlashLoan events identify 'Borrower' users using the `initiator` field to capture the actual loan initiator. Repay events identify 'Repayer' users using the `repayer` field. All events are truncated to daily boundaries and tagged with appropriate business segment and product identifiers
- **Key fields**: Block timestamp for daily aggregation, user address from event-specific fields (`user`, `initiator`, `repayer`), user type classification based on event type, chain identifier set to 'xdc', and product identifier set to 'Fathom Lending'

### Component C: User data consolidation
- **Purpose**: Combines DEX and lending user activity into a unified dataset
- **Logic**: Unions the DEX user dataset and lending user dataset using consistent schema with timestamp, chain, user type, product identifier, and user address fields. Maintains separate user type classifications to enable dimensional analysis while ensuring no duplication of user counting across different activity types
- **Key fields**: Daily timestamp boundary, chain identifier, user type classification, product identifier, and unique user address

### Final aggregation
- **Combining components**: The consolidated user dataset is processed through four separate dimensional aggregations using approximate distinct count functions for performance optimization
- **Dimensional breakdowns**: Creates four separate views - project-level aggregation (all Fathom users regardless of dimension), chain-level aggregation (by blockchain network), user-type aggregation (by activity classification like Trader, Depositor, etc.), and product-level aggregation (by specific Fathom products like Fathom DEX or Fathom Lending)
- **Time aggregation**: All user activity is aggregated at daily boundaries using timestamp truncation to day level, with each day representing a distinct measurement period
- **Final calculation**: Each dimensional breakdown uses approximate distinct count of user addresses grouped by the relevant dimensions, then unions all breakdowns together. A finalization process applies gap-filling logic to ensure missing days are represented with zero values and standardizes the output schema for consistent reporting

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

Unique revenue-generating users over a fixed 24-hour window.

Fathom

Active users (daily)

Active users (daily)

Competitive landscape