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# Phantom Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average amount of fees generated per daily active user of the Phantom wallet. This metric is calculated by dividing the total daily fees collected by Phantom by the number of unique users who generated those fees. AFPU provides insight into the monetization efficiency and user engagement level of the Phantom wallet ecosystem, helping understand how much revenue each active user generates on average.

## 2. Data sources

The AFPU calculation relies on several key data sources:

- **Solana native transfer events**: Records of SOL transfers on the Solana blockchain, specifically transfers directed to Phantom's fee collection addresses
- **Solana SPL token transfer events**: Records of SPL (Solana Program Library) token transfers, capturing fees paid in various tokens to Phantom's collection addresses  
- **End-of-day token price feeds**: Daily closing prices for SOL and SPL tokens to enable USD conversion of fees collected in different tokens
- **Token metadata**: Information about token decimal places and contract addresses needed for proper amount normalization and identification

## 3. Step-by-step calculation

### Component A: SOL fee collection
- **Purpose**: Captures fees paid to Phantom in native SOL tokens
- **Logic**: Identifies all native SOL transfers sent to Phantom's eight designated fee collection addresses (`25mYnjJ2MXHZH6NvTTdA63JvjgRVcuiaj6MRiEQNs1Dq`, `9yj3zvLS3fDMqi1F8zhkaWfq8TZpZWHe6cz1Sgt7djXf`, and six others). Filters out transfers where the sender is also one of these fee addresses to exclude internal movements between Phantom's own accounts. Each transaction record includes the transfer amount, timestamp, transaction signer (user), and marks the token as SOL's address (`So11111111111111111111111111111111111111112`)
- **Key fields**: `block_timestamp` for timing, `transaction_signer` for user identification, `amount` for fee value, and `to_address` for fee collection validation

### Component B: SPL token fee collection  
- **Purpose**: Captures fees paid to Phantom in various SPL tokens (non-native Solana tokens)
- **Logic**: Identifies all SPL token transfers where the recipient owner is one of Phantom's eight fee collection addresses. Similar to SOL fees, excludes transfers where the transaction signer is one of the fee addresses to avoid internal movements. Records include the specific token address, transfer amount, and transaction details
- **Key fields**: `token_address` for token identification, `transaction_signer` for user identification, `amount` for fee value, and `to_owner_address` for fee collection validation

### Component C: Daily active user counting
- **Purpose**: Counts unique users who paid fees to Phantom each day
- **Logic**: Combines transaction signers from both SOL and SPL token fee payments, then deduplicates by day using the transaction signer as the unique user identifier. Uses HyperLogLog aggregation for efficient counting across large datasets. Creates breakdowns by multiple dimensions including overall project level, chain level (Solana), user type (marked as 'Trader'), and product level
- **Key fields**: `user_dau` field containing the unique user identifier, aggregated using HyperLogLog for scalable distinct counting

### Component D: Fee aggregation and USD conversion
- **Purpose**: Converts all collected fees to USD and aggregates by day
- **Logic**: Takes fees from both SOL and SPL token collections, groups by day, chain, product, and token address. Applies decimal corrections based on each token's specification (SOL uses 9 decimals, SPL tokens vary). Converts all amounts to USD using end-of-day price feeds. Sums total fees across all tokens for each day
- **Key fields**: `fees` containing the USD-converted daily fee totals, with proper decimal adjustment and price conversion applied

### Final aggregation
- **Combining components**: The user count from Component C and fee totals from Component D are joined by timestamp (day) to create matched pairs of daily users and daily fees
- **Currency conversion**: All fees are already converted to USD in Component D using end-of-day price feeds and proper decimal corrections for each token type
- **Time aggregation**: Both user counts and fees are aggregated to daily boundaries using timestamp truncation to day granularity
- **Final calculation**: AFPU is calculated by dividing the total daily fees (in USD) by the count of daily active users for each day. Days with zero users or zero fees are filled with zero values to maintain complete time series. The result represents the average fee amount in USD generated per active user per day

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

Phantom

Average fees per user (AFPU)

Average fees per user (AFPU)

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