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BONKbot

# BONKbot Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average daily fee revenue generated per active user on the BonkBot trading platform. This metric is calculated by dividing the total daily fees collected by BonkBot by the number of unique daily active users. It provides insight into user monetization effectiveness and revenue density for the platform.

## 2. Data sources

The calculation relies on several key data sources:
- **Solana native transfers**: Native SOL transfers on the Solana blockchain, specifically transfers to BonkBot's fee collection address
- **Solana SPL token transfers**: SPL token transfers on Solana, filtered to those directed to BonkBot's fee collection address
- **Transaction data**: Solana transaction records containing signer information to identify unique users
- **Token metadata**: Token contract information for proper decimal handling of SPL tokens
- **End-of-day price feeds**: Daily token price data for USD conversion of fees collected in various tokens

## 3. Step-by-step calculation

### Component A: SOL fee collection
- **Purpose**: Captures native SOL fees paid to BonkBot
- **Logic**: Extracts native SOL transfers where the recipient address is BonkBot's fee collection address (`ZG98FUCjb8mJ824Gbs6RsgVmr1FhXb2oNiJHa2dwmPd`) and the transaction signer is not the fee address itself. This filtering prevents self-transfers from being counted as user fees. Data is aggregated daily by truncating timestamps to day boundaries.
- **Key fields**: `block_timestamp` for timing, `transaction_signer` for user identification, `amount` for fee value, and `token_address` (hardcoded to SOL's address)

### Component B: SPL token fee collection  
- **Purpose**: Captures SPL token fees paid to BonkBot
- **Logic**: Extracts SPL token transfers where the recipient owner address matches BonkBot's fee collection address and the transaction signer is not the fee address. This captures fees paid in various SPL tokens rather than native SOL. The same filtering logic prevents self-transfers from being counted.
- **Key fields**: `block_timestamp` for timing, `transaction_signer` for user identification, `amount` for fee value, and `token_address` for the specific SPL token

### Component C: Daily active user calculation
- **Purpose**: Determines the count of unique users active each day
- **Logic**: Combines transaction signers from both SOL and SPL fee transactions, then counts distinct signers per day using HyperLogLog aggregation for scalability. Users are defined as addresses that initiated fee-paying transactions. The calculation uses a union of SOL and SPL fee data, with timestamp truncation to daily boundaries and deduplication of user addresses across both data streams.
- **Key fields**: `signer` addresses deduplicated across transaction types, `timestamp` truncated to daily boundaries

### Component D: Fee aggregation and USD conversion
- **Purpose**: Calculates total daily fees in USD across all token types
- **Logic**: Daily fees are summed by token address, then converted to USD using end-of-day price feeds. The conversion process includes decimal correction to handle different token precision levels. SOL fees use the native SOL token address, while SPL fees maintain their specific token addresses for accurate price lookup.
- **Key fields**: `fees` amounts summed by day and token, `token_address` for price lookup, USD-converted values after decimal correction

### Final aggregation
- **Combining components**: Daily fee totals in USD are divided by the count of daily active users using the `calculate_arpu` macro, which implements the AFPU calculation logic
- **Currency conversion**: All fees are converted to USD using end-of-day token prices, with proper decimal adjustment for each token type
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation, ensuring consistent time alignment between user counts and fee totals
- **Final calculation**: AFPU equals the sum of all daily fees in USD divided by the count of unique daily active users, with gap-filling applied to ensure continuous daily data and proper schema validation through the `finalize_metric_afpu` macro

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

BONKbot

Average fees per user (AFPU)

Average fees per user (AFPU)

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