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SolTradingBot

# SolTradingBot Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the average daily revenue generated per active user for the SolTradingBot protocol on Solana. ARPU is calculated by dividing daily revenue by daily active users, where both metrics are derived from the same underlying fee payment data. This metric answers the business question: "How much revenue does each active user generate on average per day?" The calculation uses fee payments to specific protocol addresses as the primary indicator of both user activity and revenue generation.

## 2. Data sources

The ARPU calculation relies on the following raw data sources:

- **Solana native transfers**: SOL transfer events on the Solana blockchain, specifically transfers directed to two protocol-owned fee collection addresses
- **End-of-day price feeds**: Daily SOL-to-USD exchange rates used for currency conversion
- **Chain availability metadata**: Information about Solana network operational status used for data filtering
- **Protocol addresses**: Two hardcoded Solana addresses that serve as fee collection points for the SolTradingBot protocol

## 3. Step-by-step calculation

### Component A: Fee data collection
- **Purpose**: Identify and collect all fee payments made to the SolTradingBot protocol
- **Logic**: Filter Solana native transfer events to capture SOL transfers directed to two specific protocol fee collection addresses. Exclude self-transfers by filtering out transactions where the transaction signer is also one of the fee collection addresses. Each qualifying transfer represents a fee payment from a user to the protocol.
- **Key fields**: `block_timestamp` for temporal analysis, `transaction_signer` for user identification, `to_address` for fee collection address validation, `amount` for fee value in lamports

### Component B: Revenue calculation
- **Purpose**: Convert daily fee collections into USD revenue amounts
- **Logic**: Aggregate fee payments by day, converting amounts from lamports to SOL by dividing by 1e9. Apply end-of-day SOL-to-USD conversion rates to get revenue in USD. Group by timestamp, chain, and product dimensions. Fill missing days with zero values to maintain continuous time series.
- **Key fields**: Daily aggregated `fees` converted to USD, `timestamp` truncated to day boundaries, `chain_id` and `product_id` for dimensional analysis

### Component C: Daily active user calculation  
- **Purpose**: Count unique users who paid fees each day
- **Logic**: Identify unique transaction signers from the same fee payment data used for revenue calculation. Classify all users as 'Trader' type since they represent users actively engaging with the protocol. Use HyperLogLog sketching to efficiently count distinct users across multiple dimensional breakdowns including project-level, chain-level, user-type-level, and product-level aggregations. Fill missing days with zero values.
- **Key fields**: `user_dau` representing distinct transaction signers, `user_type` classified as 'Trader', dimensional breakdown fields for chain, product, and user type

### Final aggregation
- **Combining components**: The ARPU calculation uses a macro that divides the daily revenue metric by the daily active user metric for corresponding dates and dimensions
- **Currency conversion**: Revenue amounts are converted from SOL to USD using end-of-day price feeds before the ARPU calculation
- **Time aggregation**: Both revenue and DAU are aggregated to daily boundaries using timestamp truncation to day level
- **Final calculation**: ARPU equals daily revenue in USD divided by daily active users, with zero-filling applied to ensure continuous time series coverage and handle days with no activity

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

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Average revenue per user (ARPU)

Average revenue per user (ARPU)

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