The Robonomics chain is a parachain in the Polkadot and Kusama ecosystems designed to provide a decentralized infrastructure for the Internet of Things (IoT) and cyber-physical systems.

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Robonomics Network

# Robonomics Network Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) measures the average transaction fees generated per daily active user on the Robonomics network. This metric answers the business question: "How much revenue does each active user generate through transaction fees?" The calculation divides total daily fees by the count of distinct daily active users, providing insights into user monetization and network usage patterns.

## 2. Data sources

The AFPU calculation relies on three primary data sources:

- **Robonomics blockchain events**: Specifically `TransactionFeePaid` events that contain transaction fee amounts and tip data in JSON format
- **Robonomics extrinsics data**: Transaction records showing the addresses that initiated transactions (transaction senders)
- **External price feeds**: End-of-day token price feeds from CoinGecko for the robonomics-network token to enable USD conversion

## 3. Step-by-step calculation

### Component A: Fee extraction and aggregation
- **Purpose**: Extract and aggregate daily transaction fees in USD
- **Logic**: The system processes `TransactionFeePaid` events from the Robonomics blockchain, parsing JSON event data arrays to extract two fee components: the base transaction `amount` (from the second array element) and the `tip` (from the third array element). Both values are converted from the raw blockchain format by dividing by 1e9 to handle Robonomics' decimal precision. Daily fees are calculated by summing both components (amount + tip) grouped by day, chain, and product identifiers.
- **Key fields**: `block_timestamp` for daily grouping, `amount` and `tip` for fee values, `extrinsic_hash` for transaction identification

### Component B: USD conversion
- **Purpose**: Convert native token fees to USD values
- **Logic**: Daily aggregated fees in native Robonomics tokens are converted to USD using end-of-day price feeds from CoinGecko for the robonomics-network token. The conversion uses daily timestamps to match appropriate exchange rates.
- **Key fields**: `timestamp` for price matching, `fees` for the native token amounts, converted USD values

### Component C: Daily active user counting
- **Purpose**: Count distinct users who performed transactions each day
- **Logic**: The system identifies active users by extracting user addresses from Robonomics extrinsics data, specifically targeting transaction senders. Users are deduplicated at the daily level using timestamp truncation to day boundaries. The calculation uses HyperLogLog (HLL) aggregation for efficient distinct counting, particularly useful for large user sets.
- **Key fields**: `user_address` for user identification, `block_timestamp` truncated to daily boundaries, `user_type` marked as "Transaction sender"

### Component D: Multi-dimensional user aggregation
- **Purpose**: Create user count breakdowns across different dimensions
- **Logic**: Daily active users are aggregated using HyperLogLog across multiple dimensions including project level, individual chains, user types, and product identifiers. This enables flexible AFPU calculations across different analytical breakdowns.
- **Key fields**: `dimensions` for breakdown types, `chain_id` for chain-specific analysis, `product_id` for product-level metrics, `user_type` for user categorization

### Final aggregation
- **Combining components**: The AFPU calculation divides the daily USD fees by the daily active user count using the `calculate_arpu` macro, which performs the mathematical division of revenue metrics by user metrics
- **Currency conversion**: All fees are converted to USD using end-of-day CoinGecko price feeds before the AFPU calculation
- **Time aggregation**: Both fees and user counts use daily boundaries created by truncating timestamps to day level, ensuring consistent temporal alignment
- **Final calculation**: AFPU equals total daily fees in USD divided by the count of distinct daily active users, with zero-filling applied for days with missing data to maintain complete time series

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

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