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Blockchains (L2)

Aventus

# Aventus Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) for Aventus measures the daily revenue generated per active user on the Aventus blockchain ecosystem. This metric is calculated by dividing daily revenue (derived from transaction fees) by the number of daily active users (unique addresses that executed transactions). ARPU provides insight into the economic efficiency and user monetization of the Aventus Layer 2 blockchain platform.

## 2. Data sources

The calculation relies on several core data sources:
- **Aventus blockchain events**: Parsed `TransactionFeePaid` events containing fee amounts and tips from successful transactions
- **Aventus substrate extrinsics**: Native Aventus transaction records including sender addresses
- **Aventus EVM execution events**: Ethereum-compatible transaction events on Aventus, specifically `Executed` events from the `evm` pallet
- **External price data**: End-of-day price feeds from CoinGecko for the Aventus token to enable USD conversion
- **Chain availability data**: Metadata ensuring data quality and completeness across the calculation period

## 3. Step-by-step calculation

### Component A: Fee collection and processing
- **Purpose**: Extract and process transaction fees from Aventus blockchain events
- **Logic**: The system identifies successful `TransactionFeePaid` events from Aventus blockchain event logs. Each event contains JSON-formatted data with fee amounts and tip values stored in specific array positions (offset 1 for amount, offset 2 for tip). These values are parsed from JSON, converted from the native 1e18 decimal format to standard units, and filtered to include only successful transactions
- **Key fields**: `amount` (base transaction fee), `tip` (additional fee), `block_timestamp` (transaction timing), `extrinsic_hash` (transaction identifier)

### Component B: Revenue aggregation and USD conversion
- **Purpose**: Calculate daily fee totals and convert to USD values
- **Logic**: Daily fee totals are computed by summing the `amount` and `tip` fields for each day, grouped by timestamp truncated to day boundaries, chain identifier, and product identifier. The aggregated native token amounts are then converted to USD using end-of-day price feeds from CoinGecko for the Aventus token, applying the conversion at the daily level to match the fee aggregation timeframe
- **Key fields**: `fees` (combined amount + tip), `timestamp` (daily boundary), `chain_id` (blockchain identifier), `product_id` (product classification)

### Component C: User identification and tracking
- **Purpose**: Identify unique active users across Aventus transaction types
- **Logic**: Active users are identified from two distinct sources to capture the full scope of Aventus activity. For native substrate transactions, user addresses are extracted directly from the `id` field in extrinsics data. For Ethereum-compatible transactions, user addresses are parsed from EVM execution events, specifically from the first element of the JSON `event_data` array in `Executed` events from the `evm` pallet. All users are classified as "Transaction sender" type and associated with the Layer 2 blockchain market sector
- **Key fields**: `user_address` (unique identifier), `block_timestamp` (transaction timing), `user_type` (sender classification), `chain` (blockchain identifier)

### Component D: Daily active user counting
- **Purpose**: Calculate daily distinct user counts using efficient aggregation
- **Logic**: User addresses are aggregated into daily distinct counts using timestamp truncation to day boundaries. The system employs HyperLogLog (HLL) functions for efficient distinct counting, particularly important for large user datasets. Initial HLL sketches are created at the daily level, then merged across multiple dimensions including project-level aggregates, chain-specific breakdowns, user type classifications, and product-specific segments. The final distinct counts are extracted from the merged HLL sketches
- **Key fields**: `user_dau` (daily distinct count), `timestamp` (daily boundary), `dimensions` (aggregation level), `hll` (HyperLogLog sketch)

### Final aggregation
- **Combining components**: The ARPU calculation divides daily revenue totals by daily active user counts using the `calculate_arpu` macro, matching records by timestamp and relevant dimensional breakdowns (chain, product, etc.)
- **Currency conversion**: USD conversion occurs at the revenue stage using end-of-day CoinGecko price feeds for the Aventus token, ensuring consistent currency representation before the division
- **Time aggregation**: Both revenue and user metrics use day-level timestamp truncation to ensure proper alignment, with calculations performed on daily boundaries
- **Final calculation**: ARPU is computed as daily revenue (in USD) divided by daily active user count, with the result processed through the `finalize_metric_arpu` macro which applies appropriate fill strategies (fill_zeros for missing periods) and standardizes the output schema for downstream consumption

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

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