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Unichain

# Unichain Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the average revenue generated per daily active user on the Unichain network. This metric answers the business question: "How much revenue does each active user generate per day on average?" The calculation divides total daily revenue (derived from gas fees) by the number of daily active users. ARPU provides insight into the economic efficiency and monetization effectiveness of the Unichain blockchain.

## 2. Data sources

The ARPU calculation relies on these underlying raw data sources:

- **Unichain transaction logs**: Complete transaction records from the Unichain blockchain containing transaction metadata, gas usage metrics, user addresses, and execution details
- **End-of-day token price feeds**: Daily closing prices for ETH used to convert gas fees from native tokens to USD values
- **Token metadata**: Information about the native ETH token on Unichain, including the canonical token address `0x4200000000000000000000000000000000000006` and symbol
- **Chain availability configuration**: Data defining the operational date ranges and availability periods for Unichain metrics

## 3. Step-by-step calculation

### Component A: Transaction data extraction
- **Purpose**: Extract and standardize transaction data with gas metrics and user information
- **Logic**: Raw Unichain transaction logs are processed to extract key fields including block timestamps, transaction hashes, sender addresses (`from_address`), recipient addresses (`to_address`), and comprehensive gas metrics. Gas metrics include Layer 2 gas usage (`gas_used`), gas price (`gas_price`), Layer 1 gas usage (`l1_gas_used`), Layer 1 gas price (`l1_gas_price`), and Layer 1 fee scalar (`l1_fee_scalar`). The native ETH token is identified using address `0x4200000000000000000000000000000000000006`
- **Key fields**: `block_timestamp`, `transaction_hash`, `from_address`, `gas_used`, `l1_gas_used`, `gas_price`, `l1_gas_price`, `l1_fee_scalar`

### Component B: Gas fee calculation  
- **Purpose**: Calculate total gas fees per transaction combining Layer 1 and Layer 2 components
- **Logic**: For each transaction, Layer 2 gas fees are calculated by multiplying gas used by gas price, then dividing by 1e18 to correct for wei decimals. Layer 1 gas fees are calculated by multiplying Layer 1 gas used by Layer 1 gas price and Layer 1 fee scalar, then dividing by 1e18. The total gas fee per transaction is the sum of Layer 1 and Layer 2 components
- **Key fields**: `l2_gas_fee`, `l1_gas_fee`, total gas fee as sum of both components

### Component C: Revenue aggregation
- **Purpose**: Convert gas fees to USD and aggregate daily revenue
- **Logic**: Gas fees are converted from ETH to USD using end-of-day price feeds through the currency conversion process. Transaction timestamps are truncated to day granularity, and gas fees are summed for each day to calculate total daily revenue. The revenue represents the total gas fees collected by the Unichain network per day
- **Key fields**: `timestamp` (daily), `fees` (in USD), `chain_id`

### Component D: Daily active user counting
- **Purpose**: Count distinct users who performed transactions each day
- **Logic**: User addresses are extracted from transaction sender fields (`from_address`). Transaction timestamps are truncated to day granularity. HyperLogLog (HLL) algorithms are used to efficiently count distinct user addresses per day, enabling scalable computation even with large transaction volumes. The process creates dimensional breakdowns including project-level, chain-level, user-type-level, and product-level aggregations
- **Key fields**: `user_address`, `timestamp` (daily), `user_dau` (distinct count)

### Final aggregation
- **Combining components**: Revenue and daily active user metrics are combined using the ARPU calculation macro, which performs a division operation matching records by date and dimensional attributes
- **Currency conversion**: All gas fees are converted to USD using end-of-day token price feeds, ensuring consistent currency representation across the metric
- **Time aggregation**: Both revenue and user data are aggregated to daily boundaries using timestamp truncation to ensure alignment between numerator and denominator
- **Final calculation**: ARPU is calculated as daily revenue divided by daily active users (Revenue / DAU). Missing days are filled with zeros to maintain a continuous time series. The result represents the average USD revenue generated per daily active user on each day

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

UnichainUNI

Average revenue per user (ARPU)

Average revenue per user (ARPU)

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