Ajuna is a gaming blockchain built on Polkadot, focused on enabling performance and scalability, for web3 gaming supporting the Unity and Unreal Engine game engines.

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Blockchains (L2)

Ajuna Network

# Ajuna Network Average revenue per user (ARPU) Methodology

## 1. Overview

ARPU measures the average revenue generated per daily active user on the Ajuna blockchain network. This metric is calculated by dividing the total daily revenue (transaction fees converted to USD) by the number of distinct daily active users. ARPU helps evaluate the monetization effectiveness and user value on the Ajuna network by showing how much revenue each user generates on average per day.

## 2. Data sources

- **Blockchain events**: Parsed Ajuna `TransactionFeePaid` events containing transaction fee amounts and tips
- **Transaction data**: Ajuna extrinsics records containing transaction sender addresses and execution details
- **External data**: End-of-day price feeds from CoinGecko for Ajuna network token (ajuna-network-2) to enable USD conversion
- **Data types**: Native token amounts with 12 decimal places, transaction timestamps, user addresses, and daily price snapshots

## 3. Step-by-step calculation

### Component A: Revenue calculation
- **Purpose**: Calculate total daily revenue from transaction fees in USD
- **Logic**: Extract successful `TransactionFeePaid` events from Ajuna blockchain data. Each event contains an `amount` field (base transaction fee) and `tip` field (additional fee paid by users). Convert amounts from native token units (with 12 decimal places) to standard decimal format by dividing by 1e12. Sum the `amount` and `tip` for each transaction to get total fees per transaction. Aggregate all transaction fees by day to get daily total revenue in native tokens. Convert daily native token revenue to USD using end-of-day price feeds from CoinGecko for the Ajuna network token.
- **Key fields**: `amount` (base transaction fee), `tip` (additional user-paid fee), `block_timestamp` (transaction time), `success` (transaction status filter)

### Component B: Daily active users calculation
- **Purpose**: Count distinct users who performed transactions each day
- **Logic**: Extract all extrinsics (transactions) from Ajuna blockchain data, focusing on the transaction sender addresses (`id` field). Filter to successful transactions and truncate timestamps to daily boundaries. Count distinct user addresses per day using HyperLogLog (HLL) algorithm for scalable computation. Apply HLL aggregation across multiple dimensional breakdowns including project-level, chain-level, user type, and product ID to support various analytical perspectives.
- **Key fields**: `id` (transaction sender address), `block_timestamp` (transaction time), user addresses as distinct count targets

### Final aggregation
- **Combining components**: Join daily revenue totals with daily active user counts by matching on the same date boundaries. Both components use daily timestamp truncation to ensure proper alignment
- **Currency conversion**: Revenue conversion to USD occurs before the final ARPU calculation using end-of-day CoinGecko price feeds for the Ajuna network token
- **Time aggregation**: All calculations use daily boundaries with timestamp truncation to day level. Missing days are filled with zero values for both revenue and user counts
- **Final calculation**: Divide the daily revenue amount (in USD) by the daily active user count to produce the average revenue per user for each day. Apply zero-fill strategy for missing days to maintain continuous time series data

*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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