Stakers deposit funds into Frax and receive a return on investment in the form of staking rewards (supply-side fees).


Frax Ether is a liquid staking derivative product created by the Frax Finance protocol. Frax Finance was founded by Sam Kazemian, Stephen Moore, Jason Huoan & Travis Moore and launched in 2019.


FRAX tokenholders own and govern the Frax Finance protocol, including the Frax Ether business line. They currently take a cut of the total staking rewards earned by the protocol (revenue). Frax’s investors include Crypto.com Capital & Ascensive Assets.


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Frax Ether

# Frax Ether Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the average daily revenue generated per active user on the Frax protocol. This metric helps evaluate the monetization efficiency of the liquid staking protocol by dividing daily protocol revenue by the number of daily active users. The calculation captures revenue from staking rewards distributed through the protocol and divides it by users who actively deposit ETH for liquid staking.

## 2. Data sources

The ARPU calculation relies on the following raw data sources:
- **Frax protocol events**: Parsed Ethereum blockchain events including `SfrxETH_NewRewardsCycle` events that capture staking reward distributions and `FrxETHMinter_ETHSubmitted` events that track user ETH deposits
- **Blockchain transaction data**: Ethereum transaction records containing event logs, block timestamps, and transaction hashes
- **External price feeds**: End-of-day token price feeds used for USD conversion of reward amounts
- **Token metadata**: Token decimal precision data for accurate amount calculations

## 3. Step-by-step calculation

### Component A: Supply-side fee collection
- **Purpose**: Captures staking rewards distributed to users as the basis for protocol fee calculation
- **Logic**: Extracts `SfrxETH_NewRewardsCycle` events from Ethereum blockchain logs. Each event contains a `rewardAmount` field representing staking rewards distributed to users. Events are filtered to exclude removed/invalid transactions. The component maps each reward event to the sfrxETH token contract address and classifies all activity under the "liquid staking" business segment.
- **Key fields**: `rewardAmount` (reward tokens distributed), `block_timestamp` (event timing), `transaction_hash` and `log_index` (unique event identification)

### Component B: Fee calculation from supply-side rewards  
- **Purpose**: Converts user staking rewards into total protocol fees
- **Logic**: Takes the supply-side rewards and applies business logic to calculate total fees. The calculation assumes that supply-side rewards represent 90% of total fees (with 10% going to the protocol). Total fees are calculated by dividing supply-side rewards by 0.9. All reward amounts are converted to USD using end-of-day price feeds and corrected for token decimal precision. Daily aggregation is applied using timestamp truncation.
- **Key fields**: `fees_supply_side` (USD-converted rewards), `timestamp` (daily boundary), `chain_id` (blockchain identifier)

### Component C: Revenue calculation
- **Purpose**: Determines protocol revenue from total fees
- **Logic**: Applies a revenue multiplier of 0.1 (10%) to total fees to calculate protocol revenue. This represents the portion of fees that the protocol retains as revenue, with the remaining 90% distributed to stakers. The calculation multiplies daily total fees by the revenue multiplier to get daily revenue amounts in USD.
- **Key fields**: `fees` (total daily fees), `revenue` (protocol's portion of fees)

### Component D: Daily active user identification
- **Purpose**: Counts unique users who actively interact with the protocol each day
- **Logic**: Parses `FrxETHMinter_ETHSubmitted` events from Ethereum to identify user deposit transactions. Extracts the `sender` field as the user address for each deposit event. Events are classified by user type (Depositor) and business segment (liquid staking). Daily boundaries are established through timestamp truncation to day granularity.
- **Key fields**: `user_address` (unique user identifier), `block_timestamp` (interaction timing), `user_type` (interaction classification)

### Component E: Daily active user aggregation
- **Purpose**: Efficiently counts distinct daily active users across multiple dimensions
- **Logic**: Uses HyperLogLog (HLL) probabilistic data structure to count distinct users per day. The aggregation creates multiple dimensional breakdowns including project-level totals, chain-level breakdowns, user-type breakdowns, and product-level breakdowns. HLL enables efficient distinct counting while maintaining accuracy for large datasets. Daily user counts are extracted from the merged HLL sketches.
- **Key fields**: `user_dau` (distinct daily active users), `dimensions` (aggregation level), `timestamp` (daily boundary)

### Final aggregation
- **Combining components**: The `calculate_arpu` macro joins daily revenue data with daily active user counts on matching timestamps and dimensional attributes (chain, product). Revenue values are divided by user counts to calculate average revenue per user for each day.
- **Currency conversion**: All revenue amounts are already converted to USD during the fee calculation phase using end-of-day price feeds and decimal correction
- **Time aggregation**: Daily boundaries are consistently applied across both revenue and user calculations using timestamp truncation to day granularity
- **Final calculation**: ARPU equals daily revenue divided by daily active users (ARPU = Revenue ÷ DAU). The `finalize_metric_arpu` macro applies a fill-zeros strategy to ensure continuous time series data and standardizes the output format with proper metadata and dimensional attributes.

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

Frax Ether

Average revenue per user (ARPU)

Average revenue per user (ARPU)

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