Validators process transactions and receive fees from users (supply-side fees).

Gnosis Chain is a smart contract platform for decentralized applications (a blockchain). Gnosis was founded by Martin Köppelmann and Stefan George and launched in 2015.

GNO holders own and govern the protocol. They currently take a cut of the total transaction fees paid by users (revenue). 

governance

github

twitter

discord

etherscan

website

Blockchains (L1)

Gnosis

# Gnosis Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the daily revenue generated per active user on the Gnosis blockchain. This metric answers the business question: "How much revenue does each active user generate on average per day?" The calculation divides total daily revenue by the number of daily active users, where revenue consists of burned base fees and blob fees, and active users are defined as unique transaction senders.

## 2. Data sources

The ARPU calculation relies on these underlying data sources:
- **Gnosis blockchain transaction records**: Complete transaction data including sender addresses, gas usage, blob gas usage, effective gas prices, and blob gas prices
- **Gnosis blockchain block records**: Block-level data containing base fee per gas, gas used, and block timestamps
- **End-of-day token price feeds**: USD price data for WXDAI token conversion
- **Token metadata**: Decimal precision and address information for the WXDAI token (0xe91d153e0b41518a2ce8dd3d7944fa863463a97d)

## 3. Step-by-step calculation

### Component A: Daily active users calculation
- **Purpose**: Count unique transaction senders per day to determine daily active users
- **Logic**: Extract all Gnosis chain transactions and identify unique `from_address` values for each day. Transaction timestamps are truncated to day boundaries to ensure proper daily aggregation. Users are classified as "Transaction sender" type and tagged with market sector "blockchains_l1" and business segment "blockchain". The system uses HyperLogLog sketching to efficiently count distinct users across multiple dimensions including project level, chain level, user type, and product level breakdowns.
- **Key fields**: `from_address` as the user identifier, `block_timestamp` truncated to day for temporal grouping, `user_dau` as the final distinct user count

### Component B: Base fee revenue calculation  
- **Purpose**: Calculate daily revenue from burned base fees on Gnosis chain
- **Logic**: Extract block-level data including `gas_used` and `base_fee_per_gas` values. Base fee per gas amounts are converted from wei to full units by dividing by 10^18. For each block, multiply `gas_used` by the corrected `base_fee_per_gas` to get the base fee amount. Sum these amounts by day to get daily base fee revenue. All amounts are denominated in WXDAI initially.
- **Key fields**: `gas_used` from block data, `base_fee_per_gas` converted from wei, `base_fee_amount` as the daily sum

### Component C: Blob fee revenue calculation
- **Purpose**: Calculate daily revenue from blob fees on type-3 transactions  
- **Logic**: Filter Gnosis transactions to include only type-3 transactions (blob transactions). For each qualifying transaction, multiply `blob_gas_used` by `blob_gas_price` (converted from wei by dividing by 10^18) to calculate the blob fee amount. Sum these amounts by day to get daily blob fee revenue. All amounts are initially denominated in WXDAI.
- **Key fields**: `blob_gas_used` and `blob_gas_price` from transaction data, `transaction_type` filter for value 3, `blob_fee_amount` as the daily sum

### Final aggregation
- **Combining components**: Base fee revenue and blob fee revenue are combined through a union operation to create total daily revenue. Both components are tagged with the WXDAI token address and appropriate business metadata including "Blockchain" business line, "blockchains_l1" market sector, and "blockchain" business segment.
- **Currency conversion**: WXDAI amounts are converted to USD using end-of-day price feeds through the convert_to_usd_and_correct_decimals macro, with decimal correction disabled since gas prices are already normalized
- **Time aggregation**: All data is aggregated to daily boundaries using timestamp truncation to day level granularity
- **Final calculation**: The ARPU value is calculated by dividing total daily revenue (in USD) by the daily active user count using the calculate_arpu macro, with zeros filled for missing days to maintain time series continuity

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

GnosisGNO

Average revenue per user (ARPU)

Average revenue per user (ARPU)

Competitive landscape