Validators process & store the uploaded data and collect upload & storage fees from data uploaders (supply-side fees).

Swarm is a data storage network built on Gnosis. Swarm was founded by Viktor Tron, Jeffrey Wilcke and Daniel A. Nagy and launched in 2016.

BZZ tokenholders own and govern the protocol. They currently don’t take a cut of the fees paid by data uploaders.

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Swarm

# Swarm Average revenue per user (ARPU) Methodology

## 1. Overview

ARPU measures the average revenue generated per daily active user on the Swarm network. This metric provides insight into revenue efficiency and user monetization. The calculation divides total daily revenue by the number of daily active users. For Swarm, this metric currently results in $0 ARPU as revenue is set to zero in the calculation, while user activity is tracked through interactions with Swarm's PostageStamp contract.

## 2. Data sources

- **Gnosis chain events**: Parsed `BatchCreated` and `BatchTopUp` events from Swarm's PostageStamp contract
- **Token transfer data**: Gnosis chain BZZ token transfer records to identify batch top-up users
- **Price feeds**: End-of-day BZZ token price feeds for USD conversion
- **Token metadata**: BZZ token contract information and decimal precision data

## 3. Step-by-step calculation

### Component A: User identification and classification
- **Purpose**: Identify and categorize daily active users based on their interactions with Swarm's PostageStamp contract
- **Logic**: Extract user addresses from `BatchCreated` events where the user is the batch owner, categorizing them as "Batch Creator" users. For batch top-up users, join `BatchTopUp` events with BZZ token transfer records to identify the sender addresses, categorizing them as "Batch TopUpper" users. Token transfers are filtered to include only transfers to the PostageStamp contract address using the BZZ token. All user interactions are timestamped and associated with the Gnosis chain.
- **Key fields**: `owner` addresses from batch creation events, `from_address` from token transfers, `block_timestamp` for daily aggregation, `user_type` for categorization

### Component B: Daily active user aggregation
- **Purpose**: Count distinct daily active users across different dimensions using efficient aggregation
- **Logic**: Group user interactions by day and count distinct user addresses using HyperLogLog (HLL) algorithm for memory-efficient distinct counting. Create multiple aggregation dimensions including project-level totals, chain-level breakdowns, user-type breakdowns, and product-level breakdowns. Apply chain availability filtering to ensure data quality and completeness.
- **Key fields**: `timestamp` truncated to day, `user_address` for distinct counting, `chain` and `user_type` for dimensional breakdowns

### Component C: Fee extraction and processing
- **Purpose**: Extract fee amounts from PostageStamp contract interactions for potential revenue calculation
- **Logic**: Collect fee amounts from `BatchCreated` events using the `totalAmount` field and from `BatchTopUp` events using the `topupAmount` field. Map these Gnosis chain transactions to Ethereum for price calculation purposes using the Ethereum BZZ token address. Convert amounts to USD using end-of-day price feeds and correct for token decimal precision.
- **Key fields**: `totalAmount` and `topupAmount` for fee values, `token_address` for price lookup, `block_timestamp` for daily aggregation

### Component D: Revenue calculation
- **Purpose**: Calculate daily revenue from fee data (currently set to zero)
- **Logic**: Process the fee data through USD conversion and decimal correction, but override all revenue values to zero in the final revenue calculation step. This results in zero revenue for all days and dimensions.
- **Key fields**: `fees` amounts converted to USD, `timestamp` for daily aggregation, final `revenue` value set to 0

### Final aggregation
- **Combining components**: The ARPU calculation divides the daily revenue (from Component D) by the daily active user count (from Component B) using the `calculate_arpu` macro
- **Currency conversion**: All amounts are converted to USD using end-of-day BZZ token price feeds, though final revenue is zeroed out
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation to day level
- **Final calculation**: ARPU = Daily Revenue ÷ Daily Active Users = $0 ÷ User Count = $0, since revenue is hardcoded to zero in the revenue calculation step. The result is finalized using a fill-zeros strategy to ensure complete time series coverage.

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

SwarmBZZ

Average revenue per user (ARPU)

Average revenue per user (ARPU)

Competitive landscape