Collators aggregate parachain transactions block candidates and producing state transition proofs for validators based on those blocks.

Bifrost is the Staking Yield Layer app-chain for stablecoins, RWAs, and DeFi, powered by the Polkadot Relay chain.

BNC holders own and govern the protocol. Bifrost’s investors include OKX Ventures, Long Hash Ventures, etc.

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Bifrost

# Bifrost Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the average daily revenue generated per active user on the Bifrost network. This metric is calculated by dividing total daily revenue by the number of daily active users. ARPU provides insight into the monetization efficiency of Bifrost's liquid staking and stable swap services, helping assess the economic value generated per user across the protocol's various revenue streams.

## 2. Data sources

- **Bifrost Substrate events**: Parsed blockchain events containing fee collection data from various protocol modules including `vtokenMinting`, `channelCommission`, `systemStaking`, `stableAsset`, `slp`, and `transactionPayment`
- **Bifrost EVM events**: Ethereum execution events from the EVM compatibility layer for cross-chain user activity
- **Substrate extrinsics**: Transaction records from users interacting with Bifrost's native Substrate chain
- **End-of-day price feeds**: CoinGecko price data for USD conversion of native tokens and supported assets
- **Token metadata**: Hardcoded definitions mapping token symbols, decimals, and CoinGecko IDs for supported assets including DOT, GLMR, ASTR, FIL, MANTA, and BNC along with their corresponding vToken equivalents
- **vToken price ratios**: Exchange rates between vTokens and their underlying assets derived from minting event data

## 3. Step-by-step calculation

### Component A: Daily active user calculation
- **Purpose**: Count distinct users who interact with Bifrost services daily
- **Logic**: Extract user addresses from two sources - Substrate extrinsic senders and EVM transaction executors. For Substrate chain activity, users are identified as the `id` field from extrinsics. For EVM activity, users are extracted from `Executed` events in the `ethereum` pallet using JSON parsing of event data. Users are aggregated using HyperLogLog algorithms to handle distinct counting across different dimensional breakdowns including chain level, user type, and product level
- **Key fields**: User addresses (`user_address`), transaction timestamps (`block_timestamp`), chain identifiers, and user classification as "Transaction sender"

### Component B: Application fee collection
- **Purpose**: Capture revenue from Bifrost's core services including liquid staking and stable swaps
- **Logic**: Process multiple fee types from Substrate events. vToken commission fees are extracted from `slp` pallet `HostingFeeCharged` events. Channel commissions come from `channelCommission` pallet events. System staking payouts are captured from `systemStaking` pallet `Payout` events. Stable swap fees are collected from `stableAsset` pallet `FeeCollected` events. Redemption fees are extracted from `vtokenMinting` pallet `Redeemed` events. Each event's fee amount is parsed from JSON-encoded event data arrays using specific offset positions. Currency information is extracted using regex patterns to parse nested JSON structures containing currency keys and indices
- **Key fields**: Fee amounts (`fees`), currency metadata (currency keys and indices), transaction identifiers (`extrinsic_id`), and timestamps

### Component C: Transaction fee collection
- **Purpose**: Capture basic network usage fees from chain operations
- **Logic**: Extract transaction fees and tips from `transactionPayment` pallet `TransactionFeePaid` events. Parse fee amounts and tips from JSON event data arrays, then sum them to get total transaction cost. Normalize amounts by dividing by 10^12 for BNC token decimal handling
- **Key fields**: Transaction fees (`transaction_fee`), tips (`transaction_tip`), and extrinsic identifiers

### Component D: Fee normalization and conversion
- **Purpose**: Standardize fee amounts across different tokens and convert to USD
- **Logic**: Join fee data with token mapping definitions to get decimal precision and CoinGecko identifiers. Normalize raw fee amounts by dividing by 10^(token decimals). For vToken fees, apply additional conversion using price ratios from minting events to convert vToken amounts to underlying asset equivalents. The price ratios are calculated daily by averaging the token-to-vToken exchange rates from `Minted` events. Apply USD conversion using end-of-day CoinGecko price feeds matched by timestamp and token identifier
- **Key fields**: Normalized fee amounts (`fees`), token identifiers (`coingecko_id`), decimal adjustments, and price conversion ratios (`vtoken_price_ratio`)

### Component E: Revenue aggregation
- **Purpose**: Combine all revenue sources into daily totals
- **Logic**: Union transaction fees from chain operations with application fees from liquid staking and stable swap services. Transaction fees are attributed to the "Bifrost Substrate" product with BNC token pricing. Application fees are categorized into "Bifrost Liquid Staking" for staking-related fees and "Bifrost Stable Swaps" for swap fees. Special handling multiplies vToken commission fees by 10 to account for protocol-specific fee structures. Aggregate fees by timestamp, chain, and product to create daily revenue totals
- **Key fields**: Daily revenue amounts (`revenue`), product classifications (`product_id`), and chain identifiers (`chain_id`)

### Final aggregation
- **Combining components**: Revenue totals are joined with daily active user counts using timestamp as the common dimension. Both metrics are aggregated to daily boundaries using timestamp truncation to day level
- **Currency conversion**: All fees are converted to USD using end-of-day CoinGecko price feeds with appropriate token matching via `coingecko_id` fields. vToken fees undergo two-step conversion - first to underlying assets using minting ratios, then to USD using standard price feeds
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation. Missing days are filled with zero values to ensure consistent time series data
- **Final calculation**: ARPU is computed by dividing total daily revenue in USD by the count of daily active users. The calculation uses the `calculate_arpu` macro which performs the division and handles edge cases where user counts might be zero or null

*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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