Stakers deposit funds into Jito and receive a return on investment in the form of staking rewards (supply-side revenue). Note: fee, revenue and supply-side fees currently only include validator tips.

Jito is a non-custodial liquid staking protocol built on Solana. Jito was founded by Zano Sherwani and Lucas Bruder and launched in 2022.

Jito team and investors own and govern the protocol. They currently don’t take a cut of the total return on investment (revenue).

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Jito

# Jito Average revenue per user (ARPU) Methodology

## 1. Overview

Average Revenue Per User (ARPU) measures the average daily revenue generated per active user on the Jito protocol. This metric is calculated by dividing daily revenue by daily active users (DAU). The calculation captures revenue from MEV tips collected by Jito validators and tracks users across liquid staking operations and MEV tipping activities. ARPU helps assess the monetization efficiency and user value generation of Jito's MEV infrastructure and liquid staking services.

## 2. Data sources

- **MEV tips data**: Scraped data from Jito validators containing daily MEV tip amounts, validator tips, and Jito tips
- **Solana native transfers**: On-chain SOL transfer events to specific Jito fee collection accounts
- **JitoSOL token operations**: Parsed Solana `mint` and `burn` events for the JitoSOL liquid staking token
- **Transaction data**: Solana transaction records with signer information for user identification
- **End-of-day price feeds**: Daily SOL/USD price data for revenue conversion
- **Token metadata**: JitoSOL token contract information and decimals

## 3. Step-by-step calculation

### Component A: Fee collection
- **Purpose**: Aggregate all MEV tips collected by Jito across different time periods and data sources
- **Logic**: For dates before 2025, use scraped MEV data containing `validator_tips` and `jito_tips` amounts. For dates from 2025 onward, collect native SOL transfers sent to eight specific Jito fee accounts. Convert amounts from lamports to SOL by dividing by 1e9. Deduplicate scraped data by taking the most recent insertion for each date
- **Key fields**: `validator_tips`, `jito_tips`, `amount` (in lamports), `daily_timestamp`, target fee account addresses

### Component B: Revenue calculation  
- **Purpose**: Convert collected fees into protocol revenue using governance-decided rate
- **Logic**: Apply a 3% rate to total fees starting from March 10, 2025, when the revenue sharing mechanism was fully implemented. Convert SOL amounts to USD using end-of-day price feeds. Sum `validator_tips` and `jito_tips` from scraped data, or aggregate transfer amounts from on-chain data. Fill missing days with zero revenue
- **Key fields**: `fees` (total tips), `revenue` (3% of fees), USD conversion rate, `timestamp`

### Component C: User identification
- **Purpose**: Track daily active users across Jito's different services and user types
- **Logic**: Identify three distinct user types: Depositors who mint JitoSOL tokens through liquid staking, Withdrawers who burn JitoSOL tokens to unstake, and Tippers who send MEV tips to Jito fee accounts. Extract user addresses from transaction signers for each activity type. Exclude Jito's own fee accounts from user counts to avoid counting internal operations. Track users daily based on transaction timestamps truncated to day boundaries
- **Key fields**: `transaction_signer` as user address, `user_type` (Depositor/Withdrawer/Tipper), `block_timestamp`, JitoSOL token address

### Component D: User aggregation
- **Purpose**: Calculate unique daily active users across all Jito services with proper deduplication
- **Logic**: Use HyperLogLog data structure to accurately count unique users who may appear in multiple user types on the same day. Aggregate users across all product types (liquid staking and MEV tips) and user types. Group by daily timestamp to get total unique users per day. Apply chain availability filters and fill missing days with zero users
- **Key fields**: `user_dau` (unique user count), HyperLogLog sketch, `dimensions` (aggregation level)

### Final aggregation
- **Combining components**: Join daily revenue amounts with daily active user counts on the same timestamp. Both metrics are aggregated to daily granularity before combination
- **Currency conversion**: Revenue is converted to USD using end-of-day SOL price feeds, with amounts normalized from lamports to SOL units
- **Time aggregation**: All data is truncated to daily boundaries, with the ARPU calculation performed for each day separately
- **Final calculation**: Divide daily revenue (in USD) by daily active users to produce daily ARPU values. Apply fill-zeros strategy to ensure no gaps in the time series, setting ARPU to zero when either revenue or users are zero

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

JitoJTO

Average revenue per user (ARPU)

Average revenue per user (ARPU)

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