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Dolomite

# Dolomite Active users (daily) Methodology

## 1. Overview

Daily Active Users (DAU) measures the number of unique addresses that interact with Dolomite's margin trading protocol on any given day. The metric captures all forms of user engagement including deposits, withdrawals, trading, transfers, and liquidations across multiple blockchain networks. This provides insight into the daily user engagement and adoption of Dolomite's lending and margin trading services.

## 2. Data sources

The calculation relies on the following blockchain data sources:

- **Smart contract event logs**: Parsed event logs from DolomiteMargin contracts deployed on Arbitrum, Base, Ink, Berachain, and Ethereum networks
- **Deposit events**: `LogDeposit` events containing user deposit activities with `accountOwner` addresses
- **Withdrawal events**: `LogWithdraw` events containing user withdrawal activities with `accountOwner` addresses  
- **Trading events**: `LogSell`, `LogBuy`, and `LogTrade` events capturing trading activities with various user address parameters
- **Transfer events**: `LogTransfer` events for margin position transfers with `accountOneOwner` addresses
- **Liquidation events**: `LogLiquidate` and `LogVaporize` events capturing liquidation activities with `solidAccountOwner` addresses
- **Transaction metadata**: Block timestamps and transaction hashes for temporal context

## 3. Step-by-step calculation

### Component A: User interaction collection
- **Purpose**: Aggregate all user interactions with Dolomite's margin trading protocol across multiple chains
- **Logic**: Collect parsed event logs from DolomiteMargin smart contracts on Arbitrum, Base, Ink, Berachain, and Ethereum. Each event type represents a different user interaction: deposits, withdrawals, sells, buys, trades, transfers, liquidations, and vaporizations. The system extracts the relevant user address from different event parameters depending on the event type - `accountOwner` for deposits and withdrawals, `takerAccountOwner` for trades, `accountOneOwner` for transfers, and `solidAccountOwner` for liquidations
- **Key fields**: Extract `block_timestamp` for temporal analysis, `transaction_hash` for transaction identification, `chain` identifier, and the appropriate user address field based on event type. Each interaction is classified with a `user_type` (Depositor, Withdrawer, Trader, Margin User, or Liquidator) and assigned to the lending market sector

### Component B: Daily user deduplication  
- **Purpose**: Calculate unique active users per day by removing duplicate addresses
- **Logic**: Truncate all block timestamps to day-level granularity using daily boundary logic. For each day, select distinct user addresses to ensure each unique address is counted only once per day, regardless of how many transactions they performed. This creates a daily snapshot of unique active users
- **Key fields**: Daily truncated `timestamp`, `chain` identifier, `user_type` classification, `product_id` (set to null), and deduplicated `user_address` as the `user_dau` metric

### Final aggregation
- **Combining components**: The daily user deduplication component directly processes the output from user interaction collection, maintaining the chain, user type, and temporal dimensions
- **Currency conversion**: No currency conversion required as this is a count-based metric
- **Time aggregation**: Block timestamps are truncated to daily boundaries, creating daily snapshots of unique user activity
- **Final calculation**: The metric represents the count of distinct user addresses that performed any qualifying interaction with Dolomite's protocol on each day, segmented by chain and user activity type. Chain availability filtering ensures data quality by excluding periods where data may be incomplete or unreliable.

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

Unique revenue-generating users over a fixed 24-hour window.

DolomiteDOLO

Active users (daily)

Active users (daily)

Competitive landscape

Chain breakdown