Unipilot removes the complexities and costs of providing concentrated liquidity, making liquidity more capital efficient. For projects, this optimization of liquidity enables lower-slippage trading.

Unipilot is a concentrated liquidity manager live on multiple chains and DEXs. Unipilot currently supports Uniswap V3 and QuickSwap V3 across six chains: Ethereum, Polygon, Polygon zkEVM, Arbitrum, BNB Chain and Dogechain. Unipilot is in the Xord.com ecosystem. This dashboard does not take into account Unipilot's transition into A51 Finance.


PILOT tokenholders own and govern the protocol. PILOT stakers earn a share of the total LP fees (revenue).

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Unipilot

# Unipilot Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) for Unipilot measures the number of unique users who interact with Unipilot's yield aggregation vaults over rolling 7-day periods. This metric answers how many distinct users are actively depositing or withdrawing from Unipilot's liquidity management solutions across multiple blockchain networks within any given week. The calculation uses HyperLogLog algorithms to efficiently count unique users across large datasets and provides breakdowns by chain, user type, and product dimensions.

## 2. Data sources

- **Blockchain events**: Parsed `Deposit` and `Withdraw` events from Unipilot's vault contracts across Ethereum, BSC, Polygon, and Arbitrum networks
- **Contract events**: Events from both `UnipilotActiveVault` and `UnipilotPassiveVault` contract types, capturing different vault strategies
- **Transaction data**: Blockchain transaction timestamps and hashes for temporal ordering and deduplication
- **User addresses**: Depositor and recipient addresses extracted from event parameters

## 3. Step-by-step calculation

### Component A: Raw user event extraction
- **Purpose**: Identifies and normalizes all user interactions with Unipilot vaults across supported blockchains
- **Logic**: Extracts user addresses from `Deposit` and `Withdraw` events across four blockchain networks (Ethereum, BSC, Polygon, Arbitrum). For `Deposit` events, captures the `depositor` address and labels them as 'Depositor'. For `Withdraw` events, captures the `recipient` address and labels them as 'Withdrawer'. All events are normalized with consistent chain identifiers and categorized under the asset management market sector and yield aggregator business segment
- **Key fields**: `block_timestamp` for temporal analysis, `transaction_hash` for deduplication, `chain` for network identification, `user_type` for interaction classification, and `user_address` for unique user identification

### Component B: Daily active user aggregation
- **Purpose**: Converts raw events into daily unique user counts using HyperLogLog for efficient distinct counting
- **Logic**: Groups all user events by day using `timestamp_trunc` on the block timestamp. Creates distinct user counts for each combination of date, chain, user type, and product dimensions. Applies a data cutoff before December 28, 2023, and includes chain availability filtering to ensure data quality. Uses HyperLogLog initialization to create probabilistic sketches of daily unique users for efficient downstream processing
- **Key fields**: `timestamp` truncated to day granularity, `user_dau` containing unique user addresses, dimensional breakdown fields including `chain`, `user_type`, and `product_id`

### Component C: Rolling window construction
- **Purpose**: Creates 7-day rolling windows for each date to capture weekly user activity patterns
- **Logic**: Generates a complete datespine covering all dates from the earliest DAU data to yesterday. For each date in the spine, creates a 7-day lookback window by generating an array of timestamps from 6 days prior through the current day. This ensures every day has a complete 7-day window for WAU calculation, even when some intermediate days have no user activity
- **Key fields**: `timestamp` for the target date, `joinday` representing each of the 7 days in the rolling window

### Component D: HyperLogLog window aggregation
- **Purpose**: Merges daily HyperLogLog sketches across the 7-day windows to calculate weekly unique users
- **Logic**: Joins the rolling window structure with daily HLL data, collecting all HLL sketches that fall within each 7-day period. For each target date, retrieves HLL sketches from the current day and the 6 preceding days. Uses HLL merge operations to combine these sketches, which automatically handles user overlap across days to provide accurate weekly unique counts
- **Key fields**: HLL sketches merged across the temporal window, maintaining dimensional breakdowns for chain, user type, and product

### Component E: Dimensional breakdowns
- **Purpose**: Provides multiple analytical perspectives by aggregating WAU across different dimension combinations
- **Logic**: Creates four distinct dimensional views of the WAU data. Project-level aggregation provides overall Unipilot metrics by nulling all dimensional fields. Chain-level breakdown maintains chain identity while nulling user type and product. User type breakdown maintains the depositor/withdrawer classification while nulling other dimensions. Product-level breakdown maintains product identity while nulling other dimensions. Each breakdown uses HLL merge operations to combine sketches appropriately for the target dimension
- **Key fields**: `dimensions` field indicating the breakdown type, selectively nulled dimensional fields based on aggregation level, `user_wau` containing the final unique user count

### Final aggregation
- **Combining components**: All dimensional breakdowns are combined using union operations to create a comprehensive dataset with multiple analytical perspectives in a single table
- **Time aggregation**: Daily boundaries are maintained throughout the calculation, with each record representing WAU for a specific date calculated from the 7-day rolling window ending on that date
- **Schema standardization**: Applied through the `finalize_metric_user_wau` macro which ensures consistent field naming, data types, and includes zero-filling for dates with no user activity
- **Final calculation**: The final WAU value represents the count of unique users who performed any deposit or withdrawal action within the 7-day period ending on each date, calculated using HyperLogLog extraction from the merged sketches

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

Unique revenue-generating users over a rolling 7-day window.

UnipilotPILOT

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown