Liquidity providers (LPs) deposit funds into Aura Finance and receive a return on investment (supply-side fees).

Aura Finance is an asset management and staking protocol built on Ethereum. Aura Finance was founded by an anonymous team and launched in June 2022.

AURA tokenholders own and govern the protocol. They currently take a cut of the total yield generated (revenue).

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Aura Finance

# Aura Finance Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of unique users who interact with the Aura Finance protocol within any 7-day rolling window. This metric captures user engagement across multiple blockchain networks where Aura Finance operates, providing insight into the protocol's active user base over weekly periods. The calculation uses HyperLogLog data structures to efficiently count distinct users across large datasets while maintaining accuracy.

## 2. Data sources

The calculation relies on the following blockchain data sources:

- **Sidechain events**: Parsed `BoosterLite_Deposited` events from Aura Finance smart contracts deployed on Arbitrum, Base, Gnosis, Optimism, and Polygon networks, capturing user deposit activities
- **Ethereum token transfers**: Parsed `Transfer` events from Ethereum mainnet where tokens are sent to the Aura Finance deposit contract address `0xaf52695e1bb01a16d33d7194c28c42b10e0dbec2`
- **Transaction metadata**: Blockchain transaction records containing timestamps, transaction hashes, and log indices for event ordering and deduplication
- **Chain availability data**: Network-specific availability filters to ensure data quality across different blockchain networks

## 3. Step-by-step calculation

### Component A: User interaction identification

- **Purpose**: Identifies all meaningful user interactions with Aura Finance across supported blockchain networks
- **Logic**: Extracts user addresses from two types of events. On sidechains (Arbitrum, Base, Gnosis, Optimism, Polygon), it captures `BoosterLite_Deposited` events and extracts the `user` parameter as the depositor address. On Ethereum mainnet, it identifies token transfers to the Aura Finance deposit contract by filtering `Transfer` events where the `to_address` matches the deposit contract address. The system excludes transfers from known Balancer fee distributor contracts (`0x26743984e3357efc59f2fd6c1afdc310335a61c9` and `0xd3cf852898b21fc233251427c2dc93d3d604f3bb`) and filters out removed or invalid events
- **Key fields**: Captures `user_address` as the primary identifier, along with `block_timestamp` for temporal analysis, `chain` for network identification, and `user_type` classified as "Depositor"

### Component B: Daily active user aggregation

- **Purpose**: Converts raw user interaction events into daily active user counts
- **Logic**: Groups user interactions by day using timestamp truncation to daily boundaries. For each day, chain, user type, and product combination, it creates a distinct list of user addresses who interacted with the protocol. This creates the foundational daily active user dataset that serves as input for weekly calculations
- **Key fields**: Produces `timestamp` truncated to day, `chain` identifier, `user_type`, `product_id`, and `user_dau` containing the user address for distinct counting

### Component C: HyperLogLog conversion

- **Purpose**: Converts daily user sets into efficient probabilistic data structures for scalable distinct counting
- **Logic**: Transforms the daily active user data into HyperLogLog (HLL) structures using 15-bit precision via the `hll_count.init()` function. This allows efficient storage and merging of user sets across time periods while maintaining counting accuracy. The conversion happens at the daily level, grouped by timestamp, chain, user type, and product dimensions
- **Key fields**: Creates `hll` structures containing the compressed user set data alongside dimensional keys for later aggregation

### Component D: Date spine and rolling window creation

- **Purpose**: Ensures complete date coverage and creates 7-day rolling windows for WAU calculation
- **Logic**: Generates a complete date spine from the earliest data date to yesterday using `generate_timestamp_array()` with daily intervals. For each date in the spine, it creates associations with the current date plus the previous 6 days, effectively building 7-day rolling windows. This ensures that even days with no user activity are included in the calculation and that each WAU value represents a complete 7-day period
- **Key fields**: Creates `timestamp` for the target date and `joinday` for each day within the 7-day window

### Component E: Window aggregation and HLL merging

- **Purpose**: Combines daily HLL structures across 7-day windows to count distinct users
- **Logic**: Joins the rolling window structure with the daily HLL data, matching each window day with its corresponding HLL data. For each target date and dimensional breakdown, it merges all HLL structures from the 7-day window using `hll_count.merge_partial()`, then extracts the final distinct user count using `hll_count.extract()`. This produces separate WAU calculations for different dimensional breakdowns
- **Key fields**: Produces `user_wau` containing the distinct user count for each 7-day window, along with dimensional keys

### Final aggregation

- **Combining components**: The system calculates WAU across four dimensional breakdowns: project-level (all chains combined), chain-level (individual networks), user-type-level (different user classifications), and product-level (specific products within the protocol). Each breakdown uses the same 7-day rolling window logic but aggregates HLL structures at different dimensional levels using union operations to combine all breakdowns into a single result set
- **Currency conversion**: Not applicable for user count metrics
- **Time aggregation**: Uses 7-day rolling windows where each date represents the distinct user count for that date plus the previous 6 days. Daily boundaries are maintained using timestamp truncation to day level
- **Final calculation**: The final WAU value for any given date represents the count of distinct users who interacted with Aura Finance during the 7-day period ending on that date, calculated by merging HyperLogLog structures across the window and extracting the probabilistic distinct count

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

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

Aura FinanceAURA

Archived

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown