Stakers deposit funds into BENQI and receive a return on investment in the form of staking rewards (supply-side fees).

BENQI Liquid Staking is the liquid staking derivative business line of BENQI. BENQI was founded by an international team of software developers and launched in 2021.

BENQI tokenholders own and govern the BENQI protocol, including the BENQI Liquid Staking business line. They currently take a cut of the total staking rewards earned by the protocol (revenue). BENQI's investors include Dragonfly Capital, Mechanism Capital, Spartan, etc.

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BENQI Liquid Staking

# BENQI Liquid Staking Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) for BenQi Liquid Staking measures the number of unique users who interact with the BenQi liquid staking protocol within any 7-day period. This metric answers the business question: "How many distinct users are actively engaging with BenQi's liquid staking services on a weekly basis?" The calculation uses a rolling 7-day window approach, building from daily active user data and employing HyperLogLog algorithms for efficient approximate counting of unique users across multiple dimensional breakdowns.

## 2. Data sources

- **Avalanche blockchain events**: Parsed event logs from the BenQi V1 StakedAvax contract on Avalanche
- **Contract interaction data**: Specifically `Submitted` events (representing deposits) and `Redeem` events (representing withdrawals) from the liquid staking protocol
- **Transaction metadata**: Block timestamps and transaction hashes from Avalanche blockchain records
- **User identification data**: Ethereum-style addresses of users interacting with the protocol

## 3. Step-by-step calculation

### Component A: User interaction extraction
- **Purpose**: Identifies all user interactions with the BenQi liquid staking protocol
- **Logic**: Extracts data from two key contract events on Avalanche: `Submitted` events where users deposit assets for liquid staking (categorized as "Depositor" user type) and `Redeem` events where users withdraw assets (categorized as "Withdrawer" user type). Each interaction captures the user address, transaction hash, block timestamp, and classifies the interaction under the 'liquid_staking' market sector and business segment. The product_id is set to null as this represents protocol-level activity rather than specific product interaction.
- **Key fields**: `block_timestamp` for timing, `user_address` for user identification, `user_type` indicating whether the user is depositing or withdrawing, `chain` identifying Avalanche network

### Component B: Daily active user calculation  
- **Purpose**: Converts raw user interactions into daily unique active user counts
- **Logic**: Groups all user interactions by day using timestamp truncation to daily granularity. Within each day, deduplicates user addresses to ensure each unique user is counted only once regardless of how many transactions they performed. Maintains dimensional attributes including chain, user type, and product information. Applies chain availability filtering to ensure data quality and consistency across the protocol's operational timeline.
- **Key fields**: `timestamp` truncated to day level, `user_dau` containing deduplicated user addresses, dimensional breakdowns by `chain`, `user_type`, and `product_id`

### Component C: HyperLogLog conversion and window creation
- **Purpose**: Converts daily user counts to efficient data structures and creates rolling 7-day windows
- **Logic**: Transforms daily active user data into HyperLogLog sketches using 15-bit precision for memory-efficient approximate counting. Creates a datespine covering all days from the minimum available date to yesterday. For each day in the datespine, generates a 7-day window including that day and the previous 6 days. Joins the daily HLL sketches with each relevant day in the rolling window, ensuring complete coverage even when some days have no activity.
- **Key fields**: `hll` sketches for efficient counting, `timestamp` representing the end date of each 7-day window, dimensional attributes preserved from daily data

### Component D: Dimensional WAU breakdowns
- **Purpose**: Calculates weekly active users across different dimensional cuts
- **Logic**: Creates four separate dimensional breakdowns of weekly active users. For each breakdown, merges HLL sketches across the 7-day window and extracts the approximate unique user count. The breakdowns include: project-level WAU (aggregating all dimensions), chain-level WAU (by individual blockchain), user-type-level WAU (by depositor vs withdrawer), and product-level WAU (by specific products, though currently null for protocol-level metrics). Each breakdown maintains proper dimensional labeling while nullifying irrelevant dimensions.
- **Key fields**: `user_wau` containing the unique weekly active user count, `dimensions` indicating the breakdown type, dimension-specific fields like `chain_id`, `user_type`, `product_id`

### Final aggregation
- **Combining components**: All dimensional breakdowns are combined using union operations to create a comprehensive dataset with multiple perspective views of weekly active users
- **Time aggregation**: Uses rolling 7-day windows where each day's WAU represents unique users active in that day plus the previous 6 days, providing continuous weekly measurements rather than discrete week boundaries
- **Final calculation**: The `user_wau` field contains the HyperLogLog-estimated count of unique users active within each 7-day window, broken down by the specified dimensional perspective (project, chain, user type, or product level)

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

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

BENQI Liquid Staking

Active users (weekly)

Active users (weekly)

Competitive landscape