Liquidity providers deposit funds into Balancer and receive trading fees from traders (supply-side fees). In addition, Balancer provides liquidity providers with additional yield using boosted pools.

Balancer is a non-custodial exchange protocol built on Ethereum. Balancer was founded by Fernando Martinelli and launched in 2018.

BAL tokenholders own and govern the protocol. They currently take a cut of the total trading and yield fees (revenue). Balancer's investors include DeFiance Capital, Three Arrows Capital, Alameda Research, etc.

governance

github

twitter

discord

etherscan

website

Exchanges (DEX)

Balancer

# Balancer Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of unique users who interact with Balancer v2 protocol within any 7-day period. This metric captures both trading activity and flash loan usage across multiple blockchain networks, providing insight into user engagement and protocol adoption. The calculation uses HyperLogLog functions to efficiently aggregate unique users across rolling 7-day windows, with results broken down by project, chain, user type, and product dimensions.

## 2. Data sources

The metric relies on the following raw data sources:
- **Balancer v2 Vault contract events**: Parsed `Swap` events from Balancer v2 Vault contracts across Arbitrum, Avalanche, Base, Ethereum, Gnosis, Optimism, and Polygon networks
- **Balancer v2 FlashLoan events**: Parsed `FlashLoan` events from Balancer v2 Vault contracts across the same seven blockchain networks  
- **Transaction data**: Native blockchain transaction records from all seven supported chains, used to identify the actual user addresses (from_address) initiating each interaction
- **Chain metadata**: Network-specific information for classifying activities by blockchain

## 3. Step-by-step calculation

### Component A: Trade activity extraction
- **Purpose**: Identifies unique users performing token swaps on Balancer v2 pools
- **Logic**: Processes parsed `Swap` events from Balancer v2 Vault contracts across seven chains. Filters out liquidity provision and withdrawal activities by ensuring both `tokenIn` and `tokenOut` addresses differ from the pool address (extracted from `poolId`). Each swap event is joined with transaction data to retrieve the `user_address` from the transaction's `from_address` field. Activities are classified as 'Exchange AMM' business line with 'dex' business segment and 'exchanges' market sector
- **Key fields**: `user_address`, `block_timestamp`, `chain`, `tokenIn`, `tokenOut`, `poolId`, `transaction_hash`

### Component B: Flash loan activity extraction  
- **Purpose**: Identifies unique users utilizing Balancer v2 flash loan functionality
- **Logic**: Processes parsed `FlashLoan` events from Balancer v2 Vault contracts across seven chains. These events are emitted directly from the Vault contract when users take flash loans. Each event is joined with transaction data to identify the `user_address` from the `from_address` field. Flash loan users are classified separately as 'Flashloan Trader' user type under the same business categories as traders
- **Key fields**: `user_address`, `block_timestamp`, `chain`, `token`, `amount`, `feeAmount`, `transaction_hash`

### Component C: Daily user aggregation
- **Purpose**: Combines trading and flash loan users into daily active user counts
- **Logic**: Unions traders and flash loan users into a single dataset, truncating `block_timestamp` to day boundaries using timestamp truncation. Each user is classified by `chain`, `user_type` (either 'Trader' or 'Flashloan Trader'), `market_sector_id`, `business_segment_id`, and `product_id`. Excludes Optimism chain data as those users are attributed to Beethoven X protocol. Applies HyperLogLog initialization to prepare for efficient distinct counting
- **Key fields**: `timestamp` (daily), `user_address`, `chain`, `user_type`, `product_id`

### Component D: Rolling window creation
- **Purpose**: Establishes 7-day rolling windows for weekly active user calculation
- **Logic**: Creates a datespine covering all days from the earliest data through current date minus one day. For each date in the datespine, generates a 7-day array including the current day and six preceding days using timestamp array generation. This creates join relationships between each date and its corresponding 7-day window period
- **Key fields**: `timestamp` (target date), `joinday` (dates within the 7-day window)

### Final aggregation
- **Combining components**: Daily HLL sketches are merged across 7-day rolling windows using HyperLogLog merge functions, which efficiently combine unique user counts without double-counting users who were active on multiple days within the window
- **Dimensional breakdowns**: Results are calculated across four separate dimensions: (1) project-level aggregation across all chains and user types, (2) chain-level breakdown maintaining chain separation, (3) user type breakdown separating traders from flash loan users, and (4) product-level breakdown when product classifications exist
- **Time aggregation**: Each day represents the count of unique users active within that day's 7-day trailing window, ensuring consistent weekly periods without gaps
- **Final calculation**: HyperLogLog sketches are extracted to produce final unique user counts, with the finalize_metric_user_wau macro standardizing output format and filling missing days with zero values where no activity occurred

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

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

BalancerBAL

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown