Auctioneers create auctions on Bounce Finance which users can participate in.

Bounce Finance is a non-custodial auction protocol built on Ethereum and other adjacent blockchains. Bounce Finance was founded by Ryan Fang & Jack Lu and launched in 2020.

AUCTION tokenholders own and govern the protocol. They currently take a cut of the total auction fees paid by auction creators (revenue). Bounce Finance's investors include Coinbase Ventures, Binance Labs, Pantera Capital, etc.

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Infrastructure

Bounce Finance

# Bounce Finance Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the number of distinct users who interacted with Bounce Finance's auction platform within a rolling 30-day period. This metric captures user engagement across Bounce Finance's multi-chain ecosystem by tracking interactions with BounceFixedSwap contracts. The calculation uses HyperLogLog probabilistic data structures to efficiently compute distinct user counts across large datasets and time windows. MAU provides insights into platform adoption, user retention, and cross-chain activity patterns for Bounce Finance's decentralized auction infrastructure.

## 2. Data sources

- **Bounce Finance contract events**: Parsed event logs from BounceFixedSwap smart contracts deployed across Arbitrum, Avalanche, BSC, Ethereum, Fantom, Gnosis, Optimism, and Polygon networks
- **Blockchain transaction data**: Block timestamps and transaction hashes from each supported blockchain network
- **Event types**: Five specific contract events capturing different user interactions: `Created`, `CreatorClaimed`, `UserClaimed`, `Swapped`, and `Reversed` events
- **User addresses**: Sender addresses extracted from contract event logs representing users interacting with the platform
- **Metadata**: Chain identifiers, user interaction types, and product categorization data

## 3. Step-by-step calculation

### Component A: Event extraction and user identification
- **Purpose**: Extract and categorize user interactions from Bounce Finance contract events across all supported blockchains
- **Logic**: Parse BounceFixedSwap contract events from eight blockchain networks, extracting the `sender` address from each event log. Categorize users based on their interaction type: auction creators who create new auctions via `Created` events, creator claimers who claim funds via `CreatorClaimed` events, user claimers who claim tokens via `UserClaimed` events, buyers who purchase tokens via `Swapped` events, and refunders who reverse transactions via `Reversed` events. Include block timestamps and transaction hashes for temporal tracking. Set business metadata including business line as "Auction", market sector as "infrastructure", and business segment as "other"
- **Key fields**: `block_timestamp` for timing, `transaction_hash` for uniqueness, `chain` identifier, `user_type` category, `user_address` for distinct counting

### Component B: Daily active user aggregation
- **Purpose**: Create daily distinct user counts while maintaining dimensional granularity
- **Logic**: Group user interactions by day using timestamp truncation to daily boundaries. Calculate distinct users per day while preserving dimensions for chain, user interaction type, and product categorization. This creates the foundation Daily Active User (DAU) dataset that feeds into the monthly calculation
- **Key fields**: `timestamp` truncated to day, `timestamp_grain` set to "day", `chain`, `user_type`, `product_id`, `user_dau` containing the user address

### Component C: HyperLogLog initialization
- **Purpose**: Convert daily user data into probabilistic sketches for efficient distinct counting across time windows
- **Logic**: Transform the daily user counts into HyperLogLog sketches using precision parameter 15, which provides a good balance between accuracy and memory efficiency. Group by timestamp, chain, user type, and product to maintain dimensional breakdown capability
- **Key fields**: `hll` sketch containing compressed user data, dimensional fields for grouping

### Component D: Rolling window construction  
- **Purpose**: Create 30-day rolling windows for each day to enable MAU calculation
- **Logic**: Generate a datespine covering all relevant dates, then use array functions to create 30-day windows. For each target date, generate an array of the previous 29 days plus the current day. Join this window structure with the daily HLL data to create a comprehensive dataset where each row represents one day within a 30-day window
- **Key fields**: `timestamp` as the target date, `joinday` representing each day within the 30-day window

### Component E: MAU calculation across dimensions
- **Purpose**: Calculate monthly active users across different dimensional breakdowns
- **Logic**: Merge HyperLogLog sketches across each 30-day window and extract the final distinct user count. Create four separate dimensional breakdowns: project-level aggregation combining all users regardless of chain or type, chain-level breakdown showing MAU per blockchain, user type breakdown showing MAU by interaction category, and product-level breakdown. Use HyperLogLog merge operations to combine sketches from multiple days within each window
- **Key fields**: `user_mau` containing the final distinct user count, `dimensions` indicating the breakdown type

### Final aggregation
- **Combining components**: Union all four dimensional breakdowns (project-level, chain-level, user-type-level, product-level) into a single result set with standardized schema
- **Currency conversion**: Not applicable for user counting metrics
- **Time aggregation**: Each row represents a single day with MAU calculated as a 30-day rolling window ending on that date
- **Final calculation**: The `user_mau` field contains the approximate distinct count of users who interacted with Bounce Finance within the 30-day period ending on the given timestamp, calculated using HyperLogLog probabilistic counting with merge operations across daily sketches

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

Unique revenue-generating users over a rolling 30-day window.

Bounce FinanceAUCTION

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown