Hop allows users to send tokens from one rollup to another almost immediately without having to wait for the rollup’s challenge period. Liquidity providers deposit funds into Hop AMM pools and receive trading fees from traders (supply-side fees).

Hop is a scalable rollup-to-rollup general token bridge. Hop was co-founded by Christopher Whinfrey and launched in 2021.

HOP tokenholders own and govern the protocol. They currently take a cut of the total transfer fees paid by users (revenue). Hop’s investors include 1confirmation, Infinite Capital, etc.

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Hop Protocol

# Hop Protocol Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the count of unique users who interacted with the Hop bridge protocol within any 30-day rolling window. This metric answers the business question: "How many distinct users are actively using Hop's cross-chain bridge services each month?" The calculation uses HyperLogLog probabilistic counting to efficiently compute distinct user counts across large datasets while maintaining accuracy. The metric is calculated as a rolling 30-day window, meaning each day shows the count of unique users who were active in that day plus the previous 29 days.

## 2. Data sources

The calculation relies on the following raw data sources:

- **Hop bridge events**: Parsed `TransferSent` and `TransferSentToL2` events from Hop protocol bridge contracts across Ethereum, Arbitrum, Optimism, Polygon, and Base networks
- **Bridge contract events**: Token-specific bridge contract events for various assets including DAI, ETH, USDT, WBTC, HOP, MAGIC, RETH, SNX, SUSD, and MATIC
- **Blockchain transaction data**: Transaction timestamps and hashes from the underlying blockchain networks to establish when user interactions occurred
- **Event log data**: Parsed smart contract event logs containing user addresses (recipients) from cross-chain bridge transfer operations

## 3. Step-by-step calculation

### Component A: Daily user extraction
- **Purpose**: Identifies unique user addresses that interacted with Hop bridge contracts on each day
- **Logic**: Extracts user addresses from Hop bridge transfer events across all supported chains and token types. The system identifies users from the `recipient` field in `TransferSent` and `TransferSentToL2` events. Each user interaction is classified as "Trader" user type and categorized under "bridges" market sector and "mint_and_burn" business segment. The data is aggregated by day using timestamp truncation to create daily snapshots of active users grouped by chain, user type, and product dimensions
- **Key fields**: `block_timestamp` for daily grouping, `user_address` for unique user identification, `chain` for network classification, `user_type` for user categorization

### Component B: HyperLogLog sketch creation  
- **Purpose**: Creates efficient probabilistic data structures for counting distinct users across large datasets
- **Logic**: Converts daily user address lists into HyperLogLog sketches with precision parameter 15. These sketches enable efficient merging and counting of distinct users across multiple time periods and dimensions. The sketches are grouped by timestamp, chain, user type, and product to maintain granular tracking while enabling efficient aggregation
- **Key fields**: `timestamp` for time boundaries, `hll` sketch for probabilistic counting, dimensional grouping fields for breakdown categories

### Component C: Rolling window construction
- **Purpose**: Creates 30-day rolling windows for each day to calculate monthly active user counts
- **Logic**: Generates a datespine covering all days from the earliest available data to the current day. For each day in the datespine, creates a 30-day lookback window by generating timestamps for the current day plus the previous 29 days. Joins this window with the daily HLL sketches to collect all user activity within each 30-day period. This ensures complete coverage of user activity without gaps in the time series
- **Key fields**: `timestamp` for window end dates, `joinday` for individual days within each window, `hll` sketches for user counting data

### Component D: Dimensional breakdowns
- **Purpose**: Calculates MAU across different analytical dimensions for flexible reporting
- **Logic**: Creates four separate dimensional views of the MAU data. Project-level breakdown merges all chains and dimensions to show overall protocol MAU. Chain-level breakdown shows MAU for each individual blockchain network. User-type breakdown segments users by their interaction type. Product-level breakdown enables analysis by specific product categories. Each breakdown merges HLL sketches appropriately and extracts final distinct counts
- **Key fields**: `dimensions` for breakdown type identification, `chain_id`, `user_type`, `product_id` for dimensional filtering, `user_mau` for final counts

### Final aggregation
- **Combining components**: The four dimensional breakdowns are combined using union operations to create a comprehensive dataset with multiple analytical perspectives in a single output table
- **Currency conversion**: No currency conversion is applied as this metric counts users rather than financial values
- **Time aggregation**: Each day represents a 30-day rolling window ending on that date, providing continuous monthly snapshots
- **Final calculation**: The exact MAU value for each day and dimension is extracted from merged HyperLogLog sketches using the `hll_count.extract` function applied to `hll_count.merge_partial` of all sketches in the 30-day window, yielding probabilistic distinct user counts with high accuracy

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

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

Hop ProtocolHOP

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown