Index Cooperative offers a range of token-based index products, which could be streamed, issued, and redeemed against a fee (supply-side fees).

Index Cooperative is an asset management protocol built on Ethereum. Index Cooperative was founded by Set Protocol and launched in 2020.

INDEX tokenholders own and govern the protocol. They currently take all of the total streaming fees paid by liquidity providers (revenue).

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Index Cooperative

# Index Cooperative Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of unique users who interact with Index Coop's set token products within any 7-day period. This metric tracks user engagement with Index Coop's asset management protocols by identifying users who mint (issue) or redeem (burn) set tokens across supported blockchain networks. The calculation uses HyperLogLog data structures to efficiently count unique users over rolling 7-day windows, providing insights into protocol adoption and user retention patterns.

## 2. Data sources

- **Ethereum blockchain events**: Parsed `SetTokenIssued` and `SetTokenRedeemed` events from Index Coop's BasicIssuanceModule and DebtIssuanceModule smart contracts on Ethereum network
- **Polygon blockchain events**: Parsed `SetTokenIssued` and `SetTokenRedeemed` events from Index Coop's DebtIssuanceModule smart contracts on Polygon network  
- **Transaction metadata**: Blockchain transaction timestamps and hashes from Ethereum and Polygon networks to establish timing and uniqueness of user interactions
- **Protocol contract data**: SetProtocol v2 smart contract interactions that facilitate set token minting and redemption operations

## 3. Step-by-step calculation

### Component A: User identification and classification
- **Purpose**: Identifies unique users interacting with Index Coop protocols and classifies them by interaction type
- **Logic**: Extracts user addresses from Index Coop protocol events across Ethereum and Polygon chains. Users are identified from `SetTokenIssued` events (where users mint/issue set tokens) and `SetTokenRedeemed` events (where users burn/redeem set tokens). Each interaction captures the user address, transaction timestamp, chain identifier, and interaction type. Users are classified as 'Minter' for those issuing tokens or 'Burner' for those redeeming tokens.
- **Key fields**: User addresses from the `to` parameter (for minting) and `redeemer` parameter (for redemption), `block_timestamp` for timing, `transaction_hash` for uniqueness, and derived `user_type` classification

### Component B: Daily active user aggregation  
- **Purpose**: Aggregates unique users by day to create Daily Active Users (DAU) counts
- **Logic**: Groups the identified users by day using timestamp truncation to daily granularity. For each day, identifies distinct user addresses along with their chain, user type (Minter/Burner), and product classifications. This creates a daily snapshot of unique users who interacted with the protocol on each specific day, serving as the foundation for weekly calculations.
- **Key fields**: Daily `timestamp`, `chain` identifier, `user_type` classification, `product_id`, and unique `user_address` for each day

### Component C: HyperLogLog initialization
- **Purpose**: Converts daily user sets into HyperLogLog data structures for efficient unique counting
- **Logic**: Takes the daily user aggregations and initializes HyperLogLog (HLL) data structures for each day's user set. HLL is a probabilistic algorithm that allows efficient estimation of unique counts in large datasets while using minimal memory. Each day's unique users are converted into an HLL structure that can be efficiently merged with other days to calculate unique users across time periods.
- **Key fields**: Daily `hll` structures containing compressed representations of unique user sets, maintaining groupings by `timestamp`, `chain`, `user_type`, and `product_id`

### Component D: Seven-day rolling window creation
- **Purpose**: Creates 7-day rolling windows for WAU calculation using a datespine approach
- **Logic**: Generates a complete datespine covering all days from the earliest available data to the present day to ensure no days are skipped in the analysis. For each day in the datespine, creates a 7-day window by joining that day with its 6 preceding days (creating a 7-day total window). This approach ensures every day has a complete 7-day lookback period for calculating weekly active users, handling missing data gracefully by including days even if no activity occurred.
- **Key fields**: Window `timestamp` (the end date of each 7-day period), `joinday` dates (the 7 individual days in each window), and associated HLL structures for each day in the window

### Component E: Weekly unique user calculation
- **Purpose**: Calculates unique users across each 7-day window by merging HLL structures
- **Logic**: For each 7-day window, merges the HLL structures from all days within that window to count unique users who were active at any point during those 7 days. The HLL merge operation efficiently combines the daily user sets while avoiding double-counting users who were active on multiple days within the same week. This produces the actual Weekly Active Users count for each day's 7-day lookback period.
- **Key fields**: Weekly `user_wau` counts representing unique users in each 7-day period, maintaining dimensional breakdowns by `timestamp`, `chain`, `user_type`, and `product_id`

### Component F: Multi-dimensional breakdown
- **Purpose**: Provides WAU metrics across different analytical dimensions
- **Logic**: Calculates WAU across four different dimensional breakdowns: project-level (overall protocol WAU), by chain (Ethereum vs Polygon), by user type (Minters vs Burners), and by product (different set token products). Each breakdown aggregates the weekly unique users at the appropriate level while setting non-relevant dimensional fields to null. All breakdowns are then combined using union operations to create a comprehensive dataset.
- **Key fields**: `dimensions` field indicating the breakdown type, relevant dimensional identifiers (chain_id, user_type, product_id), and the calculated `user_wau` value for each combination

### Final aggregation
- **Combining components**: The multi-dimensional breakdown components are combined through union operations, creating a single dataset containing WAU metrics at project, chain, user type, and product levels for each day
- **Time aggregation**: Each record represents the count of unique users who were active within a 7-day window ending on the specified timestamp, providing daily updates of rolling weekly activity
- **Schema finalization**: The results are processed through a standardization macro that applies consistent formatting, fills missing days with zero values where appropriate, and ensures proper data types and field naming conventions across all dimensional breakdowns

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

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

Index CooperativeINDEX

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown