# Worldcoin Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the number of unique users who interacted with the Worldcoin ecosystem within a 30-day rolling window. This metric combines users from two distinct sources: wallet creators on Optimism (users who created Worldcoin wallets) and transaction senders on Worldchain (users who submitted transactions). The calculation uses HyperLogLog probabilistic data structures to efficiently count distinct users across multiple dimensions and time periods.

## 2. Data sources

The calculation relies on the following raw blockchain data sources:

- **Optimism event logs**: Specifically `SafeSetup` events (topic hash `0x141df868a6331af528e38c83b7aa03edc19be66e37ae67f9285bf4f8e3c6a1a8`) emitted by Worldcoin wallet contracts during wallet creation
- **Optimism transaction records**: Transaction data used to validate wallet creation events, filtered to only include transactions from whitelisted wallet creator addresses
- **Worldchain transaction records**: All successful transactions on the Worldchain network, used to identify active transaction senders
- **Hardcoded wallet creator addresses**: A predefined list of 24 addresses that are authorized to create Worldcoin wallets, used for filtering legitimate wallet creation activities

## 3. Step-by-step calculation

### Component A: Daily active user identification

- **Purpose**: Identify unique daily active users from both Optimism wallet creation and Worldchain transaction activity
- **Logic**: The calculation combines users from two distinct sources. For Optimism, it identifies wallet creators by finding `SafeSetup` events in event logs, then validates these events by ensuring the transaction hash matches a transaction sent from one of the whitelisted wallet creator addresses. For Worldchain, it identifies all unique transaction senders from successful transactions. Each user is classified with a user type ('Wallet creator' for Optimism, 'Transaction sender' for Worldchain) and associated metadata including chain, market sector, and business segment
- **Key fields**: The process captures `block_timestamp` for daily aggregation, `user_address` for distinct user identification, `user_type` for classification, `chain` for chain identification, and transaction validation fields like `transaction_hash` and `receipt_status`

### Component B: HyperLogLog preparation and daily aggregation

- **Purpose**: Convert daily user addresses into HyperLogLog sketches for efficient distinct counting and aggregate by day
- **Logic**: The system takes the daily active users and groups them by day (using timestamp truncation), chain, user type, and product ID. For each group, it creates HyperLogLog sketches from the user addresses using a precision parameter of 15 bits. This probabilistic approach allows efficient storage and merging of large sets of distinct values while maintaining accuracy
- **Key fields**: Key fields include `timestamp` (truncated to day), `timestamp_grain` (set to 'day'), `chain`, `user_type`, `product_id`, and `hll` (the HyperLogLog sketch of user addresses)

### Component C: 30-day rolling window creation

- **Purpose**: Generate a complete datespine and create 30-day lookback windows for MAU calculation
- **Logic**: The system first creates a datespine covering all days from the earliest DAU date to yesterday, ensuring no missing timestamps. For each date in the datespine, it generates a 30-day lookback window by creating an array of dates from 29 days prior to the current date. This approach ensures that every day has a complete 30-day window for MAU calculation, even if some days within the window have no user activity
- **Key fields**: The process uses `timestamp` for the main date and `joinday` for each day in the 30-day lookback window

### Component D: Window aggregation and HLL merging

- **Purpose**: Merge HyperLogLog sketches across the 30-day windows to calculate monthly active users
- **Logic**: For each date, the system joins the 30-day window dates with the daily HLL sketches, collecting all HLL sketches that fall within each 30-day period. It then merges these HLL sketches using HyperLogLog merge operations and extracts the final distinct count estimate. This provides an efficient way to calculate rolling 30-day unique user counts without having to store and deduplicate individual user addresses
- **Key fields**: The aggregation maintains `timestamp`, `timestamp_grain`, `chain_id`, `user_type`, `product_id`, and produces the merged `hll` sketches

### Component E: Multi-dimensional breakdown

- **Purpose**: Calculate MAU across different analytical dimensions for flexible reporting
- **Logic**: The system creates four separate breakdowns of the MAU data. The project-level breakdown aggregates all users regardless of chain, user type, or product. The chain-level breakdown maintains chain separation while aggregating across user types and products. The user-type breakdown separates wallet creators from transaction senders while aggregating across chains and products. The product-level breakdown maintains product separation while aggregating other dimensions. Each breakdown nullifies non-relevant dimension fields and applies HLL merge operations followed by count extraction
- **Key fields**: Each breakdown maintains relevant dimension fields (`chain_id`, `user_type`, `product_id`) while setting others to null, and produces `user_mau` as the final distinct user count

### Final aggregation

- **Combining components**: All dimensional breakdowns are combined using union operations, creating a unified dataset with different aggregation levels identified by the `dimensions` field
- **Currency conversion**: No currency conversion is applied as this metric counts users rather than monetary values
- **Time aggregation**: The metric uses daily timestamps with 30-day rolling windows, providing daily MAU values that represent the unique user count over the preceding 30 days
- **Final calculation**: The final MAU value for each day represents the distinct count of users who were active at any point during the 30-day window ending on that date, calculated using HyperLogLog probabilistic counting for efficiency and accuracy across large user sets

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

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

Active users (monthly)

Worldcoin

Users sign up for World ID by visiting a Worldcoin Operator and verifying their unique personhood at an Orb. The Orb uses iris biometrics to establish an individual’s unique personhood and then creates a digital World ID, which is stored on the users device using a compatible identity wallet. World App is built on top of Safe's smart contract accounts and also serves as an identity wallet.

Worldcoin is an open source protocol primarily consisting of World ID - a privacy-preserving digital identity and World App - a fully self custodial wallet. Worldcoin was founded by Sam Altman, Alex Blania and Max Novendstern and publicly launched in July 2023.

Worldcoin is currently governed by the Worldcoin Foundation, but intends to decentralize governance over time. Worldcoin's investors include a16z, Multicoin Capital, 1confirmation, CoinFund etc.

WorldcoinWLD

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown