Collators aggregate parachain transactions block candidates and producing state transition proofs for validators based on those blocks.

Kilt is digital identity solution powered by Polkadot Relay chain.

KILT holders own and govern the protocol.

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Kilt

# Kilt Active users (daily) Methodology

## 1. Overview

Daily Active Users (DAU) for KILT measures the number of unique addresses that initiated at least one transaction on the KILT parachain within a 24-hour period. This metric provides insight into daily user engagement and network activity on the KILT blockchain ecosystem. The calculation follows a straightforward approach: identify all transaction senders from KILT extrinsics data, then count distinct addresses per day.

## 2. Data sources

The methodology relies on a single primary data source:
- **KILT extrinsics data**: Raw transaction data from the KILT parachain containing all substrate extrinsics (equivalent to Ethereum transactions). Each record includes the transaction sender address (`id` field) and block timestamp for when the transaction was included in a block. KILT operates as a Polkadot parachain using the Substrate framework, where extrinsics represent any state changes or actions initiated by users.

## 3. Step-by-step calculation

### Component A: User activity extraction
- **Purpose**: Extract and standardize user activity data from raw KILT blockchain transactions
- **Logic**: Pull all extrinsics from KILT blockchain data and treat each transaction sender as an active user. Apply data type casting to ensure consistent timestamp and address formatting. Assign standardized metadata including chain identifier, market sector classification, and user type categorization.
- **Key fields**: Extract `block_timestamp` for timing information and `id` field as the user address (transaction sender). Apply consistent metadata: `chain` as 'kilt', `market_sector_id` as 'blockchains_l2', `business_segment_id` as 'blockchain', and `user_type` as 'Transaction sender'.

### Component B: Daily aggregation
- **Purpose**: Aggregate user activity data to calculate daily distinct active users
- **Logic**: Group user activity by day using timestamp truncation to day boundaries. Count distinct user addresses within each day to eliminate duplicate counting of users who made multiple transactions. Apply incremental processing logic to efficiently update recent data without reprocessing the entire dataset.
- **Key fields**: Truncate `block_timestamp` to daily boundaries creating `timestamp` field. Preserve `user_address` for distinct counting as `user_dau`. Maintain dimensional attributes including `chain`, `user_type`, and `product_id`.

### Final aggregation
- **Combining components**: The calculation flows directly from user extraction to daily aggregation without complex joins, as both components operate on the same underlying transaction data
- **Currency conversion**: Not applicable - this metric counts users rather than measuring monetary values
- **Time aggregation**: Daily boundaries are established using timestamp truncation to day granularity, ensuring consistent 24-hour periods aligned with UTC
- **Final calculation**: Count distinct user addresses per day where each unique address that initiated at least one transaction is counted exactly once per day, regardless of the number of transactions they performed

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

Unique revenue-generating users over a fixed 24-hour window.

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Active users (daily)

Active users (daily)

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