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Blockchains (L2)

Shape

# Shape Active users (daily) Methodology

## 1. Overview

Shape daily active users (DAU) measures the number of unique addresses that initiated at least one transaction on the Shape blockchain network within a given day. This metric provides a fundamental measure of user engagement and adoption on the Shape Layer 2 network by counting distinct transaction senders, reflecting actual blockchain usage rather than passive holdings or token transfers.

## 2. Data sources

The calculation relies on the following raw data sources:

- **Shape blockchain transactions**: Complete transaction records from the Shape Layer 2 network, including transaction metadata, timestamps, sender addresses, and transaction hashes
- **Transaction sender data**: The originating addresses (`from_address`) that initiated transactions on the Shape network
- **Block timestamp data**: Precise timestamps indicating when each transaction was included in a Shape network block

## 3. Step-by-step calculation

### Component A: User identification and standardization
- **Purpose**: Extract and standardize user data from raw Shape blockchain transactions
- **Logic**: Process all transaction records from the Shape network to identify unique users. Each transaction's sender address represents a potential active user. The system extracts the `from_address` field as the primary user identifier and applies data quality measures through safe casting. Metadata is enriched with fixed classifications specific to Shape network operations, including chain identification as 'shape', market sector as 'blockchains_l2' (Layer 2 blockchain), business segment as 'blockchain', and user type as 'Transaction sender'
- **Key fields**: `block_timestamp` for temporal analysis, `transaction_hash` for transaction uniqueness, `from_address` as the user identifier, and `user_address` as the standardized user field

### Component B: Daily user aggregation
- **Purpose**: Count distinct active users per day by aggregating transaction senders
- **Logic**: Transform block-level timestamps to daily boundaries using day-level truncation of `block_timestamp`. Group all users by the truncated daily timestamp and apply distinct counting to eliminate duplicate users within each day. A user who sends multiple transactions on the same day is counted only once for that day. The system includes metadata fields for dimensional analysis and applies incremental processing logic that looks back a configurable number of days to ensure data freshness while maintaining efficiency
- **Key fields**: `timestamp` (daily boundary), `timestamp_grain` set to 'day', `user_dau` containing the distinct user address, and classification fields for analytics segmentation

### Final aggregation
- **Combining components**: The final metric combines the standardized user data with daily aggregation by selecting distinct user addresses grouped by daily timestamp boundaries
- **Currency conversion**: Not applicable for this user count metric
- **Time aggregation**: Daily boundaries are created by truncating block timestamps to day level, ensuring all transactions within a 24-hour period contribute to the same daily count
- **Final calculation**: The daily active user count represents the number of distinct `user_address` values (derived from transaction sender addresses) within each daily time boundary, filtered for chain availability and processed incrementally for operational efficiency

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

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

ShapeSHAPE

Active users (daily)

Active users (daily)

Competitive landscape