# Scroll Active addresses (daily) Methodology

## 1. Overview

The Scroll active addresses daily metric measures the number of unique addresses that initiated at least one transaction on the Scroll blockchain each day. This metric serves as a key indicator of blockchain adoption and user engagement by tracking distinct daily active users. The calculation uses HyperLogLog probabilistic counting for efficient processing of large transaction datasets and provides dimensional breakdowns at both chain and project levels.

## 2. Data sources

- **Scroll blockchain transaction records**: Complete transaction logs from the Scroll Layer 2 blockchain containing sender addresses, transaction hashes, and block timestamps
- **Chain availability configuration**: Metadata defining valid data periods and handling chain downtime or maintenance windows

## 3. Step-by-step calculation

### Component A: User identification and classification
- **Purpose**: Extract and classify unique user addresses from Scroll blockchain transactions
- **Logic**: Process all Scroll transaction records to identify transaction senders as blockchain users. Each `from_address` field represents a user initiating a transaction. Users are classified with standardized metadata including chain identifier ('scroll'), market sector ('blockchains_l2'), business segment ('blockchain'), and user type ('Transaction sender'). The `product_id` field is set to null as this metric tracks chain-level activity rather than specific application usage.
- **Key fields**: `from_address` becomes `user_address`, `block_timestamp` for timing, `transaction_hash` for deduplication

### Component B: Daily user aggregation with probabilistic counting
- **Purpose**: Calculate daily distinct active users using HyperLogLog sketching for efficient large-scale counting
- **Logic**: Truncate all transaction timestamps to daily boundaries using day-level time truncation. Create distinct records for each unique combination of day, user address, and metadata fields. Initialize HyperLogLog sketches for each user address to enable probabilistic distinct counting. This approach allows efficient processing of millions of daily transactions while maintaining accuracy for distinct count calculations.
- **Key fields**: `timestamp` truncated to day boundaries, `user_address` as the distinct counting target, HyperLogLog sketches for aggregation

### Component C: Dimensional breakdown aggregation  
- **Purpose**: Create multiple dimensional views of daily active users for different analysis perspectives
- **Logic**: Group HyperLogLog sketches by timestamp and merge them across different dimensional breakdowns. Generate four distinct dimensional views: project-level aggregation (combining all Scroll activity), chain-level aggregation (Scroll-specific), user-type-level aggregation (transaction senders), and product-level aggregation (null for chain-level metrics). Use HyperLogLog merge operations to combine sketches and extract final distinct user counts. Each dimensional breakdown maintains separate grouping keys while preserving the underlying distinct user count accuracy.
- **Key fields**: `dimensions` field indicating breakdown type, `chain_id` for chain-specific views, `user_dau` containing extracted distinct counts

### Final aggregation
- **Combining components**: Filter the dimensional breakdown results to include only 'chain' and 'project_dbt_tag' dimensions, as these represent the relevant scopes for active addresses calculation. The `user_dau` field is renamed to `active_addresses_daily` to match the specific metric definition.
- **Currency conversion**: Not applicable - this metric counts addresses rather than monetary values
- **Time aggregation**: Daily boundaries are established through day-level timestamp truncation, with each day representing a complete 24-hour period in the blockchain's native timezone
- **Final calculation**: Extract distinct address counts from merged HyperLogLog sketches for each day and dimensional combination. Apply standardization through the finalize metric macro to ensure consistent schema structure and fill any missing days with zero values. Apply chain availability filters to exclude periods when the Scroll blockchain was not operational or data was unavailable.

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

Unique active addresses over a fixed 24-hour window.

Active addresses (daily)

Scroll

Scroll batches users' transactions and submits them to Ethereum, paying a share of the transaction fees to Ethereum validators (expense).

Scroll is an L2 smart contract platform for decentralized applications on Ethereum. Scroll was founded by Sandy Peng, Haichen Shen, and Ye Zhang and launched in 2023.

SCR tokenholders own and govern the protocol. Scroll's investors include Polychain, Qiming Venture Partners, etc.

ScrollSCR

Active addresses (daily)

Active addresses (daily)

Competitive landscape

Chain breakdown