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Blockchains (L3)

# XAI Active addresses (monthly) Methodology

## 1. Overview

Monthly active addresses measures the number of unique wallet addresses that have sent at least one transaction on the XAI blockchain within a rolling 30-day window. This metric provides insight into user engagement and adoption by tracking distinct transaction senders over time. The calculation uses a rolling window approach where each day's value represents the count of unique addresses that were active as transaction senders within the previous 30 days (including the current day).

## 2. Data sources

- **XAI blockchain transaction records**: Raw transaction data from the XAI blockchain containing transaction metadata including sender addresses, recipient addresses, transaction hashes, block timestamps, gas pricing, and gas consumption data
- **Table modification tracking**: Internal timestamps used for incremental data processing optimization to determine which data requires reprocessing

## 3. Step-by-step calculation

### Component A: Transaction data extraction
- **Purpose**: Extracts and standardizes all transaction records from the XAI blockchain
- **Logic**: Retrieves distinct transaction records from XAI blockchain transaction logs, filtering to include only transactions with block timestamps up to August 22, 2025. Each record includes the `block_timestamp`, `transaction_hash`, `from_address` (sender), `to_address` (recipient), gas pricing data, and gas consumption amounts. The data is categorized with XAI-specific metadata including token address, symbol, and market classification as a Layer 3 blockchain in the blockchain business segment.
- **Key fields**: `from_address` serves as the user identifier, `block_timestamp` provides temporal context, `transaction_hash` ensures transaction uniqueness, and gas-related fields support fee calculations

### Component B: Daily active user identification  
- **Purpose**: Creates daily snapshots of unique transaction senders
- **Logic**: Groups transaction data by day using timestamp truncation to day level granularity. For each day, identifies all distinct `from_address` values that sent transactions, creating a set of daily active users. Each unique sender address is classified as a 'Transaction sender' user type and associated with the XAI chain identifier. The process uses incremental materialization partitioned by day to efficiently process new data.
- **Key fields**: `user_dau` contains the unique sender addresses, `timestamp` represents the day-level aggregation boundary, and `user_type` categorizes the activity type

### Component C: Monthly active user calculation using rolling windows
- **Purpose**: Calculates monthly active users using a 30-day rolling window approach with approximate distinct counting
- **Logic**: Implements a sophisticated rolling window calculation using HyperLogLog probabilistic data structures for memory-efficient distinct counting. First, daily user sets are converted to HyperLogLog sketches with precision parameter 15. A continuous date spine is generated covering the full time range, then each day is joined with the previous 29 days to create 30-day rolling windows. For each window, the HyperLogLog sketches from constituent days are merged using probabilistic union operations, then the final distinct count is extracted. The calculation produces multiple dimensional breakdowns including project-level aggregation, chain-level aggregation, user-type-level aggregation, and product-level aggregation.
- **Key fields**: `user_mau` contains the approximate distinct count of unique users within each 30-day window, `timestamp` represents the end date of each rolling window, and `dimensions` indicates the aggregation level

### Final aggregation
- **Combining components**: The target model selects monthly active user data specifically for 'chain' and 'project_dbt_tag' dimensional breakdowns, filtering to these relevant aggregation levels from the comprehensive MAU calculation
- **Currency conversion**: No currency conversion is applied as this metric counts addresses rather than monetary values
- **Time aggregation**: Uses rolling 30-day windows calculated daily, where each day's value represents distinct users active within the trailing 30-day period including the current day
- **Final calculation**: Renames the `user_mau` field to `active_addresses_monthly` and applies schema standardization through the finalize metric macro, which ensures consistent column naming, data types, and fills any missing days with zero values. The final metric represents the approximate count of unique wallet addresses that sent at least one transaction within each rolling 30-day window.

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

Unique addresses active over a rolling 30-day window.

XAIXAI

Archived

Active addresses (monthly)

Active addresses (monthly)

Competitive landscape

Chain breakdown