website

github

twitter

Blockchains (L1)

XDC Network

# XDC Network Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) for XDC measures the number of unique addresses that initiated at least one transaction on the XDC blockchain within a rolling 7-day window. This metric provides insight into the weekly engagement and adoption of the XDC network by tracking transaction senders as active users. The calculation uses HyperLogLog approximation algorithms for efficient computation across large datasets and multiple dimensional breakdowns.

## 2. Data sources

- **XDC blockchain transaction records**: Raw transaction data from the XDC network containing transaction hashes, timestamps, sender addresses, and other transaction metadata
- **Token Terminal chain availability configuration**: Internal data quality filters that exclude certain time periods or chains from analysis to ensure metric reliability

## 3. Step-by-step calculation

### Component A: User identification and daily aggregation
- **Purpose**: Identifies unique active users on a daily basis from XDC transaction activity
- **Logic**: Extracts all transaction sender addresses from XDC blockchain transaction records. Each transaction sender is classified as a "Transaction sender" user type and mapped to the XDC product within the blockchains L1 market sector. Transaction timestamps are truncated to daily boundaries, and unique user addresses are aggregated per day to create Daily Active Users (DAU). The process applies incremental loading with a lookback period to ensure data freshness while maintaining efficiency.
- **Key fields**: `block_timestamp` (transaction time), `from_address` (transaction sender), `transaction_hash` (unique transaction identifier), `user_address` (active user identifier)

### Component B: HyperLogLog sketch creation  
- **Purpose**: Converts daily user lists into memory-efficient probabilistic data structures for approximate distinct counting
- **Logic**: Transforms the daily active user addresses into HyperLogLog sketches using 15-bit precision. This probabilistic data structure allows for efficient storage and computation of approximate distinct counts across large datasets and time windows. Each daily user list becomes a single HLL sketch that can be efficiently merged with other periods.
- **Key fields**: `hll` (HyperLogLog sketch), `timestamp` (daily boundary), `chain_id` (XDC identifier), `user_type` (Transaction sender), `product_id` (XDC)

### Component C: Date spine and rolling window generation
- **Purpose**: Creates continuous time series and 7-day rolling windows for WAU calculation
- **Logic**: Generates a complete date spine from the earliest available data date to the current date minus one day to ensure comprehensive time coverage without gaps. For each day in the date spine, creates a 7-day rolling window by generating timestamps for the current day plus the 6 previous days. This approach ensures that every day has a complete 7-day lookback period for WAU calculation, even when source data has missing days.
- **Key fields**: `timestamp` (target date), `joinday` (dates within 7-day window)

### Component D: Multi-dimensional WAU aggregation
- **Purpose**: Calculates weekly active users across different analytical dimensions
- **Logic**: Joins the rolling 7-day windows with the daily HLL sketches, grouping by each day and its corresponding 7-day lookback period. Merges the HLL sketches across each 7-day window using HyperLogLog merge operations, then extracts the approximate distinct count to get the final WAU value. Creates separate breakdowns for four dimensions: overall project level (XDC as a whole), chain level (XDC chain), user type level (Transaction senders), and product level (XDC product). Each breakdown nullifies non-relevant dimension fields while preserving the specific dimension being analyzed.
- **Key fields**: `user_wau` (weekly active user count), `dimensions` (breakdown category), `timestamp_grain` (day-level aggregation)

### Final aggregation
- **Combining components**: Unions all dimensional breakdowns (project, chain, user_type, product_id) into a single result set, with each row representing WAU for a specific date and dimension combination
- **Time aggregation**: Uses daily timestamp boundaries with 7-day rolling windows, ensuring each day's WAU represents unique users active in that day plus the 6 preceding days
- **Final calculation**: The final WAU value is the approximate distinct count of user addresses extracted from merged HyperLogLog sketches across the 7-day window, providing an efficient approximation of weekly unique transaction senders on the XDC blockchain

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

Unique revenue-generating users over a rolling 7-day window.

XDC NetworkXDC

Active users (weekly)

Active users (weekly)

Competitive landscape