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Blockchains (L1)

XDC Network

# XDC Network Active users (daily) Methodology

## 1. Overview

Daily Active Users (DAU) for XDC measures the number of unique addresses that initiated at least one transaction on the XDC blockchain each day. This metric provides insights into user engagement and network activity by tracking distinct transaction senders across daily time periods. The calculation uses HyperLogLog sketches for memory-efficient distinct counting and provides breakdowns across multiple dimensions including chain, user type, and product classifications.

## 2. Data sources

- **XDC blockchain transactions**: Raw transaction records from the XDC network containing sender addresses, transaction hashes, block timestamps, and transaction metadata
- **Transaction metadata**: Blockchain transaction details including `from_address` fields that identify transaction initiators and `block_timestamp` data for temporal aggregation

## 3. Step-by-step calculation

### Component A: User extraction and classification
- **Purpose**: Extract and classify all transaction senders from XDC blockchain data
- **Logic**: Process raw XDC transaction records and extract the `from_address` field as the user identifier for each transaction. Cast `block_timestamp` to timestamp format and `transaction_hash` and `from_address` to string format. Classify all users uniformly as 'Transaction sender' user type and assign them to the 'xdc' product under the 'blockchains_l1' market sector and 'blockchain' business segment. Every transaction sender is considered a user regardless of transaction type or value.
- **Key fields**: `block_timestamp` for temporal aggregation, `from_address` as the unique user identifier, `transaction_hash` for transaction tracking, and standardized classification fields including `chain` (set to 'xdc'), `user_type` (set to 'Transaction sender'), and `product_id` (set to 'xdc')

### Component B: Daily user aggregation with HyperLogLog
- **Purpose**: Calculate daily distinct active users using probabilistic counting for efficient aggregation
- **Logic**: Group transactions by daily boundaries using `timestamp_trunc` to truncate `block_timestamp` to day granularity. For each day, identify distinct user addresses and store them using HyperLogLog sketches with 15-bit precision for memory-efficient distinct counting. Apply incremental processing filters to only process data from recent months when running incrementally. Each unique `user_address` on a given day contributes to that day's DAU count.
- **Key fields**: `timestamp` (daily boundary), `timestamp_grain` (set to 'day'), `chain`, `user_type`, `product_id`, and `user_dau` (the distinct user address contributing to the daily count)

### Component C: Multi-dimensional aggregation
- **Purpose**: Aggregate DAU across different dimensional breakdowns using HyperLogLog merge operations
- **Logic**: Create separate aggregations for four different dimensional views: project-level DAU (rolling up all dimensions), chain-level DAU (broken down by blockchain), user-type-level DAU (broken down by user classification), and product-level DAU (broken down by product classification). Use HyperLogLog merge operations (`hll_count.merge_partial`) to combine sketches across dimensions while maintaining distinct count accuracy. Extract final counts using `hll_count.extract` to convert sketches back to numeric values.
- **Key fields**: `timestamp`, `timestamp_grain`, `dimensions` (indicating the breakdown type), `chain_id`, `product_id`, `user_type`, and `user_dau` (the final distinct count for each dimensional combination)

### Final aggregation
- **Combining components**: Union all dimensional breakdowns (project, chain, user type, product) into a single result set with consistent schema structure. Each row represents DAU for a specific day and dimensional combination.
- **Schema standardization**: Apply the `finalize_metric_user_dau` macro to standardize the output schema and implement a 'fill_zeros' strategy to populate missing days with zero values, ensuring complete time series data.
- **Chain availability filtering**: Apply chain availability filters to ensure results only include data for periods when the XDC chain was actively monitored and available for analysis.
- **Final calculation**: The final DAU value represents the count of distinct user addresses that initiated at least one transaction on XDC blockchain for each day, aggregated across the specified dimensional breakdown. No currency conversion is needed as this is a count-based metric rather than a value-based metric.

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

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

XDC NetworkXDC

Active users (daily)

Active users (daily)

Competitive landscape