Traders buy NFTs either via the Blur aggregator or Blur's own marketplace from creators & and other users. When trading via Blur's own marketplace, traders pay royalty fees to the creators (supply-side fees).

Blur is a non-custodial NFT marketplace and a marketplace aggregator protocol built on Ethereum. Blur was founded by a pseudonymous team and launched in 2022.

BLUR tokenholders own and govern the protocol. They currently do not take a cut of the royalty fees paid by traders (revenue). Blur's investors include Paradigm, eGirl Capital, etc.

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Blur

# Blur Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the number of unique users who engaged in NFT trading activity on the Blur protocol within a 30-day sliding window. This metric answers the question "How many distinct users traded NFTs on Blur in the past 30 days?" and uses a rolling window approach where each day represents the count of unique users active over the previous 30 days. The calculation employs HyperLogLog probabilistic data structures for efficient computation of unique user counts across large datasets.

## 2. Data sources

The calculation relies on multiple types of blockchain event data and transaction records:

- **Blur v1 exchange events**: Parsed `OrdersMatched` events from the original Blur exchange contract containing trade details, user addresses, NFT collections, and pricing information
- **Blur v2 exchange events**: Parsed execution events including `Execution721TakerFeePacked`, `Execution721MakerFeePacked`, `Execution721Packed`, and `Execution` events from the newer exchange contract with packed data structures
- **Seaport protocol events**: Parsed `OrderFulfilled` events from OpenSea's Seaport protocol versions 1.1 through 1.6, filtered to include only trades where Blur acts as the zone owner
- **Blur Blend lending events**: Parsed function calls for collateral NFT trades including `buyLockedETH`, `buyLocked`, `buyToBorrowLocked`, and `buyToBorrowLockedETH` from the Blend protocol
- **Ethereum transaction data**: Base transaction records providing user addresses, timestamps, and transaction metadata
- **Seaport order matching detection**: Events identifying when multiple orders are matched together in batch transactions to ensure proper trade attribution

## 3. Step-by-step calculation

### Component A: Daily active user extraction
- **Purpose**: Identifies unique users who traded NFTs on any Blur platform each day
- **Logic**: Extracts user addresses from all trade events across Blur v1, v2, Seaport, and Blend protocols. For each completed trade, captures both the NFT seller address and NFT buyer address. Handles special cases like trades through the Blur swap contract by identifying the actual user from the transaction originator. Categorizes users as either "NFT seller" or "NFT buyer" based on their role in each transaction. Groups data by day, chain, user type, and product to create distinct daily user lists.
- **Key fields**: `user_address` (buyer/seller addresses), `timestamp` (truncated to day), `user_type` (seller/buyer), `chain`, `product_id`

### Component B: Trade data parsing and standardization
- **Purpose**: Processes raw blockchain events into standardized trade records with consistent user identification
- **Logic**: Parses complex Blur v2 packed event data using JavaScript functions to extract token IDs, trader addresses, pricing, and fee information from bitwise-encoded values. Standardizes token addresses by converting null addresses and pool addresses to WETH for consistent pricing. Identifies actual user addresses by checking if trades route through intermediary contracts like Blur swap. For Seaport trades, filters to include only those with Blur's zone owner ID and handles both individual and matched order scenarios. Combines royalty and fee information to track complete trade economics.
- **Key fields**: `nft_seller_address`, `nft_buyer_address`, `volume_amount`, `token_address`, `order_hash`, `trade_id`

### Component C: HyperLogLog conversion and windowing
- **Purpose**: Converts daily user lists into probabilistic data structures for efficient 30-day aggregation
- **Logic**: Transforms each day's unique user list into HyperLogLog data structures with 15-bit precision for memory-efficient storage. Creates a datespine covering all days from the earliest trade data to present. For each day, generates a 30-day lookback window including the current day plus previous 29 days. Joins the windowed dates with daily HLL user data to create overlapping 30-day periods for every day.
- **Key fields**: `hll` (HyperLogLog user data), `timestamp` (window end date), `joinday` (days within window)

### Component D: Dimensional breakdown aggregation  
- **Purpose**: Calculates MAU at different granularities for various analysis perspectives
- **Logic**: Aggregates HLL data within each 30-day window across four dimensional breakdowns. Project-level aggregation merges all user activity regardless of chain, product, or user type. Chain-level breakdown maintains separate counts for each blockchain. User type breakdown separates NFT sellers from buyers. Product-level breakdown distinguishes different Blur offerings. Uses HLL merge operations to combine user sets while maintaining uniqueness across the aggregation dimensions.
- **Key fields**: `dimensions` (aggregation level), `chain_id`, `user_type`, `product_id`

### Final aggregation
- **Combining components**: Unions all dimensional breakdowns into a single result set with appropriate null values for non-applicable dimension columns
- **Currency conversion**: Not applicable for user count metrics
- **Time aggregation**: Uses 30-day sliding windows where each day represents unique users active over the trailing 30-day period including that day
- **Final calculation**: Extracts actual user counts from merged HyperLogLog structures using probabilistic estimation, applies project metadata and formatting through the finalization macro, and fills missing days with zero values to ensure continuous time series data

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

Unique revenue-generating users over a rolling 30-day window.

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Active users (monthly)

Active users (monthly)

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