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 Average fees per user (AFPU) Methodology

## 1. Overview

Average Fees Per User (AFPU) for Blur measures the average fee revenue generated per daily active user across all Blur protocol trading activities. This metric answers the question: "How much fee revenue does each active user generate on average per day?" The calculation divides total daily fees by the number of daily active users, providing insight into user monetization efficiency across Blur's NFT marketplace ecosystem.

## 2. Data sources

The calculation utilizes several types of raw blockchain data and external feeds:

- **Blur Exchange v1 events**: Parsed Ethereum `OrdersMatched` events from the Blur Exchange v1 contract containing trade details, buyer/seller addresses, and royalty fee information
- **Blur Exchange v2 events**: Parsed Ethereum execution events from Blur Exchange v2 contract, including packed data structures for trades with maker/taker fee details
- **Seaport marketplace events**: Parsed Ethereum `OrderFulfilled` events from various Seaport contract versions, filtered specifically for trades using Blur's owner ID (`0x0000000000d80cfcb8dfcd8b2c4fd9c813482938`)
- **Blur Blend protocol traces**: Ethereum function call traces from the Blend protocol for NFT collateral trades, including locked NFT purchases
- **Transaction records**: Ethereum transaction data used to identify user addresses when trades involve intermediary contracts
- **End-of-day price feeds**: Token price data for USD conversion of fee amounts
- **Token metadata**: Information about token decimals and addresses for proper amount normalization

## 3. Step-by-step calculation

### Component A: Trade event extraction and parsing
- **Purpose**: Extract all NFT trading activity across Blur's ecosystem
- **Logic**: The system identifies NFT trades from multiple sources. For Blur Exchange v1, it parses `OrdersMatched` events to extract trade details, buyer/seller addresses, and royalty fees from the fee structure. For Blur Exchange v2, it processes execution events that use packed data structures, applying JavaScript user-defined functions to perform bitwise operations on large integers to unpack token IDs, trader addresses, and fee information. For Seaport trades, it processes `OrderFulfilled` events from multiple Seaport contract versions, filtering only those with Blur's specific owner ID to capture Blur-facilitated trades. For Blend protocol, it extracts collateral NFT trades from function call traces involving locked NFT purchases.
- **Key fields**: Extracted fields include `block_timestamp`, `transaction_hash`, `nft_seller_address`, `nft_buyer_address`, `royalty_amount`, `volume_amount`, `token_address`, and `nft_address`

### Component B: User identification and deduplication
- **Purpose**: Identify unique daily active users across all trading activities
- **Logic**: The system extracts user addresses from trade events, creating separate records for NFT sellers and NFT buyers to capture all user activity. When trades involve intermediary contracts like Blur Swap, it traces back to the original transaction sender to identify the actual user. The system then applies HyperLogLog aggregation to efficiently count distinct users, handling cases where the same address may appear as both buyer and seller on the same day. Users are deduplicated across all Blur ecosystem activities to provide an accurate daily active user count.
- **Key fields**: Key identifications include `nft_seller_address`, `nft_buyer_address`, `user_type` (NFT seller or NFT buyer), and deduplicated `user_dau` counts

### Component C: Fee aggregation and normalization
- **Purpose**: Calculate total daily fee revenue from all Blur trading activities
- **Logic**: The system aggregates royalty amounts from all trade types as the fee revenue component. For Blur v1 trades, it calculates royalty fees using the rate and price from the fee structure. For Blur v2 trades, it applies maker and taker fee tiers to calculate fee amounts. For Seaport trades, it identifies fee components from consideration items where recipients differ from buyers and sellers. The system handles token address normalization, replacing null addresses and Blur pool addresses with WETH addresses for consistent processing. All fee amounts are converted to USD using end-of-day price feeds and corrected for token decimals.
- **Key fields**: Core fields include `royalty_amount`, `token_address`, `fees_supply_side` (aggregated fees), and USD-converted values

### Final aggregation
- **Combining components**: The daily active user counts and daily fee totals are combined using the ARPU calculation macro, which performs the division of total fees by total daily active users
- **Currency conversion**: All fee amounts are converted to USD using end-of-day token price feeds, with proper decimal correction applied based on token metadata
- **Time aggregation**: Data is aggregated to daily boundaries using timestamp truncation, with incremental processing handling new data while maintaining historical accuracy
- **Final calculation**: AFPU is calculated as the total daily fees in USD divided by the total number of unique daily active users, where users include anyone who bought or sold NFTs through any Blur protocol component on that day

## Critical guidelines

The methodology ensures data quality through several mechanisms: incremental processing with lookback periods to handle late-arriving data, validation of transaction success status, proper handling of packed data structures in v2 contracts, normalization of token addresses for consistent processing, deduplication of users across multiple roles, and gap filling with zeros for days without trading activity. The calculation captures the complete Blur ecosystem including the main exchange contracts, Seaport integration, and Blend collateral trading to provide a comprehensive view of user monetization.

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

BlurBLUR

Average fees per user (AFPU)

Average fees per user (AFPU)

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