Liquidity providers deposit funds into DODO and receive trading fees from traders (supply-side fees).

DODO is a non-custodial exchange protocol built on Ethereum and other blockchains. DODO launched in 2020.

DODO tokenholders own and govern the protocol. They currently take a cut of the total trading fees paid by traders (revenue). DODO's investors include Pantera Capital, Three Arrows Capital, Binance Labs, etc.

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DODO

# DODO Average fees per user (AFPU) Methodology

## 1. Overview

Average fees per user (AFPU) measures the average trading fees generated per daily active user on the DODO decentralized exchange. This metric provides insights into user monetization efficiency by dividing total daily trading fees by the number of unique daily active users. The calculation incorporates trading activity across all supported DODO versions (v1 and v2) and chains (Ethereum, BSC, Polygon, Arbitrum, Optimism, Avalanche, Base), accounting for dynamic fee structures and multi-token trading pairs.

## 2. Data sources

- **DODO smart contract events**: Parsed trading events including v1 `BuyBaseToken` and `SellBaseToken` events, and v2 `DODOSwap` events from VendingMachine, StablePool, and PrivatePool contracts across all supported chains
- **Blockchain transaction data**: Transaction records from supported chains to identify user addresses through transaction senders
- **Factory contract functions**: DODO factory contract function calls for pool creation and initial fee tier configuration
- **Fee management events**: Contract events and functions tracking liquidity provider and maintainer fee tier updates
- **Token metadata**: Token information including decimal places and symbols for proper amount calculation and trading pair identification
- **End-of-day price feeds**: Daily token price data in USD for volume conversion and manipulation protection
- **Contract deployment data**: Information about DODO contract addresses and their associated token pairs

## 3. Step-by-step calculation

### Component A: Trade data collection
- **Purpose**: Aggregate all DODO trading activity across supported chains and versions
- **Logic**: Collect trading events from DODO v1 contracts capturing `BuyBaseToken` and `SellBaseToken` events with `receiveBase`, `payQuote`, `payBase`, and `receiveQuote` amounts. For v2 contracts, capture `DODOSwap` events from VendingMachine, StablePool, and PrivatePool contracts with `fromAmount` and `toAmount` values. Join each trade event with blockchain transaction data to identify the user address from the transaction sender (`from_address` field). Combine trades with trading pair metadata to map contract addresses to their underlying token pairs and obtain decimal information for proper amount calculation.
- **Key fields**: `user_address` from transaction sender, `token0_amount` and `token1_amount` from trade events, contract `address` for trading pair identification, `block_timestamp` for daily aggregation

### Component B: Fee tier management
- **Purpose**: Track and apply appropriate trading fees based on dynamic fee structures
- **Logic**: Collect fee tier updates from DODO contract functions during pool creation and fee update events. Combine liquidity provider fees and maintainer fees from contract events like `UpdateLiquidityProviderFeeRate` and `UpdateMaintainerFeeRate`. Convert fee rates from basis points by dividing by 10^18. Forward-fill fee tiers daily for consistent application, with special handling for days when fees change multiple times by tracking updates at block-level granularity. Match each trade to the appropriate fee tier based on transaction timing, ensuring trades use the fee rate that was active at the time of execution.
- **Key fields**: `fee_tier` as combined LP and maintainer fees, `block_timestamp` for temporal matching, `account_address` for pool-specific fees

### Component C: Trading volume calculation  
- **Purpose**: Convert raw trade amounts to standardized USD trading volumes
- **Logic**: Correct token amounts by dividing raw values by the token's decimal places (typically 10^18 for most tokens). Convert both tokens in each trading pair to USD using end-of-day price feeds. Apply manipulation protection by taking the minimum USD value between the two tokens to prevent inflated volumes from price disparities. Calculate fees by multiplying the standardized trading volume by the applicable fee tier for each trade. Aggregate results daily by summing all trading fees across pools and chains.
- **Key fields**: Corrected `token0_amount` and `token1_amount`, `token0_price_usd` and `token1_price_usd`, calculated `trading_volume` as minimum USD value, `fees` as volume × fee tier

### Component D: Daily active users calculation
- **Purpose**: Count unique users engaging with DODO protocols daily
- **Logic**: Identify distinct user addresses from trade transactions daily across all supported chains and DODO versions. Classify all users as 'Trader' type since they are derived from trading activity. Use HyperLogLog data structures for efficient distinct counting across different dimensional breakdowns including project-level, chain-level, user-type, and product-level aggregations. Apply chain availability filtering to ensure only supported networks are included in the count.
- **Key fields**: `user_address` as unique identifier, `timestamp` truncated to daily granularity, `user_type` set to 'Trader'

### Final aggregation
- **Combining components**: Sum total daily trading fees across all DODO pools, chains, and versions. Sum total distinct daily active users across the same scope using HyperLogLog merge operations for accurate cross-dimensional counting.
- **Currency conversion**: All amounts are converted to USD using end-of-day price feeds, with manipulation protection through minimum value selection between trading pair tokens
- **Time aggregation**: Both fees and user counts are aggregated to daily boundaries using timestamp truncation to day level
- **Final calculation**: Calculate average fees per user by dividing total daily fees by total daily active users using the `calculate_arpu` macro, then apply standardized formatting through the `finalize_metric_afpu` macro with zero-filling strategy for missing data

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

DODODODO

Average fees per user (AFPU)

Average fees per user (AFPU)

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