Liquidity providers (LPs) deposit funds into Convex Finance and receive a return on investment (supply-side fees).

Convex Finance is an asset management and staking protocol built on Ethereum. Convex Finance launched in May 2021.

CVX tokenholders own and govern the protocol. They currently take a cut of the total yield generated (revenue).

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Asset management

Convex Finance

# Convex Finance Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) measures the number of unique users who have interacted with Convex Finance over a rolling 30-day period. This metric captures user engagement by tracking deposit activities to Convex Finance's yield aggregation platform. The calculation uses HyperLogLog data structures for efficient distinct user counting across multiple dimensional breakdowns and maintains rolling 30-day windows for each day in the time series.

## 2. Data sources

- **Ethereum token transfer events**: Parsed `Transfer` events from Ethereum blockchain containing transaction details, addresses, and timestamps
- **Token metadata**: Contract addresses and configuration data for Convex Finance's deposit account
- **Chain availability data**: Configuration data determining which blockchain networks are included in calculations

## 3. Step-by-step calculation

### Component A: User interaction extraction
- **Purpose**: Identifies all user deposit activities to Convex Finance
- **Logic**: Filters Ethereum `Transfer` events to capture deposits made to Convex Finance's specific deposit account contract at address `0x989aeb4d175e16225e39e87d0d97a3360524ad80`. Each transfer event represents a user depositing tokens to the platform. The `from_address` field identifies the depositing user, while all interactions are classified as 'Depositor' user type within the 'asset_management' market sector and 'yield_aggregator' business segment
- **Key fields**: `block_timestamp` for timing, `transaction_hash` and `log_index` for event identification, `from_address` as the user identifier, `chain` for blockchain network identification

### Component B: Daily active user calculation  
- **Purpose**: Aggregates user interactions into daily distinct user counts
- **Logic**: Groups the extracted user interactions by day using timestamp truncation to day boundaries. Counts distinct user addresses for each day, maintaining dimensional attributes like chain, user type, and product classifications. Creates a daily time series of unique active users who performed deposit activities
- **Key fields**: `timestamp` truncated to day grain, `user_address` for distinct counting, dimensional fields like `chain`, `user_type`, and `product_id`

### Component C: HyperLogLog initialization and windowing
- **Purpose**: Prepares efficient data structures for rolling 30-day distinct user calculations
- **Logic**: Converts daily user lists into HyperLogLog sketches using `hll_count.init()` function for memory-efficient approximate distinct counting. Creates a datespine covering the full time range and generates 30-day rolling windows by joining each day with the previous 29 days using `generate_timestamp_array()`. This windowing approach ensures every day has a complete 30-day lookback period for MAU calculation
- **Key fields**: `hll` sketches containing compressed user data, `timestamp` for window boundaries, `joinday` for window period identification

### Component D: Dimensional breakdowns
- **Purpose**: Calculates MAU across multiple analytical dimensions
- **Logic**: Aggregates the 30-day windowed data across four different dimensional levels: project-level (overall MAU), chain-level (per blockchain), user-type-level (by user classification), and product-level (by product category). Uses HyperLogLog merge operations (`hll_count.merge_partial()`) to combine daily sketches within each 30-day window, then extracts final distinct counts (`hll_count.extract()`) to get MAU values
- **Key fields**: `dimensions` indicating breakdown type, dimensional identifiers like `chain_id` and `user_type`, `user_mau` containing the final count

### Final aggregation
- **Combining components**: Unions all dimensional breakdowns into a single result set, with null values for non-applicable dimensional fields in each breakdown
- **Currency conversion**: Not applicable for user count metrics
- **Time aggregation**: Maintains daily granularity with each day representing a 30-day rolling window MAU calculation
- **Final calculation**: The metric represents the approximate distinct count of users who made deposits to Convex Finance within any 30-day period ending on each date, calculated using HyperLogLog approximation algorithms for computational efficiency

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

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

Convex FinanceCVX

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown