Bitcoin holders deposit Bitcoin into Solv Protocol and receive yield from onchain strategies (supply-side fees).

Solv Protocol offers financial services for Bitcoin, including lending, liquid staking, yield generation, and fund management.

Solv Protocol team & investors own and govern the protocol. They currently take a cut of the total yield generated (revenue). Solv Protocol's investors include IOSG, Blockchain Capital, Binance Labs, etc.

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Solv Protocol

# Solv Protocol Active users (daily) Methodology

## 1. Overview

Daily active users (DAU) measures the number of unique users interacting with the Solv protocol each day across multiple blockchain networks. This metric tracks users who create subscriptions (deposits) or redemptions through Solv's Bitcoin-backed token routers. The calculation uses HyperLogLog aggregation to enable efficient counting across multiple dimensions while maintaining accuracy for large user sets.

## 2. Data sources

The metric relies on the following blockchain data sources:

- **Parsed contract events**: `CreateSubscription` and `CreateRedemption` events from SolvBTCRouter and SolvBTCLSTRouter contracts
- **Multi-chain coverage**: Event logs from Ethereum, BSC, Arbitrum, Base, and Avalanche blockchain networks
- **Event parameters**: User addresses extracted from `subscriber` and `redeemer` event parameters
- **Transaction metadata**: Block timestamps and transaction hashes for temporal and transaction-level tracking

## 3. Step-by-step calculation

### Component A: User interaction extraction
- **Purpose**: Identify and classify user interactions with Solv protocol contracts
- **Logic**: Parse blockchain event logs across five supported chains (Ethereum, BSC, Arbitrum, Base, Avalanche) to extract user addresses from specific contract events. Monitor two types of router contracts - SolvBTCRouter and SolvBTCLSTRouter - for subscription and redemption activities. Extract user addresses from the `subscriber` parameter in `CreateSubscription` events and the `redeemer` parameter in `CreateRedemption` events. Apply chain-specific filtering and assign each interaction a user type classification.
- **Key fields**: `block_timestamp` for temporal tracking, `user_address` for user identification, `chain` for network classification, `user_type` for interaction classification, `product_id` for product-level tracking

### Component B: Daily user aggregation
- **Purpose**: Transform raw interactions into daily unique user counts with HyperLogLog preparation
- **Logic**: Group user interactions by truncating block timestamps to daily boundaries. Create distinct combinations of date, chain, user type, and product ID, ensuring each unique user address is counted only once per day within each grouping. Initialize HyperLogLog sketches for each daily group to enable efficient cross-dimensional counting in subsequent aggregation steps.
- **Key fields**: `timestamp` truncated to day level, `timestamp_grain` set to 'day', `user_dau` containing unique user addresses for HLL processing

### Component C: Multi-dimensional breakdown creation
- **Purpose**: Generate DAU metrics across different analytical dimensions
- **Logic**: Create four separate dimensional views using HyperLogLog merge operations. Generate project-level aggregation by merging all chains and user types together. Create chain-level breakdown by preserving chain identity while merging across user types. Generate user-type breakdown by preserving user type classification while merging across chains. Create product-level breakdown by preserving product ID while merging other dimensions. Each breakdown uses HLL extract functions to convert sketches back to final count values.
- **Key fields**: `dimensions` indicating breakdown type, dimension-specific ID fields (`chain_id`, `user_type`, `product_id`), `user_dau` as final count values

### Final aggregation
- **Combining components**: Union all dimensional breakdowns into a single result set with standardized schema structure. Apply null padding to unused dimension columns for each breakdown type to maintain consistent column structure across all dimension types.
- **Time aggregation**: Daily boundaries determined by truncating blockchain timestamps to day level, ensuring consistent daily counting regardless of transaction timing within each day.
- **Final calculation**: Extract final DAU counts from merged HyperLogLog sketches, providing approximate but highly accurate unique user counts that scale efficiently across large user populations and multiple analytical dimensions.

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

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

Solv ProtocolSOLV

Active users (daily)

Active users (daily)

Competitive landscape

Chain breakdown