Lenders deposit funds into Spark and receive interest payments from borrowers (supply-side fees).

Spark is a non-custodial lending protocol built on Ethereum. Spark’s development team Phoenix Labs was founded in early 2023.

SPK tokenholders own and govern the protocol. They currently take a cut of the total interest paid by borrowers (revenue).

governance

github

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discord

website

linkedin

Lending

Spark

SparkLend | Data breakdown

# Spark Active users (monthly) Methodology

## 1. Overview

Active users (monthly) is defined as the number of unique addresses that make a revenue-generating transaction with Spark on a monthly basis. This metric is used to evaluate user adoption, engagement, and overall utility of the protocol's core products, SparkLend and Spark Savings. Unique addresses interacting with the protocol's smart contracts are tracked over a 30-day rolling window to provide a clear representation of active demand. This metric is utilized as a key indicator of protocol health and growth for institutional investors analyzing the Sky ecosystem.

## 2. Data sources

- **Blockchain events**: `Borrow`, `FlashLoan`, `Repay`, `Supply`, and `Withdraw` events from `Pool` contracts, as well as `Deposit` and `Withdraw` events from `spETH`, `spUSDC`, `spUSDT`, `spPYUSD`, `sUSDC`, and Spark Savings USDG (`Spark Savings USDG`) contracts, covering Ethereum, Gnosis, Arbitrum, Base, and 4 other chains

## 3. Step-by-step calculation

### Component A: SparkLend user tracking

- **Purpose**: Unique user addresses interacting with SparkLend are extracted.
- **Logic**: `Borrow`, `FlashLoan`, `Repay`, `Supply`, and `Withdraw` events from `Pool` contracts are parsed. The user address is extracted from the `user` field for `Borrow`, `Repay`, `Supply`, and `Withdraw` events, and from the `initiator` field for `FlashLoan` events. Each address is categorized by its role (e.g., Borrower, Repayer, Depositor, Withdrawer) and associated with the SparkLend product.
- **Key fields**: `block_timestamp`, `transaction_hash`, `user` (extracted as user address), `initiator` (extracted as user address)

### Component B: Spark Savings user tracking

- **Purpose**: Unique user addresses interacting with Spark Savings are extracted.
- **Logic**: `Deposit` and `Withdraw` events from `spETH`, `spUSDC`, `spUSDT`, `spPYUSD`, `sUSDC`, and Spark Savings USDG (`Spark Savings USDG`) contracts are parsed. The user address is extracted from the `owner` field for both deposit and withdraw events. Each address is categorized by its role (Depositor or Withdrawer) and associated with the Spark Savings product.
- **Key fields**: `block_timestamp`, `transaction_hash`, `owner` (extracted as user address)

### Component C: Monthly aggregation and deduplication

- **Purpose**: Active users across all products are consolidated and deduplicated on a monthly basis.
- **Logic**: The extracted user addresses from SparkLend and Spark Savings are combined. The dataset is truncated to 30-day rolling windows using the block timestamp. Duplicate addresses are removed within each combination of 30-day window, chain, user type, and product to determine the monthly distinct active users. Finally, a chain availability filter is applied to exclude data from archived chains or periods exceeding approved timestamps.
- **Key fields**: `block_timestamp`, `chain_id`, `product_id`, `user_type`, `user_address`

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

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

SparkSPK

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown