# Active users (monthly) Methodology

## 1. Overview

Active users (monthly) is defined as the number of unique addresses associated with transactions executed on Spark Savings within a 30-day rolling window. User interactions with Spark Savings are captured through deposit and withdrawal activities across supported blockchain networks. Active engagement with the yield-generating contracts of the protocol is represented by these transactions. Active users (monthly) are aggregated at a monthly granularity to provide insights into the adoption and ongoing utility of Spark Savings.

## 2. Data sources

- **Blockchain events**: `Deposit` and `Withdraw` events from `spETH`, `spUSDC`, `spUSDT`, `spPYUSD`, `sUSDC`, and `Spark Savings USDG` contracts, covering Ethereum, Avalanche, Arbitrum, Base, and 3 other chains

## 3. Step-by-step calculation

### Component A: Spark Savings user activity extraction

- **Purpose**: To extract unique user addresses and transaction details from Spark Savings deposit and withdrawal events.
- **Logic**: `Deposit` and `Withdraw` events are parsed from the respective savings contracts, comprising `spETH`, `spUSDC`, `spUSDT`, `spPYUSD`, `sUSDC`, and `Spark Savings USDG` contracts. For each event, the `owner` field is extracted to identify the active user address. Users are categorized as either a depositor or a withdrawer based on the event type. Transaction timestamps and chain identifiers are retained for temporal and network-based categorization.
- **Key fields**: `owner` (user address), `block_timestamp` (timing), `chain_id` (network identification)

### Component B: Chain availability and freshness filtering

- **Purpose**: To filter transaction records based on chain-specific freshness and archival parameters.
- **Logic**: Transaction records are joined with chain freshness metadata. Records are excluded if the transaction timestamp is recorded after the last approved timestamp for active chains, or after the archival timestamp for archived chains, unless a project-only archival strategy is specified. Validation and timeliness of the included data are ensured through this filtering process.
- **Key fields**: `block_timestamp` (timing), `chain_id` (network identification)

### Component C: Monthly active user aggregation

- **Purpose**: To aggregate unique user addresses to calculate active users (monthly).
- **Logic**: The filtered user addresses from Spark Savings are grouped by 30-day window, chain, and product. A distinct count of user addresses is performed over each 30-day rolling window to determine the active users (monthly). These product-level active users are then made available for project-level aggregation.
- **Key fields**: `user_address` (user address), `block_timestamp` (timing)

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

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

Active users (monthly)

Asset management

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).

Spark Savings

Active users (monthly)

Active users (monthly)

Chain breakdown