Overcollateralized nodes custody and transfer funds between blockchains and receive burn & mint fees from traders (supply-side fees).

Ren is a non-custodial interoperability protocol built on Ethereum and other blockchains. Ren was founded by Tayiang Zhang & Loong Wang and launched in 2017. Ren is currently only in redeeming-mode, due to their exposure to the effects of Alameda Research's failure.

REN tokenholders own and govern the protocol. They do not currently take a cut of the total mint/burn fees paid by traders (revenue). Ren's investors include Polychain, FBG Capital, BlockVC, etc.

governance

github

twitter

discord

etherscan

website

Bridges

# Ren Active users (weekly) Methodology

## 1. Overview

Weekly Active Users (WAU) measures the number of unique users who interact with the REN protocol bridge within any 7-day rolling period. This metric answers the business question "How many distinct users are actively using REN's cross-chain bridge services each week?" The calculation uses a sliding 7-day window approach, counting each unique user address only once per week regardless of how many bridge transactions they perform. The metric is calculated across multiple dimensions including overall protocol level, individual blockchain networks, user types (depositors vs withdrawers), and product categories.

## 2. Data sources

The calculation relies on the following raw data sources:

- **REN protocol bridge events**: Parsed `LogBurn` and `LogMint` events from REN protocol's BTCGateway and ETHGateway smart contracts deployed across seven blockchain networks
- **Multi-chain event data**: Bridge transaction events from Ethereum, Arbitrum, Avalanche, BSC, Fantom, Polygon, and Optimism networks
- **Transaction metadata**: Block timestamps, transaction hashes, and user addresses from bridge interactions
- **Contract event logs**: Smart contract event emissions capturing bridge deposit and withdrawal operations

## 3. Step-by-step calculation

### Component A: User activity extraction
- **Purpose**: Identifies and classifies all users who interact with REN protocol bridges
- **Logic**: Extracts user addresses from parsed `LogBurn` and `LogMint` events across seven supported blockchain networks. `LogMint` events represent bridge deposits and classify users as 'Depositor', while `LogBurn` events represent bridge withdrawals and classify users as 'Withdrawer'. The system processes events from BTCGateway contracts on most chains and ETHGateway contracts on Arbitrum and Avalanche. Each event record captures the user address, transaction timestamp, chain identifier, and user classification.
- **Key fields**: `user_address` (the wallet performing the bridge operation), `block_timestamp` (when the transaction occurred), `chain` (source blockchain network), `user_type` (Depositor or Withdrawer based on event type)

### Component B: Daily active user aggregation
- **Purpose**: Aggregates user activity into daily unique counts by various dimensions
- **Logic**: Groups all bridge user activity by calendar day, counting distinct user addresses within each day. The aggregation creates separate groupings by chain (individual blockchain networks), user type (Depositor vs Withdrawer), and product categories. This creates a foundation dataset of daily active users (DAU) with dimensional breakdowns that will feed into the weekly calculation.
- **Key fields**: `timestamp` (daily bucket), `user_dau` (distinct user address), `chain` (blockchain network), `user_type` (user classification)

### Component C: HyperLogLog sketch creation
- **Purpose**: Converts daily user counts into HyperLogLog sketches for efficient weekly distinct counting
- **Logic**: Transforms the daily active user data into HyperLogLog probabilistic data structures using BigQuery's HLL functions. This approach enables efficient merging of user sets across multiple days without double-counting users who are active on multiple days within the same week. Each daily user set becomes an HLL sketch that can be mathematically combined with other days' sketches.
- **Key fields**: `hll` (HyperLogLog sketch representing daily unique users), dimensional grouping fields maintained from previous step

### Component D: Sliding window construction
- **Purpose**: Creates a 7-day rolling window for each date to capture weekly active users
- **Logic**: Generates a complete datespine covering all days in the analysis period, then creates a sliding 7-day window by joining each date with the previous 6 days. For each target date, the system identifies all days from 6 days prior through the target date itself, creating a consistent 7-day window. This ensures that WAU for any given date represents users active during that date and the preceding 6 days.
- **Key fields**: `timestamp` (target date), `joinday` (each of the 7 days in the window), dimensional fields carried through from HLL sketches

### Component E: Weekly distinct user calculation
- **Purpose**: Merges HLL sketches across the 7-day window to count distinct weekly users
- **Logic**: For each 7-day window, merges all HLL sketches from the constituent days using HLL merge functions. This mathematical combination ensures that users who were active on multiple days within the week are counted only once. The merged HLL sketch is then extracted to produce the final distinct user count for that week.
- **Key fields**: `user_wau` (distinct weekly active user count), dimensional grouping maintained throughout the process

### Final aggregation
- **Combining components**: The system creates four dimensional breakdowns of the WAU metric: project-level (combining all chains and user types), chain-level (separate WAU for each blockchain), user-type level (separate WAU for Depositors and Withdrawers), and product-level breakdowns. Each breakdown uses the same sliding window and HLL merging logic but with different grouping dimensions.
- **Currency conversion**: No currency conversion required as this is a user count metric
- **Time aggregation**: Uses daily boundaries with 7-day sliding windows, where each date's WAU represents unique users from that date plus the previous 6 days
- **Final calculation**: The final WAU value for any given date equals the distinct count of user addresses who performed at least one bridge transaction (either deposit via `LogMint` or withdrawal via `LogBurn`) within the 7-day period ending on that date, calculated using HyperLogLog sketch merging for computational efficiency

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

Unique revenue-generating users over a rolling 7-day window.

RenREN

Active users (weekly)

Active users (weekly)

Competitive landscape

Chain breakdown