OpenChat users can send messages to each other containing tokens such as ICP. Users can upgrade to Diamond membership to have access to extra or enhanced features.

OpenChat is a chat application running end-to-end on the Internet Computer blockchain.

CHAT tokenholders own and govern the protocol.

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OpenChat

# OpenChat Average fees per user (AFPU) Methodology

## 1. Overview

Average fees per user (AFPU) measures the daily revenue generated per active user on the OpenChat protocol. This metric is calculated by dividing the total daily fees collected from diamond membership payments by the number of daily active users. AFPU provides insight into user monetization effectiveness and revenue density for the social messaging protocol built on the Internet Computer blockchain.

## 2. Data sources

The calculation relies on the following data sources:

- **OpenChat protocol events**: Event logs from the OpenChat application containing user activity signals and payment transactions, including user online status and diamond membership purchase events
- **End-of-day price feeds**: Token price data from CoinGecko API for CHAT and ICP tokens to enable USD conversion of payment amounts
- **Token metadata**: Mapping information linking token symbols (CHAT, ICP) to their corresponding CoinGecko identifiers ('openchat', 'internet-computer')

## 3. Step-by-step calculation

### Component A: Event data processing
- **Purpose**: Extract and deduplicate raw OpenChat protocol events
- **Logic**: All events from the OpenChat `events_v4` data source are processed and deduplicated based on timestamp, user identifier, event name, data source, and JSON payload content. Row numbering is applied to identify and retain only the first occurrence of each unique event combination.
- **Key fields**: `timestamp`, `name` (event type), `user` (user identifier), `source`, `payload` (JSON event data)

### Component B: User activity tracking
- **Purpose**: Identify daily active users from online status events
- **Logic**: Events are filtered to include only `user_online` events occurring on or after February 14, 2024. Each event represents a user coming online and contributes to the daily active user count. Users are identified by their unique user addresses from the event data.
- **Key fields**: `timestamp` (for daily aggregation), `user_address` (unique user identifier)

### Component C: User aggregation
- **Purpose**: Calculate daily active users using probabilistic counting
- **Logic**: Daily active users are counted using HyperLogLog (HLL) functions to efficiently handle unique user counting across large datasets. The aggregation creates multiple dimensional breakdowns including project-level, chain-level, user-type-level, and product-level views. All users are classified under the 'internetcomputer' chain and 'social' market sector.
- **Key fields**: `user_dau` (unique daily active user count), `timestamp_grain` (set to 'day'), `chain_id`, `dimensions` (breakdown type)

### Component D: Payment event extraction
- **Purpose**: Extract diamond membership payment transactions
- **Logic**: Events are filtered for `diamond_membership_payment` events, and the JSON payload is parsed to extract payment details. The `amount` field is extracted and divided by 1e8 to correct for decimal places. Token types are mapped from symbols (CHAT, ICP) to CoinGecko identifiers ('openchat', 'internet-computer') for price lookup purposes.
- **Key fields**: `amount` (payment amount after decimal correction), `token` (payment currency), `coingecko_id` (mapped identifier), `duration` (membership duration)

### Component E: Fee calculation and USD conversion
- **Purpose**: Convert payment amounts to USD and aggregate daily fees
- **Logic**: Payment amounts are converted to USD using end-of-day price feeds from CoinGecko for the respective tokens. Each payment is timestamped to the day level, and all payments within a day are summed to calculate total daily fees. Payments are classified under the 'internetcomputer' chain and 'social' business segment.
- **Key fields**: `fees` (USD-converted payment amounts), `daily_timestamp` (day-level timestamp), `chain_id`

### Final aggregation
- **Combining components**: Daily active user counts and daily fee totals are combined through the calculate_arpu macro, which performs the division of fees by user count to generate the average fees per user
- **Currency conversion**: All payment amounts are converted to USD using end-of-day price feeds, with token-specific price lookups based on CoinGecko identifiers
- **Time aggregation**: Both user activity and payment data are aggregated to daily boundaries using timestamp truncation, ensuring consistent time alignment between numerator and denominator
- **Final calculation**: AFPU is calculated as total daily fees (in USD) divided by daily active user count, with the result processed through the finalize_metric_afpu macro to ensure proper schema formatting and handle any data gaps with zero-filling where appropriate

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

OpenChatCHAT

Average fees per user (AFPU)

Average fees per user (AFPU)

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