Revenue Analysis

Revenue Analysis (Revenue) measures payment/revenue scale. Its core metrics are GMV / ARPU / ARPPU / payment rate, with trends shown per time granularity. It corresponds to the backend AnalyticsService.Revenue.

1. What Questions It Answers

What is the GMV (total transaction value) trend over the last 30 days? Which day is the revenue peak?
What are ARPU (per-user contribution) and ARPPU (per-paying-user contribution)?
Is the payment rate (pay_rate) healthy? Rising or falling?

2. Key Metrics

Metric	Meaning
GMV	Total transaction value (sum of `amount`)
Paying users	`pay_users` (distinct)
Paying orders	`pay_orders`
ARPU	GMV / active users (contribution per user)
ARPPU	GMV / paying users (contribution per paying user)
Payment rate	`pay_rate` = paying users / active users
Average order value	`avg_order_value` = GMV / order count

3. Backend API

gRPC: `AnalyticsService.Revenue`

Field	Type	Description
`time_range`	`TimeRange`	Analysis time range
`app_id`	uint32 (optional)	Filter by app
`granularity`	`AnalyticsGranularity`	Time granularity, default `DAY`

Response RevenueResponse: points[] (RevenuePoint contains timestamp / gmv / pay_users / pay_orders / arpu / arppu / pay_rate), total_gmv, total_pay_users, total_pay_orders, avg_order_value.

HTTP (admin proxy)

POST /admin/v1/analytics/revenue
Content-Type: application/json

{
  "timeRange": { "startMs": 1718169600000, "endMs": 1718774399000 },
  "granularity": "DAY"
}

4. Implementation

It relies on the amount field reported with payment-type events:

GMV: sum of amount across all payment events within the time range.
Paying users/orders: distinct counts by user_id / order.
ARPU: gmv / active user count (active users come from Active Users).
ARPPU: gmv / pay_users.

Therefore payment events must report amount, otherwise GMV/ARPU and similar metrics are distorted.

5. Typical Scenarios

Revenue trend dashboard

Query GMV trends at DAY granularity, together with pay_rate and ARPPU, to monitor revenue health.

Big promotion effectiveness

Compare total_gmv, avg_order_value, and pay_rate before and after a campaign to evaluate the promotion's revenue pull (incremental gain vs. borrowed future spend).

Complementing the payment conversion funnel

Combine with Funnel: the funnel shows "payment conversion rate", Revenue shows "payment amount scale and per-user value" — use them together to evaluate monetization.

6. Notes and Caveats

Depends on the amount field: if payment events do not report amounts, GMV is 0. Amount units must be site-wide consistent (e.g. yuan/CNY).
ARPU needs active users: ARPU's denominator is active users. The Revenue response computes it internally, but interpret it together with ActiveUsers.
Deduplication basis: pay_users is deduplicated by user_id; a user paying multiple times counts as 1 paying user.
Refunds: GMV is currently a positive sum of amount; to subtract refunds, flag refund events at the event layer and build your own query.