Orders Overview

Report Orders (weekly) + Summary Driver List (daily)

Trips over time

Completed vs cancelled · click a legend item to isolate

Cancellation structure

Share of cancelled orders by reason
click a segment to cross-filter

Service class mix

Completed trips by service class
click a bar to cross-filter

Revenue by service class

Fare in Yango Pro, completed trips

Service class structure over time

Share of completed trips by class, %

Payment structure over time

Cash / card / corporate / promo — share of payment amount, completed trips

Average trip: distance & fare

Completed trips only

Price per km & trips per hour

Fare ÷ km · completed trips ÷ hours online

Driver Profile

Transactions + orders + hours for a single driver

Fleet Performance

Own fleet drivers only — activity, targets, and who needs attention

🎯 Targets — minimum per driver

Fleet trend

Order structure

Drivers

All Drivers Performance

All drivers · selected metrics across time buckets

Driver Balances

Cumulative balance-affecting transactions (cash excluded) up to a chosen date & time

Balance distribution

Number of drivers per balance bucket at the cutoff

Positive vs negative totals over time

End-of-day totals, up to the cutoff date

Top debtors

Deepest negative balances at the cutoff

Drivers detail

Drivers Analytics

Recruitment, activation funnel and churn · as of the latest loaded day

New drivers added

By “Date added”, split by acquisition channel

Active drivers over time

Unique drivers with ≥ 1 completed trip in the period (orders data)

Cohort conversion

Drivers added in the period who reached their 1st / 10th / 50th trip (lifetime). Recent cohorts are naturally lower — they had less time.

Time to first trip

Average days from “Date added” to first trip, by cohort and channel

Driver status structure

Active = trip ≤ 9 days ago · Pre-churn = 10–13 · Churned = ≥ 14 · Never = no trips at all

Days since last trip

Drivers who ever made a trip, bucketed by inactivity

Drivers detail

Para el Conductor

Una página simple para mostrar al conductor por qué aceptar pedidos = ganar más · показать водителю на телефоне или распечатать

💰 ¿Quieres ganar más por hora? Acepta los pedidos.

Datos reales de nuestros conductores (último mes, mínimo 20 horas en línea). Cada barra = ganancia promedio por hora según cuántos pedidos acepta el conductor.

🧮 Calcula tu ganancia

Mueve los controles — la estimación usa la relación real entre aceptación y ganancia de nuestra flota.


✅ Tres reglas simples (basadas en datos reales)

1. Acepta los pedidos que te llegan. Los conductores que aceptan 90%+ ganan hasta 3 veces más por hora que los que aceptan menos del 30%.

2. No filtres esperando el viaje "caro". Nuestros datos muestran: cada viaje paga casi lo mismo por hora — un viaje corto y barato deja tiempo para otro viaje más. El que espera, pierde.

3. Más viajes por hora = más dinero. La zona y la hora casi no cambian tu ganancia por hora (±5%). Lo único que la cambia de verdad eres tú: acepta y maneja.

Revenue Mix

Where the partner income comes from — fleet vs aggregator, driver tenure cohorts, churn losses

Partner revenue by month

Stacked by segment

Segment shares over time

Each segment as % of that month's partner revenue

Cohort matrix — join month × revenue month

Each row = drivers who joined in that month; cells = partner revenue they generated in each later month. Reading along a row shows how a cohort's contribution holds up or fades.

Churn — lost revenue

Drivers whose partner revenue collapsed vs the previous month

Top drivers by partner revenue

Concentration: who the income actually depends on (selected range)

EPH Factors

Why one driver earns S/ 30/h and another S/ 20/h — factor decomposition of earnings per hour

EPH vs factor

Each dot = one driver over the selected range

Factor correlations with EPH

Pearson r across all analyzed drivers · |r| closer to 1 = stronger link

Driver comparison — EPH bridge

EPH = trips/hour × net per trip. The bridge splits the EPH gap between two drivers into a frequency part and a trip-value part (exact midpoint decomposition).

All drivers — factor table

Sortable: click a header. Only drivers above the minimum-hours threshold are included.

Do peak hours & districts really matter? — order-level proof

Computed from raw order coordinates of the selected range. Prices are gross fares; "active hour" = a driver-hour with ≥1 completed order.

Fare per active hour · by hour of day

Fare per active hour · by pickup district

District → district average trip price

Rows = pickup district, columns = destination district, cell = average completed fare (S/) · top districts by volume in the selected range

Map

Order geography — demand, destinations & cancellations · powered by API coordinates
Heatmap intensity = order density. Toggle layers above. The map needs internet for the base tiles; the rest of the dashboard works offline.

Data Completeness

Which exports are loaded, which are missing