Passenger Vehicle Monthly Sales

Use Cases

• Monthly passenger vehicle sales based on first-time compulsory-insurance registrations: the number of new vehicles insured for compulsory insurance for the first time, aggregated by month and mapped to brand, series, trim, and energy type via VIN.

• It is closer to vehicles actually entering use and end-delivery, so it is often used to observe retail demand; strictly speaking, however, it is neither the automaker's factory-gate sales nor the narrow retail caliber used by institutions such as the CPCA.

• Statistics must be limited to "first-time new-vehicle insurance" and exclude renewals, endorsements, cancellations, and duplicate records, and ensure correct vehicle-type attribution (passenger vs. commercial); otherwise monthly new-vehicle sales will be overestimated.

• The insured region reflects the region associated with the policy or vehicle registration and does not necessarily equal the consumer's long-term usage location; cross-region purchasing and out-of-area registration affect regional market judgment.

• Aggregated statistics only; no personal information.

• Market monitoring: track monthly passenger vehicle totals, fuel vs. new-energy vehicles, and terminal performance by brand and series to identify demand turning points and seasonality earlier.

• Competitor analysis: compare regional sales, growth, and share of same-class, same-price-band, or same-powertrain models to inform product positioning, marketing rhythm, and model planning.

• Regional operations: identify the true insured-registration distribution by province, city, or city cluster to support dealer network layout, channel target breakdown, and marketing and inventory resource allocation.

• New model assessment: observe monthly insured-registration ramp, regional penetration, and configuration structure after a new model launch to assess product acceptance and promotion effectiveness.

• Supply chain and business forecasting: combine insured-registration trends with wholesale, orders, inventory, and delivery cycles to support production/sales forecasting and reduce inventory misjudgment from wholesale data alone.

• Finance and insurance research: under compliance, provide model-level demand evidence for residual value assessment, risk pricing, parc estimation, and after-sales service network planning.

• Data product building: combined with MIIT announcements, the passenger vehicle model library, MSRP, and configuration data, more dimensional analytical frameworks can be formed.

Data Field Example

[
    {
        "year_month": 202402,
        "city": "广州市",
        "province": "广东省",
        "domestic_imported": "Domestic",
        "manufacturer": "小鹏汽车",
        "brand": "小鹏",
        "series": "小鹏X9",
        "fuel_type": "BEV",
        "sales": 19,
        "body_type": "MPV",
        "vehicle_class": "Full-size MPV",
        "vehicle_category": "MPV",
        "displacement_l": "0.0L",
        "transmission": "1AT",
        "emission_standard": "Zero-emission",
        "drive_type": "AWD",
        "usage_type": "Non-operational",
        "ownership": "Corporate",
        "city_tier": "Tier 1",
        "brand_tier": "Mid-high",
        "brand_origin": "Domestic"
    }
]

Data Table Example

The table below uses the same record as the JSON example above, with fields laid out by column for easy viewing and copying in spreadsheet form.

year_month	city	province	domestic_imported	manufacturer	brand	series	fuel_type	sales	body_type	vehicle_class	vehicle_category	displacement_l	transmission	emission_standard	drive_type	usage_type	ownership	city_tier	brand_tier	brand_origin
202402	广州市	广东省	Domestic	小鹏汽车	小鹏	小鹏X9	BEV	19	MPV	Full-size MPV	MPV	0.0L	1AT	Zero-emission	AWD	Non-operational	Corporate	Tier 1	Mid-high	Domestic