> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Orders by Chinese Province, JD.com > Orders by Chinese Province for JD.com stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Card class:** [Non-Hero](/nerve-centre/overview#card-classes-explained) • **Category:** [Marketplace](/nerve-centre/connectors#connectors-by-type) ## At a glance > **Orders by Chinese Province** maps where your JD.com demand actually sits, broken out across China's provinces, municipalities, and autonomous regions. China is not one market: a strong showing in coastal Guangdong, Zhejiang, and Jiangsu behaves very differently from demand in inland or western provinces, both in buyer expectation and in how reliably JD Logistics can hit the 24-hour promise. This choropleth turns a flat order count into a geographic story, showing where to concentrate marketing, where fulfilment SLAs are at risk, and where an untapped province might justify regional stock. It sits in the Geography family and reads best beside the province-level AOV, order-volume, and logistics cards below. | | | | --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | The number of orders in the window attributed to each Chinese province, municipality, or autonomous region, based on the buyer's delivery address. | | **Sample type** | Backend API data from JD.com, refreshed on the standard data refresh. | | **Why it matters** | Demand and fulfilment performance both vary sharply by region. Knowing where orders concentrate guides ad spend, regional stocking, and which provinces are most exposed to logistics SLA risk during surges. | | **Reading the value** | Read the map by intensity: darker provinces are higher volume. Compare against AOV by province to separate high-volume-low-value regions from high-value pockets, and watch for shifts that signal a new regional opportunity or a fulfilment problem. | | **Currency** | count | | **Time window** | `30D` | | **Alert trigger** | `-` | | **Sentiment key** | `jd_orders_by_province` | | **Roles** | owner, marketing | ## Calculation Each order in the window is assigned to a Chinese province based on the delivery address, then counted. The choropleth shades each region by its order count. Cross-border orders shipping into China are mapped to their destination province; orders without a resolvable Chinese province (for example certain cross-border or gift flows) are grouped separately so the map reflects only addressable domestic demand. ## Worked example *A representative reading of **Orders by Chinese Province** for a typical merchant on JD.com.* Say the 30-day map shows Guangdong leading with 3,100 orders, Jiangsu and Zhejiang close behind, and a sudden jump in Sichuan from 200 to 900 orders after a regional campaign. The coastal trio is steady and well served by JD Logistics, but the Sichuan surge is straining same-day delivery in inland prefectures, visible as a dip on the SLA compliance card concentrated in that province. Two reads follow: the campaign worked and Sichuan deserves regional stock to protect the promise, and the SLA risk is geographic, not store-wide. For deeper investigation, use Vortex Mind to correlate province order growth with logistics SLA by region; for natural-language exploration, ask Ask Viq "which provinces grew fastest and are any breaching the delivery promise". ## Sibling cards merchants should reference together | Card | Why merchants reach for it | | --------------------------------------------------------------------------------- | -------------------------------------------------------------------------- | | [`jdc_aov_by_province`](/nerve-centre/kpi-cards/jd-com/aov-by-chinese-province) | Geography sibling: order value per province, to read volume against value. | | [`jdc_orders`](/nerve-centre/kpi-cards/jd-com/orders) | Sales sibling: total order count this map breaks down by region. | | [`jdc_orders_per_day`](/nerve-centre/kpi-cards/jd-com/orders-day) | Fulfilment sibling: daily order trend behind a regional surge. | | [`jdc_logistics_sla`](/nerve-centre/kpi-cards/jd-com/jd-logistics-sla-compliance) | Fulfilment sibling: delivery-promise compliance that varies by province. | | [`jdc_total_revenue`](/nerve-centre/kpi-cards/jd-com/total-revenue) | Revenue sibling: the revenue context for regional order concentration. | ## Reconciling against the vendor's own dashboard **Where to look in JD.com's own dashboard:** JD's Seller Centre offers regional or geographic breakdowns of orders in its data and analytics views, typically by province. Confirm the report uses delivery address (not billing or registration address) and that the period matches the Vortex IQ 30-day window. **Why the Vortex IQ value may legitimately differ:** | Reason | Direction | What to do | | ------------------------------------------------------------------------------------------------------------------------------- | --------- | --------------------------------------------- | | **Address basis.** Vortex IQ attributes by delivery province; JD reports may use a different address field. | Variable | Confirm the report uses delivery address. | | **Period boundary.** Vortex IQ uses a 30-day rolling window; JD often defaults to calendar months. | Variable | Match the date range. | | **Cross-border mapping.** Cross-border orders into China are mapped to destination province here; JD may group them separately. | Variable | Check how cross-border orders are attributed. | | **Region naming.** Municipalities and autonomous regions may be grouped differently between systems. | Marginal | Confirm region grouping. | **Cross-connector reconciliation:** read alongside AOV by province and logistics SLA to turn a count map into a value-and-risk map. For divergence investigations, use Vortex Mind. ## Known limitations / merchant FAQs **Q: How often does Orders by Chinese Province update?** The card refreshes on the standard data refresh (typically every 30-60 minutes for live integrations). For real-time signals, force a manual refresh from the dashboard. **Q: Why does my JD.com dashboard show a different breakdown?** The common causes are the address basis (delivery vs billing vs registration), period boundaries (30-day rolling vs calendar months), and how cross-border orders are mapped to provinces. Match those before assuming a real divergence. **Q: A province jumped suddenly. Is that real demand?** It usually traces to a regional campaign, a local festival, or a marketplace promotion concentrated in that area. Cross-reference orders per day and the campaign calendar, and watch the logistics SLA for that province in case the surge outpaces fulfilment. **Q: Can I customise the alert threshold?** This card has no default alert because regional concentration is informational. You can add a sensitivity rule in the Sensitivity tab to be notified when a province's share moves beyond a chosen band. *** ### Tracked live in Vortex IQ Nerve Centre *Orders by Chinese Province* is one of hundreds of KPI pulses Vortex IQ tracks across JD.com and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. [Start for free](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.