Order Country Demand

What it is

Where the orders come from, and whether a country is growing. One row per shipping country: order and unit counts for the last 14 / 28 / 90 / 180 / 365 days, the same windows one year earlier (_py = prior year), and a look-ahead: how many orders the country produced in the next 90 days of last year — what the coming quarter looked like last time. The headline number is Momentum %: orders in the last 28 days as a percentage of orders in the same 28 days a year ago. 152 means 1.52× last year; 100 means flat. From it the view derives a trend label and a confidence. This is an aggregate designed for agents to read a handful of rows, not to walk thousands of orders. A country signal (“NL orders 28d are 3.35× prior year”) is one row here.

How it gets data

Computed view — derived from Orders (shipping_country_code, placed_at) and Order Line Items (units). Refunded / expired / voided orders are excluded via financial_status. Read-only; no ingest endpoint.

Orders without a shipping country are grouped under country_code = UNKNOWN instead of being dropped, so the gap is visible. Bulk-imported historical orders can lack the country — when the UNKNOWN row is large in a window, the country split for that window is unreliable. Check UNKNOWN before comparing countries on the 90/180/365-day windows.

Fields

Identity & trend

Field	Label	Type	Description
`country_code`	Country	text	ISO-2 shipping country, or `UNKNOWN`
`momentum_pct`	Momentum vs prior year %	number	`100 × orders_28d / orders_28d_py`. Empty when the prior-year base is under 20 orders (too thin to compare). Note: on product views the same column name compares 28 days against 90 days — here it compares against last year
`momentum_delta_pct`	Momentum Δ vs prior year %	number	`momentum_pct − 100`, the same figure as a growth delta: +46 = 46 % more orders than the same 28 days last year
`orders_forecast_next90d`	Orders next 90d (forecast)	number	`orders_next90d_py × momentum_pct ÷ 100` — last year’s coming 90 days scaled by this year’s year-over-year momentum. An assumption that the growth holds, never a truth. Empty when `momentum_pct` is empty
`trend_label`	Trend	status	`RISING` (momentum ≥ 130) / `STABLE` / `FALLING` (≤ 70) / `LOW_VOLUME` (prior-year base under 20 orders)
`trend_confidence`	Confidence	text	`high` (≥ 30 orders in 28d) / `medium` (≥ 15) / `low`
`calculated_at`	Calculated At	datetime	When the view was computed — hidden by default

Current windows

Field	Label	Type	Description
`orders_14d` / `orders_28d` / `orders_90d` / `orders_180d` / `orders_365d`	Orders Nd	number	Distinct orders in the last N days
`units_14d` / `units_28d` / `units_90d` / `units_180d` / `units_365d`	Units Nd	number	Units sold in the last N days

orders_28d is shown by default; the other windows are hidden but selectable.

Prior-year mirrors

Field	Label	Type	Description
`orders_28d_py` / `units_28d_py`	… 28d (prior year)	number	Same 28-day window, one year earlier
`orders_90d_py` / `units_90d_py`	… 90d (prior year)	number	Same 90-day window, one year earlier
`orders_365d_py` / `units_365d_py`	… 365d (prior year)	number	The year before the last 365 days
`orders_next90d_py` / `units_next90d_py`	… next 90d (prior year)	number	The 90 days that followed today’s date last year — what the coming quarter did last time

No revenue columns: the view counts orders and units only. All columns are read-only. The view also carries tenant_id / workspace_id for tenant isolation — filtered automatically, never selected.

Query it

{
  "method": "tools/call",
  "params": {
    "name": "data_query",
    "arguments": {
      "view_slug": "v_order_country_demand",
      "filters": { "trend_label": "RISING" },
      "select_fields": ["country_code", "orders_28d", "orders_28d_py", "momentum_pct", "trend_confidence", "orders_next90d_py"],
      "sort_by": "orders_28d",
      "limit": 20
    }
  }
}

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What it is

How it gets data

Fields

Identity & trend

Current windows

Prior-year mirrors

Query it

​What it is

​How it gets data

​Fields

​Identity & trend

​Current windows

​Prior-year mirrors

​Query it

What it is

How it gets data

Fields

Identity & trend

Current windows

Prior-year mirrors

Query it