Sales statistics

salesStatistics returns aggregated sales figures, grouped by the dimensions you ask for. One query covers all the usual "sales by ..." reports: by day, month, product, brand, category, country or customer, and combinations of those.

note

Requires an ADMIN token and the STATISTICS_READ API key permission.

You always provide:

• dimensions (1-3) - what to group by. You get one row per unique combination of values.
• metrics (1-10) - what to aggregate per row.
• dateRange - from is inclusive, to is exclusive, based on the order's created time.

Optional: filter (all filters are ANDed), orderBy (the metric must be one you requested) and limit (default 1000, max 5000). Only the fields matching your requested dimensions and metrics are filled in - the rest are null. All monetary metrics are expressed in the currency returned in currency.

By default only non-cancelled order statuses (id >= 0) are included; use filter.orderStatusIds to pick specific ones.

Sales per month

Request:

query salesPerMonth {
  salesStatistics(
    dimensions: [MONTH]
    metrics: [REVENUE_EXCLUDING_TAX, ORDER_COUNT]
    dateRange: { from: "2026-01-01T00:00:00Z", to: "2026-04-01T00:00:00Z" }
  ) {
    rows {
      month
      revenueExcludingTax
      orderCount
    }
    currency {
      code
    }
    truncated
  }
}

Response:

{
  "data": {
    "salesStatistics": {
      "rows": [
        { "month": "2026-01", "revenueExcludingTax": 184320.5, "orderCount": 412 },
        { "month": "2026-02", "revenueExcludingTax": 156900.0, "orderCount": 355 },
        { "month": "2026-03", "revenueExcludingTax": 201455.75, "orderCount": 468 }
      ],
      "currency": {
        "code": "SEK"
      },
      "truncated": false
    }
  }
}

Top selling products

Use orderBy together with limit for a top-N report.

Request:

query topProducts {
  salesStatistics(
    dimensions: [PRODUCT]
    metrics: [QUANTITY, REVENUE_EXCLUDING_TAX]
    dateRange: { from: "2026-01-01T00:00:00Z", to: "2026-04-01T00:00:00Z" }
    orderBy: { metric: QUANTITY, direction: DESC }
    limit: 2
  ) {
    rows {
      productId
      productName
      quantity
      revenueExcludingTax
    }
    currency {
      code
    }
    truncated
  }
}

Response:

{
  "data": {
    "salesStatistics": {
      "rows": [
        {
          "productId": "AVR 135",
          "productName": "Pioneer, DV-585A, DVD-spelare",
          "quantity": 318,
          "revenueExcludingTax": 41453.25
        },
        {
          "productId": "prod124",
          "productName": "ClearSip Elegance",
          "quantity": 254,
          "revenueExcludingTax": 14852.4
        }
      ],
      "currency": {
        "code": "SEK"
      },
      "truncated": true
    }
  }
}

truncated: true means the row limit cut the result off. For a top-N report that is expected; for a full report, narrow dateRange or filter instead of raising limit.

Combining dimensions and filtering

Up to three dimensions can be combined, for example sales per month and country for a couple of brands:

query salesPerMonthAndCountry {
  salesStatistics(
    dimensions: [MONTH, COUNTRY]
    metrics: [REVENUE_INCLUDING_TAX, TAX_AMOUNT, ORDER_COUNT]
    dateRange: { from: "2026-01-01T00:00:00Z", to: "2026-04-01T00:00:00Z" }
    filter: { brandIds: [12, 15], countryCodes: ["SE", "NO"] }
    orderBy: { metric: REVENUE_INCLUDING_TAX, direction: DESC }
  ) {
    rows {
      month
      countryCode
      countryName
      revenueIncludingTax
      taxAmount
      orderCount
    }
    currency {
      code
    }
  }
}

New customers

CUSTOMER_COUNT counts distinct customers who ordered in a row, and NEW_CUSTOMER_COUNT how many of those registered within the requested dateRange.

query newCustomersPerWeek {
  salesStatistics(
    dimensions: [WEEK]
    metrics: [CUSTOMER_COUNT, NEW_CUSTOMER_COUNT, REVENUE_EXCLUDING_TAX]
    dateRange: { from: "2026-01-01T00:00:00Z", to: "2026-04-01T00:00:00Z" }
  ) {
    rows {
      week
      customerCount
      newCustomerCount
      revenueExcludingTax
    }
    currency {
      code
    }
  }
}

note

When grouping by CATEGORY, only a product's standard category is counted, so quantity and revenue are not split across a product's secondary categories.