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Products dataset

  • Label: Products
  • Description: Catalog and performance metrics for products.
  • Default group key: product_id

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Metrics

  • total_sales (USD)
    • Sales after discounts and before taxes/returns.
    • Example: SUM(total_sales)
  • quantity_purchased (items)
    • Number of items purchased.
    • Example: SUM(quantity_purchased)
  • view_sessions (sessions)
    • Sessions where the product was viewed.
    • Example: COUNT_DISTINCT(view_sessions)
  • cart_sessions (sessions)
    • Sessions where the product was added to cart.
  • quantity_added_to_cart (items)
    • Items added to cart from online store sessions.

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Dimensions

  • geo_country: Two-letter country code.
  • geo_state: Up to three-letter province code.
  • geo_city: City name as captured.
  • marketing_source: UTM source.
  • marketing_medium: UTM medium.
  • marketing_campaign: UTM campaign.

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Product attributes (dynamic)

  • Usage: Use product_attributes.* to group or segment by dynamic product attributes defined in your catalog.
  • Examples: 
    GROUP BY product_attributes.color
GROUP BY product_attributes.size
SEGMENT BY product_attributes.material

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Dates

  • Relative offsets: -24h, -48h, -7d, -14d, -30d, -90d, -12m, -1y
  • Keywords: today, yesterday, this_week, last_week, this_month, last_month, this_quarter, last_quarter, this_year, last_year
  • Rolling windows: past_7_days, past_14_days, past_30_days, past_60_days, past_90_days, past_180_days, past_365_days
  • ISO timestamps: 2025-03-15 or 2025-03-15T10:30:00Z

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Examples

Sales by product (last 7 days) 
FROM products
SHOW SUM(total_sales)
GROUP BY product_id
SINCE -7d
Views by campaign (this month) 
FROM products
SHOW COUNT_DISTINCT(view_sessions)
GROUP BY marketing_campaign
SINCE this_month
Sales by color (past 30 days) 
FROM products
SHOW SUM(total_sales)
GROUP BY product_attributes.color
SINCE past_30_days