Products dataset

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

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Metrics

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Sales

• 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)
• buyers (customers)
  • Distinct customers who purchased the product.
• average_selling_price (USD)
  • Total sales divided by quantity purchased.
• units_per_order (items)
  • Quantity purchased per attributed product order.
• units_per_buyer (items)
  • Quantity purchased per distinct buyer.

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Sessions and funnel

• sessions (sessions)
  • Distinct sessions that touched the product.
• view_sessions (sessions)
  • Sessions where the product was viewed.
  • Example: COUNT_DISTINCT(view_sessions)
• click_sessions (sessions)
  • Distinct sessions where the product was clicked.
• cart_sessions (sessions)
  • Sessions where the product was added to cart.
• purchase_sessions (sessions)
  • Sessions where the product was purchased. Pair with view_sessions for a true conversion rate.
• quantity_added_to_cart (items)
  • Items added to cart from online store sessions.
• view_to_cart_rate (rate)
  • Cart sessions per view session.
• cart_to_purchase_rate (rate)
  • Purchase sessions per cart session.
• cart_abandonment_rate (rate)
  • One minus the cart-to-purchase rate.
• session_conversion_rate (rate)
  • Purchase sessions per view session.
• revenue_per_session (USD)
  • Total sales per view session.

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Tile engagement

• product_impressions (events)
  • Tracked product_impression events captured when a product tile enters the shopper’s viewport.
  • Example: SHOW product_impressions
• product_hovers (events)
  • Tracked product_hover events captured when a shopper hovers over a product tile on desktop.
• product_touches (events)
  • Tracked product_touch events captured when a shopper taps or long-presses a product tile on mobile.
• hover_rate (rate)
  • Product hovers divided by product impressions. Useful for measuring tile-level interest on desktop.
• touch_rate (rate)
  • Product touches divided by product impressions. Useful for measuring tile-level interest on mobile.
• product_ctr (rate)
  • Attributed clicks per product impression.
• product_atc_rate (rate)
  • Attributed add-to-carts per product impression.
• avg_click_position (position)
  • Average position of attributed clicks in the result set.

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Result exposure

• result_appearances (requests)
  • Distinct requests whose results contained the product.
• first_page_appearances (requests)
  • Distinct first-page requests whose results contained the product.
• render_rate (rate)
  • Product impressions divided by result appearances. Low values point to products that rank into the result set but rarely get scrolled into view.
• appearance_ctr (rate)
  • Attributed clicks divided by result appearances.

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Attribution transparency

• deterministic_revenue (USD)
  • Revenue from hard-attributed (deterministic) purchases.
• modeled_revenue (USD)
  • Revenue from modeled attribution.
• deterministic_revenue_pct (rate)
  • Deterministic revenue as a share of total attributed revenue.
• deterministic_clicks (clicks)
  • Clicks from hard-attributed (deterministic) events.

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Dimensions

• product_family: Canonical product family the product belongs to. Products without an active canonical family fall back to their own product ID, so every row has a value. Use in GROUP BY to roll performance up across a family (for example, all colors of the same style); auto-includes product_family_name in results. You cannot filter on product_family in WHERE, and TIMESERIES is not supported when it is the only grouping key.
• 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.
• device_type: Device category.
• variant_id: Variant ID.
• shopping_channel: The shopping channel (web, app, or retail). Resolves to retail whenever the row has a retail_location_id; otherwise reports the raw channel from the request.
• retail_location_id: Retail location ID for the purchase. NULL on non-retail orders. Use retail_location_id IS NULL to exclude retail activity, or filter by a specific ID to scope to one store.
• locale: Storefront locale code active for the request (e.g., en, fr, pt-br).
• currency: ISO 4217 currency code applied to the request (e.g., USD, EUR).
• session_returning: Session type — new or returning.
• customer_state: Whether the shopper is authenticated — signed_in or guest.
• customer_returning: Customer type — new or returning, based on prior order count.
• b2b_company: Shopify B2B company location identifier for the signed-in company account.

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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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Examples

FROM products
SHOW SUM(total_sales)
GROUP BY product_id
SINCE -7d

FROM products
SHOW COUNT_DISTINCT(view_sessions)
GROUP BY marketing_campaign
SINCE this_month

FROM products
SHOW SUM(total_sales)
GROUP BY product_attributes.color
SINCE past_30_days

FROM products
SHOW SUM(total_sales)
GROUP BY product_family
SINCE -30d

FROM products
SHOW SUM(revenue)
GROUP BY product_id
WHERE retail_location_id = 'store-123'
SINCE -7d

FROM products
SHOW SUM(total_sales)
WHERE retail_location_id IS NULL
SINCE -7d

FROM products
SHOW product_impressions
GROUP BY product
SINCE -30d

FROM products
SHOW hover_rate
SINCE -30d
COMPARE TO previous_period

FROM products
SHOW product_ctr
GROUP BY TOP 20 product
HAVING product_impressions >= 500
SINCE -30d

FROM products
SHOW render_rate
GROUP BY product_family
HAVING result_appearances >= 1000
SINCE -30d

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Next steps

• LayersQL syntax
• LayersQL functions
• Datasets overview