Enhanced Ecommerce products: dimensions & metrics
The most important enhanced ecommerce products dimensions and metrics for GA360 BigQuery export, like product, product sku, product category (enhanced ecommerce), product brand, unique purchases, product revenue, product adds to cart and product detail views.
When entering the product scope you have to verify if enhanced ecommerce is enabled in Google Analytics. If so, youβre safe to use the hits.product
fields. If only βstandardβ ecommerce is measured: use the hits.item
fields.
This example query contains all following Google Analytics enhanced ecommerce products dimensions and metrics. If you only need one dimension or metric, look at the -- comments
in the example query and copy the part you need from the select
clause. Make sure that you also add any additional conditions (in the from
, where
, group by
and order by
) that are necessary to calculate the results correctly.
Enhanced Ecommerce dimensions
- product sku
- product
- product category (enhanced ecommerce)
- product brand
- product variant
Enhanced Ecommerce metrics
- quantity
- unique purchases
- product revenue
- avg. price
- avg. quantity
- buy-to-detail rate
- cart-to-detail rate
- product adds to cart
- product checkouts
- product detail views
- product refunds
- product removes from cart
- refund amount
Example query 1
select
-- product sku (dimension)
productsku as product_sku,
-- product (dimension)
v2productname as product,
-- product variant (dimension)
productvariant as product_variant,
-- product brand (dimension)
productbrand as product_brand,
-- product category (enhanced ecommerce) (dimension)
v2productcategory as product_category_enhanced_ecommerce,
-- unique purchases (metric)
count(hits.transaction.transactionid) as unique_purchases,
-- quantity (metric)
sum(productquantity) as quantity,
-- product revenue (metric)
sum(productrevenue)/1000000 as product_revenue,
-- avg. price
sum(productrevenue)/1000000 / sum(productquantity) as avg_price,
-- avg. qty
sum(productquantity) / count(hits.transaction.transactionid) as avg_quantity
from
`bigquery-public-data.google_analytics_sample.ga_sessions_20160801`,
unnest(hits) as hits,
unnest(product) as product
where
totals.visits = 1
and hits.ecommerceaction.action_type = '6'
group by
product_sku,
product,
product_variant,
product_brand,
product_category_enhanced_ecommerce
order by
product_revenue desc
Example query 2
select
-- product sku (dimension)
productsku as product_sku,
-- unique purchases (metric)
count(case when hits.ecommerceaction.action_type = '6' then hits.transaction.transactionid else null end) as unique_purchases,
-- cart-to-detail rate (metric)
case when count(case when hits.ecommerceaction.action_type = '2' then fullvisitorid else null end) = 0 then 0 else count(case when hits.ecommerceaction.action_type = '3' then fullvisitorid else null end) / count(case when hits.ecommerceaction.action_type = '2' then fullvisitorid else null end) end as cart_to_detail_rate,
-- buy-to-detail rate (metric)
case when count(case when hits.ecommerceaction.action_type = '2' then fullvisitorid else null end) = 0 then 0 else count(case when hits.ecommerceaction.action_type = '6' then hits.transaction.transactionid else null end) / count(case when hits.ecommerceaction.action_type = '2' then fullvisitorid else null end) end as buy_to_detail_rate,
-- product detail views (metric)
count(case when hits.ecommerceaction.action_type = '2' then fullvisitorid else null end) as product_detail_views,
-- product adds to cart (metric)
count(case when hits.ecommerceaction.action_type = '3' then fullvisitorid else null end) as product_adds_to_cart,
-- product removes from cart (metric)
count(case when hits.ecommerceaction.action_type = '4' then fullvisitorid else null end) as product_removes_from_cart,
-- product checkouts (metric)
count(case when hits.ecommerceaction.action_type = '5' then fullvisitorid else null end) as product_checkouts,
-- product refunds (metric)
count(case when hits.ecommerceaction.action_type = '7' then fullvisitorid else null end) as product_refunds
from
`bigquery-public-data.google_analytics_sample.ga_sessions_20160801`,
unnest(hits) as hits,
unnest(product) as product
where
totals.visits = 1
and isimpression is null
group by
product_sku
order by
unique_purchases desc