The platform provides pre-configured metric recipes that implement common use cases for both LayersQL and Imported metrics.
Dashboard metric recipes
When you create a new store, Layers automatically provisions a set of default dashboard metrics on the Overview dashboard. These metrics give you an at-a-glance summary of key performance indicators without any manual setup.
Dashboard recipes include aggregate metrics for search, collections, orders, revenue, image search, similar products, and block recommendations. They are displayed as cards or tables depending on the metric type.
Block analytics dashboard recipes
The following recipes track how your recommendation blocks perform. They are added to the Overview dashboard automatically for all stores.
Block Impressions (30d) — Card
Total number of block recommendation requests over the last 30 days.
Block Revenue (30d) — Card
Total revenue attributed to block recommendations over the last 30 days.
Block Conversion Rate (30d) — Card
Percentage of block recommendation requests that resulted in an add to cart over the last 30 days.
Block Click Sessions (30d) — Card
Unique sessions where a product from block recommendations was clicked over the last 30 days.
Top Blocks (30d) — Table
Your most-requested recommendation blocks over the last 30 days, ranked by request volume.
Top Blocks by Revenue (30d) — Table
Recommendation blocks generating the most revenue over the last 30 days.
Geographic dashboard recipes
These recipes show where search demand is concentrated geographically. They use the geo_bar chart type, which renders a ranked horizontal bar chart and resolves two-letter country codes (for example, US) into full country names (United States). Bars are sorted in descending order by search volume, and LIMIT 12 keeps the chart readable on dashboard tiles.
Searches by Country (30d) — Geo bar
Search request volume grouped by shopper country over the last 30 days. Use this to identify the markets driving the most search demand.
Searches by State/Region (30d) — Geo bar
Search request volume grouped by shopper state or region over the last 30 days. Use this to spot regional demand within the countries you serve.
Geographic recipes query the search (text) dataset and rely on the geo_country and geo_state fields captured with each search request. Rows without geo data are excluded. Filter usage dashboard recipes
These recipes surface how shoppers use filter facets on collection pages. They query the collections dataset and rely on the shopper-applied filter_property and filter_value dimensions. Transform-injected filters and the built-in collection scope are excluded so the counts reflect facet interactions, not the base collection.
Filter usage by facet (30d) — Bar
How often shoppers apply each filter facet across collections over the last 30 days. A request that uses several facets counts once per facet, so this ranks facets by reach rather than deduplicating requests.
Filter values by facet (30d) — Table
Which values shoppers pick within each filter facet over the last 30 days. Use this to see whether specific colors, sizes, or price bands drive facet usage.
Zero-result filters by value (30d) — Table
Filter selections that returned no products over the last 30 days, by facet and value. Use this to find dead-end combinations to prune from your facet configuration or fill with catalog work.
Product engagement dashboard recipes
These recipes summarize shopper interaction with product tiles. They query the products dataset and depend on product_impression, product_hover, and product_touch events emitted by the Storefront Pixel or sent through the Tracking API.
Product Impressions (30d) — Card
Total tracked product impression events over the last 30 days, with the previous-period delta.
Top Products by Impressions (30d) — Table
Products ranked by tracked impression events over the last 30 days.
Product Hover Rate (30d) — Card
Tracked product hovers divided by impressions over the last 30 days. Indicates how often shoppers explore tiles on desktop.
Product Touch Rate (30d) — Card
Tracked product touches divided by impressions over the last 30 days. Indicates tile engagement on mobile.
LayersQL metric recipes
Total Sales (7 days)
Revenue tracked by Layers over the last 7 days. Use for merchandising based on search-driven conversions.
Total Sales - Variant Level (7 days)
Revenue tracked by Layers at the variant level. When used with variant breakouts, variant tiles sort by their individual sales while product tiles sort by total product sales.
Total Quantity (7 days)
Number of items purchased in the last 7 days. Ideal for identifying high-volume products.
View Sessions (7 days)
Unique product view sessions in the last 7 days. Track product visibility and interest.
Cart Sessions (7 days)
Unique add-to-cart sessions in the last 7 days. Measure purchase intent.
Trending metric recipes
These recipes weight recent sales more heavily than older ones so ranking reacts quickly to shifts in what shoppers are buying. Use them in a sort order when a flat trailing window (like 7-day or 30-day units) hides products whose sales are picking up right now. They only make sense once your store has enough recent purchase history for a short-horizon window to reliably predict next week’s sales. Layers gates the Trending measures in the sort metric picker on that check.
Trending units (7-day half-life, 28 days)
Units sold in the last 28 days where each sale loses half its weight every 7 days. Yesterday’s units count in full, units from a week ago count half, units from two weeks ago count a quarter. Use to surface fast-moving products without being fooled by month-old sales.
Trending units (14-day half-life, 56 days)
Same shape as the 7-day variant but with a longer memory. Recent sales still dominate, but slow-and-steady sellers aren’t shut out. Use for catalogs with steadier turnover where a 7-day half-life feels too jumpy.
Units momentum (7d vs prior 7d)
Ratio of the last 7 days of units sold to the 7 days before. Values above 1 mean the product is accelerating, values below 1 mean it’s cooling off. Pair with a threshold on prior-period units (default 100) so a product with a single unit last week can’t leapfrog established sellers.
Imported (ShopifyQL) metric recipes
Return Rate (7 days) - Refresh: Daily
Percentage of returned items from Shopify. Identify products with quality or sizing issues.
Average Sales Price (7 days) - Refresh: Daily
Average order value after discounts. Understand actual selling prices vs. list prices.
Revenue (7 days) - Refresh: Daily
Net sales (sales minus returns) from Shopify. Authoritative revenue for financial merchandising.
Sales Velocity - Refresh: Daily
Units sold per hour from 7-day Shopify data. Track product momentum and trending items.
These recipes are available in your Layers dashboard. Go to the Metrics section and select from the recipe library to install and customize them for your specific requirements.
