Metrics

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Overview

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Metric Types

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LayersQL Metrics

• Built using the LayersQL query language
• Powered by Layers’ behavioral analytics data
• Support segmentation by dimensions (country, marketing channel, etc.)
• Real-time computation from search, browse, and interaction events
• Ideal for metrics like views, add-to-carts, and search-driven conversions

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

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Imported (ShopifyQL) Metrics

• Built using full ShopifyQL syntax
• Powered by Shopify’s native sales and analytics data
• Automatically refreshed on a configurable schedule (hourly, daily, weekly)
• Access to Shopify-specific metrics like return rates, net sales, and order values
• Must include product_id in the query results for proper product association

FROM sales
SHOW product_id, returned_quantity_rate
WHERE product_id IS NOT NULL
GROUP BY product_id
SINCE -7d UNTIL today

• The ShopifyQL query must return a product_id column
• Only one metric value column (besides product_id) should be returned
• Queries must specify a refresh frequency: hourly, daily, or weekly

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What you can do with metrics

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In Sort Orders

• Sort by recent conversion rate to surface high-performing products
• Combine sales velocity with inventory levels for intelligent restocking
• Weight revenue metrics alongside engagement metrics for balanced merchandising

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In Merchandising Rules

• Pin products with high return rates to the bottom of collections
• Boost products with strong revenue per view in key collections
• Demote products with declining sales velocity

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Common Metric Use Cases

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Behavioral Metrics (LayersQL)

• View Sessions: Unique sessions where products were viewed
• Cart Sessions: Unique sessions where products were added to cart
• Purchases: Total purchases tracked through Layers
• Conversion Rate: Percentage of viewers who purchased
• Click-Through Rate: Percentage of impressions that resulted in clicks

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Financial Metrics (Imported/ShopifyQL)

• Net Sales/Revenue: Sales minus returns from Shopify data
• Return Rate: Percentage of items returned
• Average Order Value: Average price per transaction
• Sales Velocity: Units sold per time period
• Gross Margin: Profit margins from Shopify financial data

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Common Metric Recipes

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LayersQL Metric Recipes

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

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

FROM products
SHOW COUNT_DISTINCT(view_sessions)
GROUP BY product_id
SINCE -7d

FROM products
SHOW COUNT_DISTINCT(cart_sessions)
GROUP BY product_id
SINCE -7d

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Imported (ShopifyQL) Metric Recipes

FROM sales
SHOW product_id, returned_quantity_rate
WHERE product_id IS NOT NULL
GROUP BY product_id
SINCE -7d UNTIL today

FROM sales
SHOW product_id, average_order_value
WHERE product_id IS NOT NULL
GROUP BY product_id
SINCE -7d UNTIL today

FROM sales
SHOW product_id, net_sales
WHERE product_id IS NOT NULL
GROUP BY product_id
SINCE -7d UNTIL today

FROM sales
SHOW product_id, (net_items_sold / 168) as sales_velocity_per_hour
WHERE product_id IS NOT NULL
GROUP BY product_id
SINCE -7d UNTIL today

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Creating Custom Metrics

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Creating a LayersQL Metric

1. Navigate to Metrics in your Layers dashboard
2. Click “Create Metric”
3. Select “LayersQL” as the metric type
4. Write your LayersQL query following the syntax: FROM → SHOW → GROUP BY → SINCE
5. Optionally add WHERE clauses for filtering or SEGMENT BY for dimensional breakdowns
6. Name your metric and save

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Creating an Imported Metric

1. Navigate to Metrics in your Layers dashboard
2. Click “Create Metric”
3. Select “Imported (ShopifyQL)” as the metric type
4. Write your ShopifyQL query ensuring it includes product_id
5. Set the refresh frequency (hourly, daily, or weekly)
6. Name your metric and save

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Metric Refresh and Updates

• Hourly: Updated every hour for time-sensitive metrics
• Daily: Updated once per day, ideal for most sales metrics
• Weekly: Updated weekly for slower-moving or historical metrics

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Best Practices

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Choosing Between Metric Types

• You need real-time behavioral data from search and browse interactions
• Segmentation by marketing channel or geography is important
• The metric is based on user engagement (views, clicks, searches)

• You need Shopify’s authoritative sales and financial data
• Return rates, refunds, or detailed order information is required
• Daily or periodic updates are sufficient

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Query Optimization

• Keep time windows reasonable (7-30 days) to balance freshness with data volume
• Use WHERE clauses to pre-filter data before aggregation
• For Imported metrics, avoid queries that return excessive rows
• Test queries on a subset of data before deploying to production

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Naming Conventions

• Include the time window in the metric name (e.g., “Sales 7d”, “Returns 30d”)
• Use clear, descriptive names that indicate the metric’s purpose
• Distinguish between LayersQL and Imported metrics in naming when helpful

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Where metrics show up

• Sort Orders: Add metric-based conditions and weights to control product ranking
• Merchandising Rules: Preview live metrics as you pin, boost, or group products
• Analytics Dashboard: Track metric trends over time for performance monitoring
• Product Details: View individual product metric values for manual merchandising

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Learn more

• LayersQL overview
• LayersQL syntax
• LayersQL functions
• LayersQL datasets
• Sort Orders
• Merchandising