5a84473213
Replace hardcoded Keboola-specific metrics card in Data Catalog with dynamic Jinja template that renders whatever metric YAMLs exist in docs/metrics/. Add 10 sample e-commerce metric definitions across 4 categories (revenue, customers, marketing, support) that align with the sample data generator tables. Key changes: - MetricParser: new category colors + dynamic sql_* field discovery - _load_metrics_data(): scans docs/metrics/*/*.yml with prod fallback - catalog.html: 240 lines hardcoded HTML -> 35 lines Jinja loop - metric_modal.js: regex-based category class removal, new categories - 21 tests validating YAML schema, parser, and loader
66 lines
2.1 KiB
YAML
66 lines
2.1 KiB
YAML
- name: repeat_purchase_rate
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display_name: Repeat Purchase Rate
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category: customers
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type: ratio
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unit: "%"
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grain: monthly
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time_column: order_date
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table: orders
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tables:
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- orders
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- customers
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expression: "COUNT(DISTINCT CASE WHEN order_number > 1 THEN customer_id END) / COUNT(DISTINCT customer_id)"
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description: "Percentage of customers who made more than one purchase. Key loyalty and retention indicator. Higher rates signal strong product-market fit and customer satisfaction."
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dimensions:
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- customer_segment
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- acquisition_channel
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- product_category
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notes:
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- "Calculated over a rolling 12-month window by default"
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- "Joins orders to customers via customer_id"
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- "Order numbering is based on chronological order per customer"
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- "Excludes cancelled and fully refunded orders"
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synonyms:
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- retention_rate
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- repurchase_rate
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- customer_loyalty_rate
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sql: |
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WITH customer_orders AS (
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SELECT
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customer_id,
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COUNT(*) AS order_count
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FROM orders
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WHERE status = 'completed'
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AND order_date >= CURRENT_DATE - INTERVAL '12 months'
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GROUP BY 1
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)
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SELECT
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ROUND(
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COUNT(CASE WHEN order_count > 1 THEN 1 END) * 100.0
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/ COUNT(*), 2
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) AS repeat_purchase_rate_pct,
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COUNT(*) AS total_customers,
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COUNT(CASE WHEN order_count > 1 THEN 1 END) AS repeat_customers
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FROM customer_orders
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sql_by_channel: |
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WITH customer_orders AS (
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SELECT
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o.customer_id,
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c.acquisition_channel,
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COUNT(*) AS order_count
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FROM orders o
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JOIN customers c ON o.customer_id = c.customer_id
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WHERE o.status = 'completed'
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AND o.order_date >= CURRENT_DATE - INTERVAL '12 months'
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GROUP BY 1, 2
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)
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SELECT
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acquisition_channel,
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ROUND(
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COUNT(CASE WHEN order_count > 1 THEN 1 END) * 100.0
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/ COUNT(*), 2
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) AS repeat_rate_pct,
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COUNT(*) AS total_customers
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FROM customer_orders
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GROUP BY 1
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ORDER BY 2 DESC
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