07 Customer segmentation.sql

-- CUSTOMER SEGMENTATION

-- rfm_buckets
-- 1. Calculate RFM scores
WITH RecencyScore AS (
    SELECT customer_unique_id,
           MAX(order_purchase_timestamp) AS last_purchase,
           NTILE(5) OVER (ORDER BY MAX(order_purchase_timestamp) DESC) AS recency
    FROM orders
        JOIN customers USING (customer_id)
    WHERE order_status = 'delivered'
    GROUP BY customer_unique_id
),
FrequencyScore AS (
    SELECT customer_unique_id,
           COUNT(order_id) AS total_orders,
           NTILE(5) OVER (ORDER BY COUNT(order_id) DESC) AS frequency
    FROM orders
        JOIN customers USING (customer_id)
    WHERE order_status = 'delivered'
    GROUP BY customer_unique_id
),
MonetaryScore AS (
    SELECT customer_unique_id,
           SUM(price) AS total_spent,
           NTILE(5) OVER (ORDER BY SUM(price) DESC) AS monetary
    FROM orders
        JOIN order_items USING (order_id)
        JOIN customers USING (customer_id)
    WHERE order_status = 'delivered'
    GROUP BY customer_unique_id
),
-- 2. Assign each customer to a group
RFM AS (
    SELECT last_purchase, total_orders, total_spent,
        CASE
            WHEN recency = 1 AND frequency + monetary IN (1, 2, 3, 4) THEN "Champions"
            WHEN recency IN (4, 5) AND frequency + monetary IN (1, 2) THEN "Can't Lose Them"
            WHEN recency IN (4, 5) AND frequency + monetary IN (3, 4, 5, 6) THEN "Hibernating"
            WHEN recency IN (4, 5) AND frequency + monetary IN (7, 8, 9, 10) THEN "Lost"
            WHEN recency IN (2, 3) AND frequency + monetary IN (1, 2, 3, 4) THEN "Loyal Customers"
            WHEN recency = 3 AND frequency + monetary IN (5, 6) THEN "Needs Attention"
            WHEN recency = 1 AND frequency + monetary IN (7, 8) THEN "Recent Users"
            WHEN recency = 1 AND frequency + monetary IN (5, 6) OR
                recency = 2 AND frequency + monetary IN (5, 6, 7, 8) THEN "Potentital Loyalists"
            WHEN recency = 1 AND frequency + monetary IN (9, 10) THEN "Price Sensitive"
            WHEN recency = 2 AND frequency + monetary IN (9, 10) THEN "Promising"
            WHEN recency = 3 AND frequency + monetary IN (7, 8, 9, 10) THEN "About to Sleep"
        END AS RFM_Bucket
    FROM RecencyScore
        JOIN FrequencyScore USING (customer_unique_id)
        JOIN MonetaryScore USING (customer_unique_id)
)
-- 3. Calculate group statistics for plotting
SELECT RFM_Bucket, 
       AVG(JULIANDAY('now') - JULIANDAY(last_purchase)) AS avg_days_since_purchase, 
       AVG(total_spent / total_orders) AS avg_sales_per_customer,
       COUNT(*) AS customer_count
FROM RFM
GROUP BY RFM_Bucket;


-- repeat_customer_proportion
WITH CustomerOrders AS (
    SELECT COUNT(orders.order_id) AS order_count
    FROM orders JOIN customers USING (customer_id)
    GROUP BY customers.customer_unique_id
)
SELECT
    CASE WHEN order_count > 1 THEN 'repeat' ELSE 'one-time' END AS order_type,
    ROUND(100.0 * COUNT(*) / (SELECT COUNT(*) FROM CustomerOrders), 1) AS proportion
FROM CustomerOrders
GROUP BY order_type;