RFM_views 0238_13062023

View_RFM.sql

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+-- Best Customer by using RFM Analysis
+-- RFM(Recency-Frequency-Monetary) an indexing technique used to segment customers based on their past purchase history
+-- Recency - how long their last purchase was
+-- Frequent - how often they purchase 
+-- Monetary - how much spent
+
+-- Best Customer from sales data by creating view for each individual table
+CREATE VIEW RFM_C 
+AS
+	SELECT CUSTOMERNAME, 
+			sum(sales) AS MonetaryValue, 
+			avg(sales) AS AverageMonetaryValue, 
+			count(ORDERNUMBER) AS Frequency, 
+			max(ORDERDATE) AS LastOrderDate,
+			(SELECT max(ORDERDATE) FROM sales_data) AS MaxOrderDate,
+			DATEDIFF(DD, max(ORDERDATE), (SELECT max(ORDERDATE) FROM sales_data)) AS Recency -- (last-max) how long the purchase is been i.e difference of the last and max date
+			-- less recency indicated recent orders
+			-- NTILE() function helps to divide the records into equal or buckets assigning a number to each bucket from 1 
+	FROM sales_data
+	GROUP BY CUSTOMERNAME
+-- DROP VIEW RFM_C
+-- SELECT * FROM RFM_C -- RFM-C
+
+CREATE VIEW total_RFM 
+AS
+	SELECT *,
+		NTILE(4) OVER(ORDER BY Recency DESC) AS RFM_Recency,
+		NTILE(4) OVER(ORDER BY Frequency) AS RFM_Frequency,
+		NTILE(4) OVER(ORDER BY MonetaryValue) AS RFM_Monetary
+	FROM RFM_C
+-- DROP VIEW total_RFM
+-- SELECT * FROM total_RFM -- total_RFM
+
+CREATE VIEW RFM_S
+AS
+	SELECT *,
+		RFM_Recency + RFM_Frequency + RFM_Monetary AS RFM_total,
+		CAST(RFM_Recency AS varchar) + CAST(RFM_Frequency AS varchar) + CAST(RFM_Monetary AS varchar) RFM_Total_String
+	FROM total_RFM
+-- DROP VIEW RFM_S
+SELECT * FROM RFM_S -- RFM_S
+
+SELECT CUSTOMERNAME, RFM_Recency, RFM_Frequency, RFM_Monetary,
+	CASE
+		WHEN RFM_total BETWEEN 3 AND 5 THEN 'Lost Customers' -- didn't buy anything
+		WHEN RFM_total BETWEEN 6 AND 7 THEN 'Slipping customers' -- big buyers havent purchased lately
+		WHEN RFM_total = 8 THEN 'New Customers'
+		WHEN RFM_total = 9 OR RFM_total > 9 THEN 'Active' -- often buyers
+	END RFM_Segment
+FROM RFM_S