using RFM 0239_13062023

With_RFM.sql

@@ -0,0 +1,37 @@
+-- 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 using with clause
+DROP TABLE IF EXISTS #RFM
+;WITH RFM AS
+(
+	SELECT CUSTOMERNAME, 
+		sum(sales) AS MonetaryValue, 
+		avg(sales) AS AverageMonetaryValue, 
+		count(ORDERNUMBER) AS Frequencey, 
+		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
+),
+final_RFM AS
+(
+	SELECT *,
+		NTILE(4) OVER(ORDER BY Recency DESC) AS RFM_Recency,
+		NTILE(4) OVER(ORDER BY Frequencey) AS RFM_Frequencey,
+		NTILE(4) OVER(ORDER BY AverageMonetaryValue) AS RFM_Monetary
+	FROM RFM
+)
+SELECT *,
+	RFM_Recency + RFM_Frequencey + RFM_Monetary AS RFM_total,
+	CAST(RFM_Recency AS varchar) + CAST(RFM_Frequencey AS varchar) + CAST(RFM_Monetary AS varchar) RFM_Total_String
+	INTO #RFM
+FROM final_RFM
+
+SELECT * FROM #RFM