overall_RFM_insights 0237_13062023

RFM_sales.sql

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+-- RFM(Recency Frequent Monetary)
+-- Recency - Last order date
+-- Requent - count of total orders
+-- Monetary - total spend
+
+-- show complete dataset
+use bharath;
+SELECT * FROM dbo.sales_data
+
+-- show the distinct values of some common dimensions
+SELECT DISTINCT status FROM sales_data -- 6 
+SELECT DISTINCT year_id FROM sales_data -- 3
+SELECT DISTINCT PRODUCTLINE FROM sales_data --7
+SELECT DISTINCT MSRP FROM sales_data -- 80 huge plotting
+SELECT DISTINCT COUNTRY FROM sales_data -- 19
+SELECT DISTINCT TERRITORY FROM sales_data -- 4
+SELECT DISTINCT DEALSIZE FROM sales_data -- 3
+
+-- sales of all the products 
+-- group the sales by products and order the data by revenue as desc
+SELECT PRODUCTLINE, sum(sales) AS REVENUE
+FROM sales_data
+GROUP BY PRODUCTLINE
+ORDER BY 2 DESC;
+
+-- revenue with the status of product
+SELECT STATUS, sum(sales) AS REVENUE
+FROM sales_data
+GROUP BY STATUS
+ORDER BY 2 DESC;
+
+-- year with maximum sales of the product
+SELECT YEAR_ID, sum(sales) AS REVENUE
+FROM sales_data
+GROUP BY YEAR_ID
+ORDER BY 2 DESC;
+
+-- 2005 - least
+-- 2003 - modest
+-- 2004 - highest
+
+SELECT DISTINCT MONTH_ID FROM sales_data
+WHERE YEAR_ID = 2005; -- sales for only 5 months
+
+SELECT DISTINCT MONTH_ID FROM sales_data
+WHERE YEAR_ID = 2004
+ORDER BY MONTH_ID ASC;  -- sales for all months made it the highest sales
+
+-- revenue based on the dealsize
+SELECT DEALSIZE, sum(sales) AS REVENUE
+FROM sales_data
+GROUP BY DEALSIZE
+ORDER BY 2 DESC; -- with medium dealsize as highest
+
+-- maximum revenue earned in each month for the 3 years
+SELECT MONTH_ID, sum(sales) AS REVENUE, count(ORDERNUMBER) AS ORDER_COUNTS
+FROM sales_data
+GROUP BY MONTH_ID
+ORDER BY 2 DESC; -- November best month of sales
+
+-- for 2004
+SELECT MONTH_ID, sum(sales) AS REVENUE, count(ORDERNUMBER) AS ORDER_COUNTS
+FROM sales_data
+WHERE YEAR_ID = 2004
+GROUP BY MONTH_ID
+ORDER BY 2 DESC;  -- November best month of sales
+
+-- for 2005
+SELECT MONTH_ID, sum(sales) AS REVENUE, count(ORDERNUMBER) AS ORDER_COUNTS
+FROM sales_data
+WHERE YEAR_ID = 2005
+GROUP BY MONTH_ID
+ORDER BY 2 DESC;  -- May is the best month of sales
+
+-- for 2003
+SELECT MONTH_ID, sum(sales) AS REVENUE, count(ORDERNUMBER) AS ORDER_COUNTS
+FROM sales_data
+WHERE YEAR_ID = 2003
+GROUP BY MONTH_ID
+ORDER BY 2 DESC;   -- November is the best month of sales
+
+-- November is the best overall best month of sales with highest orders
+-- checking the products that are sold during this highest sales month
+SELECT MONTH_ID, PRODUCTLINE, sum(sales) AS REVENUE, count(ORDERNUMBER) AS ORDER_COUNTS
+FROM sales_data
+WHERE MONTH_ID = 11    -- add YEAR_ID in where clause to see products for each year
+GROUP BY MONTH_ID, PRODUCTLINE
+ORDER BY 3 DESC;
+
+-- 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
+SELECT max(ORDERDATE) FROM sales_data  -- max order date
+--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
+
+
+
+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
+
+
+
+--	Most often sold products
+SELECT DISTINCT ORDERNUMBER, STUFF(
+	(SELECT ',' + PRODUCTCODE
+	FROM sales_data  AS p
+	WHERE ORDERNUMBER IN
+		(
+		SELECT ORDERNUMBER 
+		FROM
+			(
+				SELECT ORDERNUMBER, COUNT(*) AS quantity
+				FROM sales_data
+				WHERE STATUS = 'shipped'
+				GROUP BY ORDERNUMBER
+			) AS b
+		WHERE quantity = 9
+	)
+	AND p.ORDERNUMBER = s.ORDERNUMBER
+	FOR XML PATH('')), 1, 1, '') AS ProductCodes
+FROM sales_data AS s
+ORDER BY ProductCodes DESC