In this project, I have explored a sales dataset and performed various analyses and drew insights from customer’s past purchase behavior by RFM technique customer segmentation using SQL and built a sales dashboard in Tableau. At the end, provided business solutions by analysing the segments of customers and products to improve the sales.
Recency
Frequency
Monetary
Sneak Peek into the RFM Segmentation Technique.
SELECT CUSTOMERNAME, rfm_recency, rfm_frequency, rfm_monetary,
CASE
WHEN rfm_cell_string IN (111, 112 , 121, 122, 123, 132, 211, 212, 114, 141, 221) THEN 'Lost Customer' -- lost customer.
WHEN rfm_cell_string IN (133, 134, 143, 244, 334, 343, 344, 144) THEN 'Slipping Away' -- big spender, slipping away.
WHEN rfm_cell_string IN (311, 411, 331, 421, 412) THEN 'New Customer' -- new customer.
WHEN rfm_cell_string IN (222, 223, 233, 322, 232, 234) THEN 'Potential Churners' -- probably leave the service.
WHEN rfm_cell_string IN (323, 333,321, 422, 332, 432, 423) THEN 'Active' -- customers who buy often at low price.
WHEN rfm_cell_string IN (433, 434, 443, 444) THEN 'Loyal' -- customers who buy regularly at high price.
END
FROM #rfm
After Customer Segmentation and Products Grouping using SQL, We will be having different segments of customers and groups of sold together products. So our aim is to bring back Customers and increase sales of brought together Products. I will be providing general business solutions for retail sales along with our Vehicle Product Sales in data.