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Statistics data analysis
- 1. Shopping Store DataAnalysis - Statistics Division A – Group 8 Anup Vaibhav Karthikeyan Karthik Raghu Shweta
- 2. Scenario 1 –Gender Wise Distribution of Previous Amount Spent 4500 4000 Previous Amount Spent 3500 3000 2500 Females Previous Spent 2000 Males Previous Spent 1500 1000 500 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Customers
- 3. Scenario 1 –Gender Wise Distribution of Current Amount Spent 7000 6000 Current Amount Spent 5000 4000 Females Amount Spent 3000 Males Amount Spent 2000 1000 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Customers
- 4. Scenario 2 –Comparative Analysis of Amount Spent by Customers - Previous and Now 1250 1206 1200 1150 Total Number of Mean Amount 1100 1060 Previous 1050 Customers - Spent 1000 697 950 Mean Previous Spent Mean Current Spent 1200 1053 1518 1600 1000 Mean Amount Spent 1400 780 Mean Amount Spent 800 1200 1065 1000 600 800 400 600 400 200 200 0 0 Mean Previous Spent Mean Current Spent Mean Previous Spent Mean Current Spent Total Number of Lower Spending Customers - 294 Total Number of Higher Spending Customers - 403
- 5. Scenario 3 –Spending Pattern Analysis Based on Proximity Spending Pattern for the Spending Pattern for the Customer Customer living Far living Near 80 250 70 200 60 Customers 50 150 40 100 30 20 50 10 0 0 0 250 750 1250 1750 2250 2750 3250 3750 4250 Current Amount Spent Mean Mode Standard Deviation Mean Mode Standard Deviation 1590 350 1182 1067 250 812
- 6. Scenario 3 –Interpretation Far Near • Customer living far • Customer near contribute contribute around 38% of around 62% of the total the total revenue. revenue. • The probability of a person • The probability of a person spending more than 1725 spending more than 1127 is 2.5%. is 2.5%. • The probability of a person • The probability of a person spending less than 1450 is spending less than 1000 is 2.5%. 2.5%. • Hence, the population • Hence, the population average lie between 1450 average lie between 1000 and 1725. and 1127.
- 7. Scenario 4 –Spending Pattern Analysis Based on Previous and New Customers New Customer Amount Spent Previous Customer Amount Spent 100 200 90 180 80 160 Number Of Customers 70 140 60 120 50 100 40 80 30 60 20 40 10 20 0 0 50 350 850 1350 1850 2350 2850 3350 3800 4750 0 250 750 1250 1750 2250 2750 3250 3750 4250 4750 5250 5750 Amount Spent Mean Mode Standard Deviation Mean Mode Standard Deviation 1234 350 862 1211 250 1007
- 8. Scenario 4 –Interpretation Previous New • Customer living far • Customer near contribute contribute around 70% of around 30% of the total the total revenue. revenue. • The probability of a person • The probability of a person spending more than 1286 spending more than 1331 is 2.5%. is 2.5%. • The probability of a person • The probability of a person spending less than 1136 is spending less than 1136 is 2.5%. 2.5%. • Hence, the population • Hence, the population average lie between 1136 average lie between 1136 and 1286. and 1331.
- 9. Scenario 3 &4 – Inferences • Offer loyalty program for high paying customers . • Introduce free home delivery on purchase of above 1500 • Offer special schemes for new customers. • Since, elder customer contribute less around 30 %, we need to provide a value packs catering to them. • For the young customer, the contribute 70%, hence, we need to work on retain them while further looking to improve the numbers
- 10. Scenario 5 –Spending Pattern Analysis of Previous Customers Previous Customers spending Previous Customers spending more less Number of Customer 403 294 Avg Age 43.29 44.37 Male 202 138 Gender Female 201 156 Own 222 147 Home Rented 181 147 Married 219 150 Marital Stat Otherwise 184 144 Close 272 219 Proximity Far 131 75 Avg Salary 59943.18 55465.99 0 193 145 1 93 77 Children 2 68 41 3 49 31 Avg PrevSpent 1065.80 1053.17 Avg Catalogs 18 12 Avg Amt Spent 1518.17 779.78
- 11. Scenario 6 –Spending Pattern Analysis of Customers Based on Age Old New Old New Old New Age Mean Prev Mean Amt Mean Amt Mid F F Mean Sal Mean Sal spent spent spent LL UL 20 30 25 176 109 35452 31875 619.5 663.1 724.9 30 40 35 140 59 72633 68144 1277.6 1496.5 1586.2 40 50 45 155 57 65505 65744 1132.9 1329.0 1595.4 50 60 55 112 41 63362 57388 1183.8 1333.1 1420.5 60 70 65 76 24 64503 54129 1309.0 1477.2 1427.4 70 80 75 38 13 50105 57346 1147.0 1244.8 1511.7
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