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Walmart weekly sales
- 1. Geeta Nadagouda Walmart Weekly Sales Analysis and Recommendations
- 2. Introduction • What factors drive in the growth of weekly sales? • The analysis will provide further insight to the Retailer identifying relationship strength between various factors like Temperature, Holidays, fuel price etc. with weekly sales to help retailer asses weekly sales impact.
- 3. Goals • Is there any relationship between weekly sales, Temperature, Fuel price and size. • What is the relationship between weekly sales and isholiday? Does holiday Drive weekly sales? • What is the relationship between weekly sales and Temperature/fuel price/size? Does Temperature/fuel price/size drive weekly sales?
- 4. Data Data Description(Variables) • Store: The store number • Size: Size of the Store • Dept: Department of the Store Date: Specifying the Week (Friday of every Week) • Temperature: Average temperature in the region (in ℉) • Fuel Price: Cost of fuel in the region • MarkDown1-5: Anonymized data related to promotional markdowns that Walmart is running. • CPI: Consumer price index • Unemployment: Unemployment rate • IsHoliday: Whether the week is a special holiday week About Data • For Analysis , the data set was historical sales data from 45 Walmart stores between 02/02/2010 and 10/26/2012(143 weeks of sales data) with 423325 Records. • There are missing values. • Categorical variables –Isholiday. • Fuel, Temperature, size are continuous variables. • The data set comes from https://www.kaggle.com/kerneler/starter- walmart-analysis-dataset-d1eaf25c-c/data
- 5. Method • Imported CSV file and Modules into Jupyter Notebook • Data Exploration, Cleaning, and Descriptive Statistics • Checked for Correlation with Pearsonr • Split data into sample populations through conditional filtering • Checked sample population distribution with Histograms • Performed statistical analysis using t-test • Found 95% confidence intervals
- 6. Weekly sales distribution and Descriptive Statistics Mean 15915.00381 Standard Error 34.86952243 Median 7551.22 Mode 0 Standard Deviation 22687.30752 Sample Variance 514713922.5 Minimum -4988.94 Maximum 693099.36 Count 423325
- 7. Data Set Correlation Matrix
- 8. Distribution of Holiday vs Non holiday weekly sales
- 9. t-Test: Two-Sample Assuming Unequal Variances Null Hypothesis : Ho: μ1 - μ2 = 0 Alternative hypothesis : Ha: μ1 - μ2 ≠ 0
- 10. Hypothesis • H₁ There is no significant difference in Weekly sales between Holiday sales and Nonholiday sales. • H₂ There is no significant difference Weekly sales between Low Temperature and High Temperature. • H3 There is no significant difference in Weekly sales between Low fuel cost and high fuel cost. • H4 There is no significant difference in Weekly sales between small store size and big store size.
- 11. RESULTS
- 12. Holiday VS Nonholiday • Reject the null hypothesis. There is significant mean difference between nonholiday and Holiday sales. • With p < 0.05, 95% confidence level, a holiday weekly sales is between 806 and 1439 more than a non holiday sales. NonHoliday Holiday
- 13. Low vs High Temperature • LowTemp = mean < 60F • Hightemp = mean > 60F • Fail to Reject the null hypothesis High Temp Low Temp
- 14. Size small Vs size big of stores(lot area) • Reject the null hypothesis. There is significant mean difference between sizesmall and sizebig sales. • With p < 0.05, 95% confidence level, a big size store weekly sales is between 8899.76 and 9166.87 more than a small size stores. Size big Size Small Mean < 136701.2 Mean > 136701.2
- 15. Low fuel Vs High Fuel cost • Reject the null hypothesis. There is significant mean difference between nonholiday and Holiday sales. • With p < 0.05, 95% confidence level, a low fuel cost , the sales is between -387 and -111 more than High fuel cost. High Fuel Cost Low Fuel Cost Mean < 3.36 Mean > 3.36
- 16. POTENTIAL IMPACT • Holidays Drive weekly sales .So need to buy more products. This will go the business. • Having big space for store has big impact on growing business. Bigger the space, large quantity of products higher the sales. • Giving some promotions while fuel price is high would help in growing business. • High temperature or low temperature has no impact on Business.
- 17. RECOMMENDATIONS Increase Products In holidays 1 Increase Size of store so that more products can be added. 2 Increase promotions when fuel price is high. 3
- 18. Questions?
Editor's Notes
- Compact Observations: 5,508 Midsize Observations: 4,395 Reject the null Hypo that there is no difference between the two populations. With p < .05, there is significant difference between the two populations. The 95% confidence interval is between -189 and -150.
- Compact Observations: 5,508 Midsize Observations: 4,395 Reject the null Hypo that there is no difference between the two populations. With p < .05, there is significant difference between the two populations. The 95% confidence interval is between -189 and -150.