Predicting top 15 items using statistics and data analysis for already selected category that would provide largest incremental profit from a price investment

1. Walmart Assignment
Sanjeev Ahuja
Graduate | Business Analytics
University of Texas at Dallas
Top 15 items
that would
provide the
largest
incremental
profit from a
price
investment
August 26th, 2018

2. Exploratory
Data Analysis
usingTableau
Data
Preparation
and model
building in R
Model Analysis
and insights
aboutTop 15
items
Process Overview
Stage 1 Stage 2 Stage 3

3. Exploratory
Data Analysis
usingTableau
Assumptions
Stage 1:
• Profit = Sales (value) – Product Cost +Vendor Allowance
• Relationship among columns
• Each store can have multiple sub category and each sub
category can be associated with multiple stores
• Each item is associated with one and only one sub category
• Each sub category can have any number of item numbers
associated with it
• Each item number belongs to one and only one product planning
group
• Each Planning group can have multiple item number associated
under it
• Degenerate columns
• Price Gap Category -Target
• Price Gap Category - Actual
• Price Gap Item -Target
• Stores are allocated based on Zone and Store Cluster - Assortment

4. Overview of Profit : YoY profits up by 23%
Trends for Sales(Units) and Profit reflects a higher slope for 2016 than 2017

5. 4413 store number was introduced in 2016 and 700, 4449 were introduced in 2017
Store wise profits reflect similar results to overall profits

6. 70172066 item was introduced in 2017 and is performing better than other items
Profits show YoY increase for most of the items

7. Data
Preparation
and model
building in R
Stage 2:
Data Preparation
• Creating individual categorical variable for Item
andYear
• Hausman test to predicts Fixed Effect model is
better in comparison to Random Effects
• Running the model using Fixed effects using
Least squares dummy variable model
Profit = Sales Unit + Items (dummy variable) +
Year (dummy variable)
• Checking for multicollinearity amongst variables
Model Building: Fixed Effects
• Converting to .csv and importing data to R
• Understanding Data Summary
• Aggregating data basis Item andYear
Model Output: Model predicts with 71.75 % accuracy
• Finding significant items and filtering top 15 items basis their estimates
using output in excel
Top 15 items
No. Item Number
1 70456523
2 70172066
3 70540129
4 70390332
5 1393604
6 1393114
7 1304683
8 70252655
9 70461961
10 70183700
11 70144601
12 70011103
13 70117115
14 70117116
15 70361010

8. Model Analysis
and insights
Analysis of Model Results
• Verification of model output of top 15 items on profits, Sales (Units) and Product
Cost (Value)
Stage 3:
Profit from the identified list of top 15 items was 29% in 2016 and 35% in 2017 of the total profit

9. S No. Item Number
1 70456523
2 70172066
3 70540129
4 70390332
5 1393604
6 1393114
7 1304683
8 70252655
9 70461961
10 70183700
11 70144601
12 70011103
13 70117115
14 70117116
15 70361010
Recommended list of Top 15 items

10. Thank You!

11. APPENDIX

12. In-store campaign promotions have been effective
It appears that other display have higher performance during the year end, end caps perform near mid-year

13. Performance of Marketing Ads for each year with respect to sub-category
Certain sub-categories have been responsive to marketing activities (6600 and 6625) during certain period of the year

14. Performance of Marketing Ads for items and sub-category
No marketing ads were run in 2016, two items (70540129 and 70172066) have been highly responsive to marketing ads

15. Profit based on in-store promotions for each item
Other displays with combination of Aisle and End-caps has been responsive in contribution to profit

16. Not all sub-categories have been profitable across stores
Two sub-categories have been performing better than others across stores

17. Store 4413 was the new store introduced in Competitive Zone – Average and Medium segment in 2016
Profits from sub-category (6600) by items
Not all sub-categories have been profitable across stores…contd.