애널리틱스, 빅데이터_판매 예측모델 프로젝트 2_Columbia Univ_Project Deliverable_Part 2

 1  애널리틱스, 빅데이터_판매 예측모델 프로젝트 2_Columbia Univ_Project Deliverable_Part 2-1
 2  애널리틱스, 빅데이터_판매 예측모델 프로젝트 2_Columbia Univ_Project Deliverable_Part 2-2
 3  애널리틱스, 빅데이터_판매 예측모델 프로젝트 2_Columbia Univ_Project Deliverable_Part 2-3
 4  애널리틱스, 빅데이터_판매 예측모델 프로젝트 2_Columbia Univ_Project Deliverable_Part 2-4
 5  애널리틱스, 빅데이터_판매 예측모델 프로젝트 2_Columbia Univ_Project Deliverable_Part 2-5
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애널리틱스, 빅데이터_판매 예측모델 프로젝트 2_Columbia Univ_Project Deliverable_Part 2에 대한 자료입니다.
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PROJECT DELIVERABLE #2
What is the recommended action and how do you expect the action to affect business or organizational goals?
BigMart must carefully consider changing its business strategy by looking at the sales pattern the sales prediction model shows. The most important variables to look at are Item MRP (the listed price of items), Outlet Type, and Item Fat Content (the fat content of an item being low fat or regular).
(* The names of the variables and their descriptions are described in Appendix)
Most of the company’s customers are supermarket shoppers rather than grocery shoppers. In addition, they are health conscious, and the majority of the products they consume is high quality (or high-priced) products. Following the information provided by our model, we suggest that BigMart can increase its total sales by incorporating the following three elements into its business strategy: offering the high-priced, high-quality products as its main products, increasing the number of large supermarkets, and establishing the brand image of a premium supermarket (similar example would be Wholefoods). This strategy can be fulfilled by closing grocery stores and establishing more supermarkets instead, filling in the supermarkets with health-conscious and high-standard products such as organic, low-fat and premium products. Finally, with these changes, the company’s marketing strategy would be to establish a brand image of an upscale premium supermarket company. This business strategy will enhance the company’s sales.
What are the conclusions of your data analysis that support your recommendation?
After applying our sales prediction model, it is found that BigMart’s major revenues will come from the sales of their large supermarkets (specifically supermarket type 1, 2 and 3).
G S1 S1 S2 G S3 S1 S1 S1 S1
* Figure 1. G (grocery store), S1, 2, and 3 (supermarket type 1, 2, and 3 respectively)
Figure 1 above shows that almost all of the sales are coming from supermarkets with the sales of the biggest store, type 3, at the highest while the sales of grocery stores being minute. It can be inferred that BigMart’s customers prefer supermarkets which is more convenient because the stores are more spacious, and the customers can find variety of products that are available in large quantity at one place. Furthermore, the customers are found to be health conscious and have high living standards (or at least have high demand for high-priced goods).
* Figure 2. Predicted sales (predFinalT) in terms of listed price of products (Item_MRP)
Figure 2 shows the highest predicted sales gathered around the items with the price of $200 which is close to the maximum price of all products. Moreover, the customers care about healthy choices for their foods. Figure 3 below shows much higher demand for low fat foods.