Big Data and Business Analytics
Essay by Paras Khushiramani • January 14, 2018 • Case Study • 905 Words (4 Pages) • 1,108 Views
NOM :
PRENOM :
UB :
“Big Data and Business Analytics”
Customer Analysis Report
QUESTIONS:
Store Overview
[pic 1]
The Store Overview section depicts sales contribution by region.
1. By looking at the pie chart, who had the highest regular sales and who had the lowest?
a. The US Atlantic Coast had the highest regular sales and US Northeast had the lowest regular sales.
2. Click on various pie widgets in the pie chart to view regions and states to see specific cities sales performance relative to available square footage. Which State in the US Atlantic Coast had the highest regular sales? Which state had the lowest?
a. Within the US Atlantic Coast, the state with the highest regular sales was New Jersey, the state with the lowest was Washington DC
3. Which cities are underperforming based on sales per square foot?
a. Based on a square foot of 120,000 + in the US Atlantic Region, the stores underperforming are Greenville, Norfolk, Saratoga Springs and New Hartford, Chattanooga, Washington.
4. Use the store square space filter to filter out the highest store square spaces.
a. From 54,814 – 120,893 square feet, the stores underperforming include New Hartford, Chattanooga and Washington
Store Performance
Click on the next tab called Store Performance. This tab allows you to identify high- and under-performing stores. Analyze them by location, type, age and merchandise categories.
1. Use the Store Location Type filter to choose which stores you want to see. Choose Mall.
2. Which store has the best electronics sales?
- Boston has the best electronic sales with $64.00
[pic 2]
3. Filter on Store Age, which is the oldest?
- Without filter
[pic 3]
Store Number : 2, Sanibel is the oldest store amongst all.
- With filter - Mall
[pic 4]
In the category of “Mall”, Store number - 24 Nashville is now 24 years old and is the oldest store!
4. Look at the report by each store type do you see any trends?
[pic 5]
We are observing a growth and spike in sales of the next day,
- 16 January, 23 January and 30 January are observed as the best performing days (Where the sales is highest)
- Also, immediate next day for the performing day, we are observing a huge spike in sales.
[pic 6]
- Major sales are observed on Saturdays and Sundays are observed as dip in sales.
Customer Segment Analysis
Click on the Customer Segment Analysis tab. This section shows how customers are shopping.
Notice how each customer segment appears to shop departments differently.
· Segment 1 spends across six areas, with the most money being spent on Men's Apparel.
· Segment 2 spends more on Electronics.
· Segment 3 spends the least overall and only shops four departments.
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