Python

Retail Store

Scenario:

A retail store company is analyzing their sales and restocking of items throughout the year
Information includes category, region, inventory level, etc.
The data was cleaned, formatted, analyzed, and visualized using python including the pandas, matplotlib, and numpy libraries for analysis
This data set was provided by Kaggle and the license can be found here

Questions:

Questions answered:

The most profitable product sold is the grocery category due to recurring purchases by people and is the most demanded
- The next most profitable is clothing, followed by electronics, then toys, then furniture as the lowest for profits (bought seldomly)
The most demanded item, is again groceries
- This is followed by toys, electronics, then furniture
  - Curious that demand alone does not match profitability
The most sold item in the retail store is groceries again
- This is followed by clothing, electronics, toys, then furniture
The most purchased item is again groceries having a total of

Recommendations:

May want to market towards groceries more since that is the vastly highest performing category for the store
- Market to clothing as well since that does the second best in a lot of categories
May want to run a sale on furniture and ads, so people are aware of their availability, high quality, and reasonable pricing
- Could possibly sell furniture as a set with the option of buying items per diem in the case someone needs just a chair for instance
  - Furniture is the most expensive item for people to buy (rightfully so if it is quality) bu that may be a determining factor of low sales
Electronics are the third most profitable category
- could be increased by offering electronics insurance, running sales, or price matching competition so the customers feel just about their purchases

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