Comprehensive-market-data-analysis

An comprehensive data analysis of a particular market and its customers.

The Dataset

The data of this project is available in the Excel file sales.xlsx and the descriptions of the columns of the dataset are given in the table below.

Column	Description
InvoiceNumber	A 6-digit number uniquely assigned to each invoice. If the beginning of this number starts with the letter C, it means that the invoice has been canceled.
ProductCode	A 5-digit number that is uniquely assigned to each type of product.
ProductName	Product's name
Quantity	The number of orders of a product type in the invoice
InvoiceDate	Invoice creation date
UnitPrice	The price of a product type per unit
CusotmerId	A 5-digit number that is uniquely assigned to each customer.
Country	The name of the customer's country of residence

This project has 5 steps:

1. Data preprocessing: A series of preprocessing steps are performed on the entire data, such as handling the missing data
2. Exploration: I answer a series of high-level questions and obtain an intuitive view of the company's financial information.
3. Study of target markets: I will analyze different locations of sale and supply and I will check which countries, despite having many customers, experience little sales.
4. Customer value: Using the RFM practical criteria, I divide the company's customers into 7 categories, each of which has its meaning and behavior in terms of marketing.
5. Customer retention rate analysis: What percentage of customers buy from this company in the following months after their first purchase.?

I only used Numpy, Pandas, Matplotlib, and Seaborn in this project