Project Description
Customer behavior and loyalty analysis is an important process that helps businesses understand and improve customer relationships. In this project, we will evaluate customer behavior, loyalty and feedback by analyzing various customer and sales data. Our goal is to increase customer loyalty, improve customer experience and optimize sales strategies. This analysis will help marketing teams and managers improve customer relationships and determine business strategies.
Project Usage Areas
This project has several uses for marketing teams, customer relationship managers, and business owners:
Analysis of Customer Behavior: Optimizing marketing strategies by analyzing customers' purchasing habits and preferences.
Loyalty Programs: Creating loyalty programs and evaluating existing programs to increase customer loyalty.
Reviewing Feedback: Improving product and service quality by analyzing customer feedback.
Sales Strategies: Developing effective sales strategies and customer segmentation by analyzing sales data.
Increasing Customer Satisfaction: Analyzing feedback and reviews to increase customer satisfaction.
Dataset Description
The data set to be used in this project includes customer and sales data. The dataset consists of four main files in total:
Customers
CustomerID: Customer ID
CustomerName: Customer name
JoinDate: Join date
Gender: Gender
Country: Country
Sales
SaleID: Sale ID
CustomerID: Customer ID
ProductID: Product ID
SaleDate: Sale date
Quantity: Sales quantity
Price: Selling price
products
ProductID: Product ID
ProductName: Product name
Category: Category
Price: Price
Feedbacks
FeedbackID: Feedback ID
CustomerID: Customer ID
ProductID: Product ID
FeedbackDate: Feedback date
Rating: Evaluation (between 1-5)
Comments: Comments
There are various dirty data problems in this dataset, such as missing data, outlier data, and wrong data type. This is an ideal data set to experience data cleaning and processing processes commonly encountered in real life.
Student Benefits
This project provides many benefits for students:
Data Manipulation: Students develop skills in examining, cleaning, and analyzing data sets.
Using Pandas: They learn to use the data processing and analysis methods of the Pandas library effectively.
Data Cleaning: They gain skills in cleaning missing data, outliers and incorrect data types.
Business Intelligence: By analyzing data sets, they improve their ability to evaluate customer behavior and loyalty and make strategic decisions.
Reporting: Provides skills to effectively report and present analysis results.
Real Life Applications: Provides practical information about data problems and analysis processes encountered in real life.
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