Customer Transaction Analysis

Author: Hang Vo Thuy Nguyen

📋 Project Description

The Customer Transaction Analysis project uses data analytics for data-driven business decision-making. It seeks to understand customer behavior and sales trends to optimize marketing strategies, enhance customer experiences, and predict future sales performance.

📈 Analysis Process

1. Data Overview

2. Data Preprocessing

3. Exploratory data analysis

3.1 Order, Products, and Customers

3.2 Category

3.3 Sales

3.4 Quantity

3.5 Ship Mode

4. Descriptive Analysis

4.1 Total Orders by States

4.2 Total Orders by quarters and years

4.3 Sales over months and years

4.4 Category sales over quarters and years

4.5 Profit by Quarter and Category

4.6 Time Delivery

4.7 Time Delivery by Ship Mode

4.8 Sales vs Profit per Category

5. Sales Prediction

Use the Pycaret library to compare time-series models and predict sales. Because Pycaret offers a comprehensive time-series modeling solution. It evaluates numerous models with diverse metrics and identifies the optimal choice.

6. Customer Segmentation

Customer Segmentation is the process of dividing customers into groups that are similar in several characteristics. In this project, use unsupervised learning, particularly the K-means clustering method to perform this task.

7. Conclusion

8. Recommendation