Advanced Customer Data Analysis

This project performs an in-depth analysis of customer data to uncover insights into purchasing behavior, customer segmentation, and lifetime value. The analysis is done using Python in a Jupyter Notebook.

Contents

• Advanced_Customer_Data_Analysis.ipynb: The main analysis notebook.
• dataset_AW.csv: The anonymized customer dataset used in the analysis.

Features

• Exploratory Data Analysis (EDA)
• Customer Lifetime Value (CLTV) computation
• RFM Segmentation
• Cohort Analysis
• Data visualization using matplotlib, seaborn, and plotly

Requirements

To run this notebook, install the required Python packages:

pip install -r requirements.txt

Getting Started

1. Download the following files from the GitHub repository:

   • Advanced_Customer_Data_Analysis.ipynb
   • dataset_AW.csv
   • requirements.txt

2. To download the CSV file:

• Go to the file dataset_AW.csv in the repository (left panel)
• Click on the file to preview it
• Then click the "Download raw file" button (top right) to save it to your computer

3. Recommended environment: This notebook is designed to run in Google Colab.

• You can open it there and run all cells smoothly.

4. When running the notebook in Google Colab:

• Locate the cell titled # Upload CSV file manually (for Google Colab)
• Run that cell and upload the dataset_AW.csv file when prompted

✅ Make sure the CSV file name remains dataset_AW.csv so it matches the expected path in the notebook.

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License

This project is licensed under the MIT License.

Authors

• Alejandro Galindo Valencia
• Carla Moreno Molina