📊 RMF Market-Basket Analysis for e-Commerce SuperStore

Authors: Apostolis Karapatis / Nikolaos Marakis

📌 Project Overview

This project involves a comprehensive market-basket analysis for an e-Commerce SuperStore. Using six different CSV files, the team focused on identifying patterns and insights that can enhance marketing strategies and customer purchasing experiences.

🎯 Business Impact

• Enhanced Marketing Strategies: Leveraged findings from EDA to improve product placement and promotional strategies.
• Customer Insight: Gained a deeper understanding of customer purchasing behaviors which can be used to tailor marketing and sales efforts.
• Presentation of Findings: Developed a concise presentation to share insights and recommendations with stakeholders.

🛠️ Technical Approach

1️⃣ Data Cleaning

• Utilized Pandas for cleaning and preparing the dataset for analysis. This included handling missing duplicate & values, erroneous entries, and data type conversions.

2️⃣ Extensive EDA

• Conducted a thorough Exploratory Data Analysis (EDA) to uncover patterns in customer purchasing behavior and product trends.
• Utilized Python (Pandas, Matplotlib, Seaborn) to visualize data and gain actionable insights.

3️⃣ Presentation of Insights

• Created a presentation to summarize the findings and proposed strategies based on the EDA, tailored for stakeholders' review.

4️⃣ Tech Stack

Languages & Libraries: Python (Pandas, Numpy, Matplotlib, Seaborn) Visualization: Matplotlib, Seaborn Notebook Environment: JupyterLab

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📂 Project Structure

Data Folder (CSV files):

• Contains the raw csv data. Includes 6 csv files:
  1. Trans_dim.csv
  2. customer_dim.csv
  3. fact_table.csv
  4. item_dim.csv
  5. store_dim.csv
  6. time_dim.csv

Data Cleaning Folder (Jupyter Notebook):

• Preliminary data cleaning and setup for further analysis.

Analysis Folder (Jupyter Notebook):

• Detailed notebook file that explores various aspects of the datasets through visualizations and statistical analysis. Also includes the cleaning process.

Presentation (PowerPoint file):

• Short presentation designed to communicate insights and recommendations.

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📞 Contact & Support For any questions, feel free to reach out: 📧 Email: nik.marakis@gmail.com, ap.karapatis@gmail.com