OliyadTeshome/Customer-Experience-Analytics-for-Ethiopian-Top-3-Banking-Apps

# Customer Experience Analytics for Ethiopian Top 3 Banking Apps ## 📊 Project Overview This project analyzes user reviews from the Google Play Store for Ethiopia's top three banking applications: - Commercial Bank of Ethiopia - Bank of Abyssinia (BoA Mobile) - Dashen Bank The analysis provides actionable insights on customer satisfaction, key pain points, and feature enhancement opportunities to help banks improve their digital user experience. ## 🎯 Key Objectives - **Data Collection**: Scrape 400+ user reviews per banking app from Google Play Store - **Text Processing**: - Clean and preprocess reviews - Remove duplicates - Normalize dates - Translate non-English reviews - **Sentiment Analysis**: - Implement DistilBERT for sentiment classification - Handle multiple languages including Amharic - **Theme Extraction**: - Identify key topics and themes - Group feedback into actionable categories - **Data Storage**: Store processed data in Oracle database - **Reporting**: Generate visualizations and Excel exports ## 📁 Project Structure ``` ├── .github/ # GitHub workflows (CI/CD) ├── .vscode/ # VSCode settings ├── data/ # Raw and processed datasets (gitignored) ├── notebooks/ # Jupyter notebooks for analysis │ ├── 1_scrape_and_explore.ipynb │ ├── 2_preprocessing_and_cleaning.ipynb │ ├── 3_sentiment_and_keywords.ipynb │ └── 4_theming_and_reporting.ipynb ├── outputs/ # Generated reports and plots ├── scripts/ # Modular pipeline scripts │ ├── run_pipeline.py # End-to-end pipeline │ ├── scrape_reviews.py # Review collection │ ├── preprocess_reviews.py # Data cleaning │ ├── analyze_sentiment.py # Sentiment analysis │ ├── extract_keywords.py # Keyword extraction │ ├── assign_themes.py # Theme assignment │ └── generate_report.py # Report generation ├── src/ # Core modules │ ├── scraper.py # Google Play scra …