binia01/Customer-Experience-Analytics

An NLP and Data Engineering pipeline analyzing customer sentiment for Ethiopia's top mobile banking apps (CBE, BOA, Dashen) using Python and PostgreSQL. # Customer-Experience-Analytics ## Task 1: Data Collection & Preprocessing ### Objective Scrape Google Play Store reviews for CBE, BOA, and Dashen Bank to analyze customer satisfaction. ### Methodology 1. **Scraping**: Used `google-play-scraper` library. - Target: >400 reviews per bank. - Sorted by: Newest. 2. **Preprocessing**: - Selected columns: Review, Rating, Date, Bank, Source. - Removed duplicates and null values. - Normalized dates to `YYYY-MM-DD`. ### Clone the repository ```bash git clone github.com cd Customer-Experience-Analysis ``` ### Create and activate a virtual environment For Windows: ```bash python -m venv .venv venv\Scripts\activate ``` For macOS / Linux: ```bash python -m venv .venv source venv/bin/activate ``` ### How to Run 1. Install requirements: `pip install -r requirements.txt` 2. Run main.py: `python main.py` 4. Output file: `reviews_analyzed.csv` ### How to run database 1. **Install PostgreSQL**: Ensure the PostgreSQL server is running locally. 2. **Create Database**: ```sql CREATE DATABASE bank_reviews; ``` 3. **Environment Variables**: Create a `.env` file in the root directory (do not commit to Git): ```ini DB_NAME=bank_reviews DB_USER=postgres DB_PASSWORD=your_password DB_HOST=localhost DB_PORT=5432 ``` ### Execution The database ingestion is integrated into the main pipeline, but can also be run independently. **Option 1: Run via Main Pipeline** The `main.py` script automatically creates the schema and inserts data after analysis. ```bash python main.py ``` **Option2: Run via Script** ```bash python src/database/db_loader.py python src/database/verify_db.py ```