AI Customer Experience Analytics is a production-ready machine learning application that predicts customer satisfaction scores on a 0-10 scale and identifies the key factors driving satisfaction. Built with ensemble ML techniques combining XGBoost, LightGBM, and Random Forest models, this system delivers robust predictions with confidence intervals and actionable insights through SHAP-based explainability.
This application is designed for businesses, developers, and data teams who need to predict and analyze customer satisfaction without building ML infrastructure from scratch. You receive a complete full-stack solution: a FastAPI REST API backend with comprehensive validation and error handling, a modern React frontend with interactive visualizations using Recharts, pre-trained models on 1,200 synthetic data samples, and an automated training pipeline that lets you retrain models on your own data. The system accepts 15 customer features across purchase behavior, experience ratings, support metrics, and customer profile data, then engineers 7 additional derived features to improve prediction accuracy.
Key capabilities include real-time satisfaction prediction with model confidence scores, SHAP-based feature importance analysis that shows which factors increase or decrease satisfaction, ensemble weighting that combines three ML models for more reliable results, and a REST API with endpoints for prediction, explanation, model metadata, and feature validation. The application runs locally on Windows, Mac, or Linux with simple startup scripts included. All dependencies are documented in requirements.txt and the system includes complete documentation covering installation, API usage, troubleshooting, and technical implementation details.
The training data consists of synthetic samples generated to ensure broad coverage of customer scenarios while protecting actual user information. This approach provides realistic feature distributions and correlations suitable for development, testing, and demonstration purposes. Buyers should plan to retrain models using their own production data for optimal performance in their specific business context.
IMPORTANT NOTE: This application has been fully developed with all features implemented. However, it has not been tested in a live production environment. Buyer should expect to perform integration testing and may encounter minor bugs that require fixing. Basic technical knowledge and development skills are required for deployment, customization, and troubleshooting.
NO REFUNDS: Due to the digital nature, all sales are final.
LICENSE TERMS: Seller retains full ownership and control. Purchase grants a non-exclusive, non-transferable, perpetual license—AS IS, no support/updates, no refunds, no other obligations. Buyer may build and operate a materially new, closed-source product (including SaaS/paid service) for their own business/customers. Buyer may not open-source or disclose the application, nor resell, redistribute, rebrand, sublicense, or use the application (or any derivative) to create a competing or substantially similar product. License terms may be updated or changed at any time; continued use constitutes acceptance.