{"id":31710981,"url":"https://github.com/arjunravi26/customer-retention-system","last_synced_at":"2026-04-19T04:37:37.259Z","repository":{"id":318254515,"uuid":"951223117","full_name":"arjunravi26/Customer-Retention-System","owner":"arjunravi26","description":"Customer Retention Project","archived":false,"fork":false,"pushed_at":"2025-10-06T03:32:11.000Z","size":223445,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-06T05:42:12.073Z","etag":null,"topics":["agno","ai-agent","fastapi","groq","html-css-javascipt","linear-regression","llama3","machine-learning","nmf","python3","rasa","requests","tableau","topic-modeling"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/arjunravi26.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-03-19T10:52:07.000Z","updated_at":"2025-10-06T03:32:16.000Z","dependencies_parsed_at":"2025-10-06T05:42:16.447Z","dependency_job_id":"945f9f82-1bb6-4b8f-ad20-38f4f1351ee0","html_url":"https://github.com/arjunravi26/Customer-Retention-System","commit_stats":null,"previous_names":["arjunravi26/customer-retention-system"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/arjunravi26/Customer-Retention-System","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/arjunravi26%2FCustomer-Retention-System","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/arjunravi26%2FCustomer-Retention-System/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/arjunravi26%2FCustomer-Retention-System/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/arjunravi26%2FCustomer-Retention-System/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/arjunravi26","download_url":"https://codeload.github.com/arjunravi26/Customer-Retention-System/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/arjunravi26%2FCustomer-Retention-System/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31995167,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-18T20:23:30.271Z","status":"online","status_checked_at":"2026-04-19T02:00:07.110Z","response_time":55,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agno","ai-agent","fastapi","groq","html-css-javascipt","linear-regression","llama3","machine-learning","nmf","python3","rasa","requests","tableau","topic-modeling"],"created_at":"2025-10-09T00:51:01.907Z","updated_at":"2026-04-19T04:37:37.216Z","avatar_url":"https://github.com/arjunravi26.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Customer Retention System for Telecom Industry\n*Proactively reduce customer churn with AI-driven personalized offers*\n\n---\n\n## Description\n\nCustomer retention is a major challenge in the telecom industry, where customer churn directly impacts revenue. According to a Harvard Business Review study, retaining an existing customer is significantly more cost-effective than acquiring a new one. Inspired by this insight, this project aims to proactively prevent churn using a combination of machine learning, AI-driven personalization, and data visualization.\n\n- **Detects churn risk** ahead of time with a Linear Regression model trained on the IBM Telco dataset.\n- **Automates personalized offers** via an Agno AI agent that pulls a customer’s data, churn score and available promotions to craft and send tailored emails.\n- **Visualizes customer insights** in a Tableau dashboard—demographics, usage patterns, churn trends—so admins spot issues and opportunities at a glance.\n- **Surfaces common pain points** through NMF topic modeling on Rasa chatbot logs, helps to identify customer need and problems.\n- **Helps customers** directly with a Rasa chatbot for quick answers about service issues and know about offers.\n\nTogether, these components turn raw data into proactive retention actions—keeping customers engaged before they consider leaving.\n\n\n---\n\n## Table of Contents\n1. [Installation](#installation)\n2. [Usage](#usage)\n3. [Contributing](#contributing)\n4. [License](#license)\n5. [Contact Information](#contact-information)\n6. [Acknowledgments](#acknowledgments)\n\n---\n\n## Installation\n\n### Prerequisites\n- Python 3.8+\n- Git\n- Docker\n### Clone the Repository\n```bash\ngit clone https://github.com/arjunravi26/Customer-Retention-System.git\ncd Customer-Retention-System\n````\n\n### Create \u0026 Activate Virtual Environment\n\n```bash\npython3 -m venv venv\nsource venv/bin/activate    # On Windows: venv\\Scripts\\activate\n```\n\n### Install Python Dependencies\n\n```bash\npip install -r requirements.txt\n```\n\n### Rasa Setup\n\n```bash\ncd rasa_chatbot\nrasa train\nrasa run --enable-api\n```\n\n---\n\n## Usage\n\n### To run service(containers)\n\n```bash\ndocker-compose up --build\n```\n\n---\n\n## Contributing\n\nContributions are welcome! To get started:\n\n1. Fork the repo\n2. Create a new branch: `git checkout -b feature/YourFeature`\n3. Commit your changes: `git commit -m 'Add some feature'`\n4. Push to your branch: `git push origin feature/YourFeature`\n5. Open a Pull Request and describe your improvements.\n\n---\n\n## License\n\nThis project is licensed under the **GNU GENERAL PUBLIC LICENSE**. See [LICENSE](LICENSE) for details.\n\n---\n\n## Contact Information\n\n* **GitHub:** [@arjunravi26](https://github.com/arjunravi26)\n* **Linkedln:** [Arjun Ravi](https://www.linkedin.com/in/arjun-ravi-60215330b/)\n\n---\n\n## Acknowledgments\n\n* **IBM** for the Telco Customer Churn dataset\n* **Rasa** for the open-source chatbot framework\n* **Agno AI** for agent orchestration\n* **Tableau** for data visualization tools\n* Research insights from **Harvard Business Review** on customer retention","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farjunravi26%2Fcustomer-retention-system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Farjunravi26%2Fcustomer-retention-system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farjunravi26%2Fcustomer-retention-system/lists"}