AI-Driven Churn Prediction For SaaS Businesses

  • Unique Paper ID: 180045
  • Volume: 12
  • Issue: 1
  • PageNo: 921-926
  • Abstract:
  • SubAnalytics is an AI-powered subscription analytics tool for SaaS businesses. It uses machine learning models to predict customer churn, calculate churn metrics, identify high-risk subscribers and analyze subscription plan distributions. SubAnalytics is built with a modular architecture using a MongoDB-backed Express.js backend and a Python-based predictive microservice. Users can upload anonymized customer data via a secure web interface and the tool will generate visual and textual insights. This paper evaluates the performance of the prediction model, usability of the tool, and real-world applicability for improving customer retention strategies. The results show SubAnalytics can support data-driven decision-making in subscription-based businesses.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{180045,
        author = {Tushar Kumar Sharma and Tushar Srivastava and Utkarsh Mishra and Varun Mishra and Kajal Gehlot},
        title = {AI-Driven Churn Prediction For SaaS Businesses},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {921-926},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180045},
        abstract = {SubAnalytics is an AI-powered subscription analytics tool for SaaS businesses. It uses machine learning models to predict customer churn, calculate churn metrics, identify high-risk subscribers and analyze subscription plan distributions. SubAnalytics is built with a modular architecture using a MongoDB-backed Express.js backend and a Python-based predictive microservice. Users can upload anonymized customer data via a secure web interface and the tool will generate visual and textual insights. This paper evaluates the performance of the prediction model, usability of the tool, and real-world applicability for improving customer retention strategies. The results show SubAnalytics can support data-driven decision-making in subscription-based businesses.},
        keywords = {Subscription Analytics, Customer Churn Prediction, SaaS, Predictive Modeling, Business Intelligence, Express.js, MongoDB},
        month = {June},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 12
  • Issue: 1
  • PageNo: 921-926

AI-Driven Churn Prediction For SaaS Businesses

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