AI-Driven Churn Prediction For SaaS Businesses

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Tushar Kumar Sharma; Tushar Srivastava; Utkarsh Mishra; Varun Mishra; Kajal Gehlot

AI-Driven Churn Prediction For SaaS Businesses

Authors: Tushar Kumar Sharma, Tushar Srivastava, Utkarsh Mishra, Varun Mishra, Kajal Gehlot

Unique Paper ID: 180045
Volume: 12
Issue: 1
PageNo: 921-926

Keywords: Subscription Analytics Customer Churn Prediction SaaS Predictive Modeling Business Intelligence Express.js MongoDB

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.

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Cite This Article

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

AI-Driven Churn Prediction For SaaS Businesses

Available:https://ijirt.org/article?manuscript=180045

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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