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AI-Driven Platform for Predictive Customer Retention

Year: 2026

Type: preprint

Abstract: Customer retention is a critical challenge for businesses, as acquiring new customers is significantly more expensive than retaining existing ones. This project presents an AI-driven platform for predictive customer retention that identifies customers at risk of churn using machine learning techniques. The system analyzes customer data such as usage patterns, demographics and engagement metrics to predict churn probability. [Model name] was trained on [dataset name] and achieved an accuracy of [X%]. The platform provides an interactive web interface, built with [tech stack], that lets users view churn predictions and actionable insights. The results show that predictive analytics can help organizations take proactive retention measures and reduce customer loss. Source code is available at the linked GitHub repository.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.24047479

Authors: Aditya Khandagale, Anshul Bhilare, Vedant Sasane, Akash Autade

Institution: MIT Art, Design and Technology University

Language: English

Topic: Customer churn and segmentation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W7225564636

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