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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64610
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

MASTER OF COMPUTER APPLICATIONS
GIET ENGNEERING COLLEGE (A)
MASTER OF COMPUTER APPLICATIONS
GIET ENGNEERING COLLEGE (A)
This project presents an AI-Powered customer churn prediction system that uses some machine learning algorithms to identify customers who are likely to stop using a product or service. Customer retention plays a vital role in the success of modern businesses, as losing long lasting customers can impact the company growth and revenue. The prediction can be achieved by analyzing customer related data, including transaction records , usage behavior , and demographic information to discover patterns associated with churn. Advanced Machine Learning algorithms such as Logistic regression, Decision tree and Random forest to predict churn with higher precision. The proposed system enhances customer retention, optimizes business performance and supports data-driven decision-making. Prediction helps businesses can implement targeted strategies such as personalised offers and improve services to enhance customer satisfaction and reduce churn , overall this project demonstrate how Artificial Intelligence and Machine Learning can be effectively utilized to enhance customer relationship management and support sustainable business growth
KEYWORDS
The AI-powered customer churn prediction system provides an effective and intelligent solution for identifying customers who are likely to discontinue a product. It provides an effective solution for predicting customer churn using machine learning algorithms. The project analyses the large amount of customer data to identify patterns. The proposed system enables businesses to take proactive retention measures, such as personalised offers and improved customer support, before customers leave. It enhances customer satisfaction and loyalty, improves efficiency through automation and reduces manual efforts. The system supports real-time insights for better decision - making, overall the project demonstrates how AI and Machine Learning can be successfully applied to improve customer retention, increase profitability and support sustainable business growth.
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Publication Date
6/8/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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