Copyright © 2026 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.

@article{198595,
        author = {Mekala Devi S and Yuvaharshini T and Amirtha G and Mohana Sangari N},
        title = {CUSTOMER CHURN ANALYSIS DASHBOARD USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {8522-8524},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198595},
        abstract = {Customer churn means losing customers when they stop using a company's products or services. A high churn rate can affect a company's growth and profit. Traditional methods of analyzing churn mostly use manual work and basic statistics, which are not very effective for large and complex data. In this project, a machine learning-based system is used to predict whether a customer is likely to leave. By studying past customer data, the models identify important factors that lead to churn. The results help organizations take actions like giving personalized offers and improving services. Overall, the system helps in better customer retention and supports data-driven decision-making.},
        keywords = {Churn Analytics, Predictive Modeling, Risk Analysis, Model Optimization, Decision Support Systems, Streamlit Dashboard, Real-Time Insights, Data-Driven Strategy},
        month = {April},
        }