Customer churn remains a huge issue for telcos. Could AI actually help? Customer churn remains one of the telecom industry’s most persistent and expensive problems. Annual churn rates typically land ...
Abstract: Uplift Modeling can be an effective machine learning method when identifying the potential customers who have the highest possibility of creating a positive impact on the marketing ...
Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria Christian Doppler Laboratory ...
Customer retention is a critical challenge for telecom companies, and understanding customer churn can significantly improve business strategies. This paper focuses on developing an accurate ...
A machine learning project that analyzes telecom customer data to predict churn using Logistic Regression, Decision Tree, and Random Forest models. Built with Python, scikit-learn, and data ...
Abstract: Customer churn prediction is essential for businesses aiming to retain their customer base in competitive markets. This study leverages machine learning to predict customer churn, employing ...
With the cost of acquiring new app installs skyrocketing, keeping users engaged who have already installed is critical for maximizing acquisition spend and customer lifetime value. Urban Airship’s ...
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