Year: 2024
Type: article
Abstract: The competitive scene inside the telecom and keeping cash businesses demands compelling client upkeep strategies. This request almost centres on making a energetic Client Churn Figure system utilizing machine learning strategies, especially the Subjective Forest Classifier, to recognize atrisk clients proactively. By analysing client data, tallying socioeconomics, advantage utilization plans, and charging information, the system predicts the likelihood of churn. The encounters picked up coordinate companies in actualizing centred on trade to make strides client steadfastness. The made system is affirmed utilizing datasets from the telecom and overseeing an account division, outlining tall precision and unflinching quality in churn figure.
Authors: Arpan Chakraborty, Manjula Sanjay Koti
Institution: Dayananda Sagar Academy of Technology and Management
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4405332369