Wyniki wyszukiwania dla: CUSTOMER CHURN - MOST Wiedzy

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Wyniki wyszukiwania dla: CUSTOMER CHURN

Wyniki wyszukiwania dla: CUSTOMER CHURN

  • Intelligent Decision Forest Models for Customer Churn Prediction

    Publikacja
    • F. E. Usman-Hamzah
    • A. O. Balogun
    • L. F. Capretz
    • H. A. Mojeed
    • S. Mahamad
    • S. A. Salihu
    • A. G. Akintola
    • S. Basri
    • R. T. Amosa
    • N. K. Salahdeen

    - Applied Sciences-Basel - Rok 2022

    Customer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....

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  • Empirical analysis of tree-based classification models for customer churn prediction

    Publikacja
    • F. E. Usman-Hamza
    • A. O. Balogun
    • S. K. Nasiru
    • L. F. Capretz
    • H. A. Mojeed
    • S. A. Salihu
    • A. G. Akintola
    • M. A. Mabayoje
    • J. B. Awotunde

    - Scientific African - Rok 2023

    Customer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...

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  • Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services

    Publikacja

    This paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of...

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