Survey Paper on Churn Prediction on Telecom
As the client is larger a large number of details are made daily in the field of telecommunications. Decision makers and business analysts say it is way more extravagant to make new customers than to keep existing customers, so it is very important for customer relations hip management analysts to know the reason for aggressive customers and behavioral patterns in deceptive customer data. It leads to the salvation of big business regardless of size. This paper proposes a predictive mode l of churn that will begin its operation by clearing the data initially. As it is very important to have information that is not uncommon it therefore leads to accurate predictions. It uses classification and integration techniques to identify targeted customers and provides the factors that lea d to customer withdrawal in the communications sector. An engineering project will then be conducted to determine which feature plays a key role in the forecast. Feature selection is made using the benefit information and the qualification rating filter. By recognizing key churn values from customer data, CRM can increase productivity, recommend appropriate promotions to a group of potential customers based on similar behavioral patterns, and radically improve the company's marketing campaigns. The outcome of the model will provide relevant information that will be of great benefit to the sector
Year of publication: |
[2021]
|
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Authors: | Singh, Damandeep ; Jatana, Vansh ; Kanchana, M. |
Publisher: |
[S.l.] : SSRN |
Subject: | Telekommunikation | Telecommunications | Prognoseverfahren | Forecasting model | Telekommunikationssektor | Telecommunications industry |
Saved in:
freely available
Extent: | 1 Online-Ressource (9 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 19, 2021 erstellt |
Other identifiers: | 10.2139/ssrn.3849664 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013226522
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