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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM16987

Churn Prediction and Prevention for OTT/Tele- Communication

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM16987

Volume:

6 |

11 |

Nov 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM16987

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AS

Aniket Shinde

AP

Ajinkya Pawar

PD

Pratik Dhamne

KS

Krushnakant Shaha

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Abstract

Customers are becoming more drawn to the quality of service (QoS) offered by businesses in the present. However, the present day shows greater rivalry in offering clients technologically cutting-edge QoS. However, effective customer relationship management systems may help the organization attract new clients, preserve client connections, and enhance client retention by generating more revenue for the company’s operations. Churners have always been a major problem for every business that offers services. Churning drives up a company’s expenses while also lowering its profit margin. However, it is possible to forecast if a consumer wishes to cancel service using predictive analysis based on historical service usage, service performance, expenditure, and other behavioral patterns. The problem with churn analysis is that it can reveal unnecessary information when used on databases that are combined by a company that owns confidential information.

KEYWORDS

customer relationship management customer retention machine learning churn analysis

Cite This Article

Aniket Shinde, Ajinkya Pawar, Pratik Dhamne, Krushnakant Shaha, "Churn Prediction and Prevention for OTT/Tele- Communication," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 11, Nov 2022. https://doi.org/10.55041/IJSREM16987

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5/26/2023

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