dc.contributor.author |
Weerasekera, Namakl |
|
dc.date.accessioned |
2024-06-04T09:20:47Z |
|
dc.date.available |
2024-06-04T09:20:47Z |
|
dc.date.issued |
2023 |
|
dc.identifier.citation |
Weerasekera, Namakl (2023) Telco Churn Predictor. MSc. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2017478 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/2188 |
|
dc.description.abstract |
"The Telco industry mainly provides prepaid and postpaid mobile packages. Customers select
the package based on the information and feedback provided by users. Identifying the package
which the particular customer is based on user behaviour and the patterns are continuously
changing. Telco marketing officers are keener on introducing postpaid packages to customers
as it leads to high revenue and loyal customers.
Analysing customer behaviour over a long period of time is challenging and performing the
analysis on a large customer base is not feasible. Hence, there is a need for a model that could
learn user patterns from historical data and predict a user base with high confidence who are
more likely to churn. As prediction is methodical and explainable, the sales officers could
promote packages that would not lead to spam for customers." |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Teco Bigdata Prediction analysis |
en_US |
dc.title |
Telco Churn Predictor |
en_US |
dc.type |
Thesis |
en_US |