• English
    • български
  • English 
    • English
    • български
  • Login
View Item 
  •   Home
  • Студии
  • Годишен алманах научни изследвания на докторанти
  • View Item
  •   Home
  • Студии
  • Годишен алманах научни изследвания на докторанти
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Customer Demographic Segmentation Based On Telecom Behavioral Data

Thumbnail
View/Open
48c6d9552207252d895905707e1c7638.pdf (2.631Mb)
Date
2020
Author
Trichkov, Dimitar
Metadata
Show full item record
Abstract
In the modern world, digitalization becomes ubiquitous and covers almost every aspect of the business and daily life. Telecom services providers have a major role in these processes due to their involvement in collecting, storing and processing enormous amounts of customer data. This also includes personal telecom services usage data, which if correctly interpreted, might be used for many different purposes. Using telecom data to predict certain demographic characteristics of the customers is helpful in more than one aspect: 1) It could add the acquired knowledge into customer segmentation to better target different customer groups. 2) Such data could be used in cases where traditional historic data is not available- the potential strength of predicting customer credit worthiness based on behavior data is still not fully explored. 3) Last but definitely not least, is the use of data for verifying customer identification in fraud detection. In this paper, an overview of some successful use of telecom data for non-telecom services is shown, as well as with a set of real telco data, statistical techniques are used to demonstrate the relation between mobile telecom services usage and subscription owners’ age. Use of alternative customer data could have enormous implication both on traditional predictive models and could alter the role of the telecoms, making them one of the most important information sources for financial institutions, which operate with sensitive customer data.
URI
http://hdl.handle.net/10610/4535
Collections
  • Годишен алманах научни изследвания на докторанти

Contact Us | Send Feedback
 

 

Browse

All of DSpaceSections & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

LoginRegister

Contact Us | Send Feedback