Abstract
Most telecommunications providers possess a remarkable amount of data about their subscribers.The knowledge that we would discover in the database of telecommunications providers is vital to understanding the behavior of subscribers. We talk about subscribers segmentation. The segmentation will identify and select the subscribers most likely to respond favorably to offers. Our paper proposes a set of techniques to analyze and design tools that manages the process of data acquisition, data cleaning and selection of the segmentation algorithm.
Highlights
The telecommunication operators generate and store a tremendous amount of data
The segmentation process in the company has to take into account knowledge of business people about the data, the features that might be used for clustering and the features of customers that might be used for profiling
Tasks related to data acquisition, data cleaning and the choice of segmentation algorithm are defined by the domain expert once
Summary
The telecommunication operators generate and store a tremendous amount of data. These data include call detail data, network data, the state of hardware and software components in the network, and customer data [10]. The segmentation process in the company has to take into account knowledge of business people about the data, the features that might be used for clustering and the features of customers that might be used for profiling. Behavioral segmentation is a process of finding the groups of customers with similar behavioral pattern. It is one of the key data mining tasks for marketing departments of telecommunication companies [2]. This paper is organized as follows: Section 2 presents the data mining tools.
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