Business Field
Current Position -> Business Field -> Application
== == Application == ==

Global Business Intelligence Consulting Ltd. Co. (GBICC) provides high quality dependable consulting and integration services in the filed of business intelligence applications to banking, telecommunication, stock, insurance, manufacturing, insurance, retail and government branches. Our solutions aim to help enterprises to improve their customer service quality, market share and sales and risk management abilities.


Telecommunication is a high data integration and high data dependency industry. Business intelligence applications are helping telecom companies to extract information, discover hidden patterns, and learn business development trends. With these gained knowledge, telecom operators can provide supportive information to decision makers, and help them to make strategic marketing decisions and policies, and respond rapidly to emerging market opportunities.

Data Mining Applications in Telecommunication Industry:

  • Customer Purchase Mode Analysis: this analysis aims to study the association relationship among historical detailed call records, such as local, long-distance, and information station calls, and archived customer information. By combining customer classification analysis, one can study customer purchase capability, purchase habits, spending cycle and other aspects of customer. The results can be used to analyze and predict customer calling behaviors, providing decision making basis for telecom operators.

  • Customer Marketing Analysis: by imitating promotion activities, this analysis uses data mining model to mimic billing processes. Results can bring insights to hidden problems of a promotion policy, providing basis for adjustment.

  • Customer Delinquency Analysis and Dynamic Fraud Prevention: by using data mining technology, summarize hidden patterns of various fraud and delinquent activities, collect and build a pattern base. When customer calling behavior happens to fit with one pattern in the base, the system can warn relevant department to prevent risks and reduce losses.

  • Customer Attrition Analysis: based on existing attrition data, build models to test association relationships among customer profile, service profile, customer purchase data and attrition probability, then monitor the possibility of customer attrition. If attrition possibility is high, promptly apply promotion activities to boost customer loyalty.