Page 501 - Handbook of Modern Telecommunications

4-32 CRC Handbook of Modern Telecommunications, Second Edition

Customer Care

Web
Customer
Information
Data Warehouse
Data Security and Consumer Privacy Protection
Customer
Analytics
Call Center Data Mart

Customers Direct Mail Real-Time Marketing and
E-Mail Contact Mgt Lead Mgt
Fulfillment Database Database
Centers

Marketing
Events Business Intelligence Marketing Program
and Predictive Modeling Automation
Shows Reports and Measures
Category Management,
Analysis, Data Mining Planning Execution
and Insight Creation

Retailers
After-Market
Service Marketing Sales

FIGu RE 4.3.3 Strategic BI architecture.
4.3.3 Business Intelligence in the Telecommunications Industry
Telecom was among the first industry verticals to experience the benefits that BI brings to the corporate
table (see Figure 4.3.3). Telecom was also the first to experiment with how BI, or rather analytical capa-
bilities in conjunction with Customer Relationship Management (CRM) solutions, can improve cus-
tomer experience and thereby the business. Among the first applications in this area were the telecom
industry’s BI initiatives to reduce customer churn. The use of BI connected to operational CRM systems
helped identify customers who were most likely to shift to another service provider, by analyzing the
number and nature of grievances registered by users.
Although the success of these initiatives has resulted in CRM products with analytical capabilities,
the case is still strong for a dedicated BI system connected to an operational CRM system, provided the
linking is done optimally. This is because the new CRM products still do not match up to a full-fledged
BI system’s analytical capabilities, not so far at least. Today telecommunications companies can provide
basic answers. However, the complex questions they need to answer today go beyond any one opera-
tional system.
For example, today they know who their customers are and are marginally effective in marketing new
services to them. However, if they want to know who their profitable customers are, which services the
customers use that make them profitable, and which marketing campaigns should be targeted to this
segment, they find themselves having to extract data from multiple systems and manipulate complex
spreadsheets.