Business intelligence (BI) will play a pivotal role in the success of operators. Integrated BI solutions will not only provide operators real-time intelligence of their customers but also help them to maximize their revenue potential from a short window of opportunity. Integrated BI solutions can potentially help operators address some of their burning issues, such as minimizing fraud and revenue leakage by integrating closely with billing, revenue assurance and mediation platforms; optimizing network resources and offload traffic; and enhancing and customer experience by reducing network outages and keep opex down.
Here are two examples of popular BI applications that can significantly reduce opex/capex and churn.
In the context of fulfillment of NGN services, accurate network capacity planning and trending is becoming critical. On-demand, bandwidth-intensive service requires dynamic, real-time allocation of network resources across the end-to-end network infrastructure. During network infrastructure expansion, the planning organization should be able to carefully target capacity growth to ensure it appropriately addresses current and developing shortfalls. It helps in justifying the need for a less physical build, which directly cuts capex, reducing overhead, saving time on field service, planning and project management.
Real-time BI solutions can play a central role in accurate, realistic and proactive network capacity planning and trending capabilities that will not only enable correct sizing of the future network but will also help CSPs reduce capacity shortfalls, minimize order fallout and increase efficiency by identifying underutilized network resources.
One other important BI use case revolves around the ability to deal with unstructured data. The ability to correlate unstructured response to questions, analysis of call center interactions and additional input sources such as blogs, forums, email, social networking sites, chat, call center transcripts and customer feedback forums helps operators enrich their understanding of their customer and have an understanding of customer perception of their services. BI solutions based on various inputs works through pattern recognition, extraction and various other techniques, thereby adding value to the carrier's BI strategy.
Social network analysis (SNA) is becoming popular among wireless operators, though many are wary of coming out in open to discuss how they are using this because of potential backlash over subscriber privacy issues. SNA is a type of analytical scoring system that enables CSPs to perform CDR and IPDR analysis to identify social calling circles among friends and families. Such analysis will have both defensive and offensive implications.
- From an offensive or up-sell perspective this analysis can help operators target or up-sell offers based on their preferences and what games or applications popular among the subscribers circle of trust.
- From a defensive perspective SNA allows operators to identify calling patterns and the influencer in a specific social group.
Algorithms allow them to figure out, based on a certain level of probability, that if an influencer churns what will happen to the rest of that social circle and how likely is it for them to churn as well. The next step is to determine customers they want to actively keep and execute compelling marketing campaigns to keep them from churning. The churn event for the rest of the social circle typically occurs within four to seven days after an influencer leaves for another provider, so time is of the essence when providing proactive retention offers or general communications to potential churners.
SNA raises pertinent question as to whether it borders on invasion of subscribers privacy. Without trying to get into that debate it should suffice to say that we always knew that the big brother was watching.
Ari Banerjee is a senior analyst at Heavy Reading