Net Promoter Scores often reveal levels of customer dissatisfaction with communications service providers. Discover two advanced analytics solutions from IBM that enable innovative analysis for keen insight into the customer experience.
Do you know what your telecommunications customers need, or are you taking a gamble and hoping that you are offering them the right products and services at the right times? Play this video game, and see if you can anticipate what is on the minds of these customers.
Customer service in communications organizations is often based on archaic models. The time is ripe for a new model that applies predictive and real-time analytics to reveal hidden patterns in data, which in turn can be used to transform service calls into positive customer experiences.
Traditional indexes and measures of customer satisfaction can be good ways to determine how satisfaction for services varies over short time periods, but a Net Promoter Score approach offers an even deeper look into how a customer feels holistically about the service.
Telecommunications companies are losing five percent of their revenue each year to fraud. Fraudsters are after free smartphones, long distance, premium services and confidential customer information resulting in $35 to $40 billion in losses from fraud worldwide.
Detecting and preventing fraud is
Telecommunications is a necessarily data-driven and capital-intensive business. Mobile network rollouts and the increasing use of mobile devices and social media generate huge amounts of customer and market data. Quick responses to changing market conditions are imperative to remaining competitive.
The mobile market is continually growing with “mobile-based payments in the United States expected to reach $142 billion in volume in 2019.” With mobile comes mobile data and the grave need for security. Vijay Dheap, global product manager for IBM MobileFirst, declares that “mobile security
TVT Chari, chief financial officer of Celcom Axiata, tells us that “if you analyze the market differently and offer the customer what they need based on their behavior” you can utilize this business intelligence to get closer to the customer. However, with the market constantly changing, and
Confidence in data is essential regardless of the bigness of the data being analyzed. In order to make business decisions based on the analysis of data, you need to be sure that the information upon which you are making those decisions is trustworthy.
Ashok Srivastava, chief data scientist at Verizon and this week’s Big Data and Analytics Hero, shares some of the challenges of deploying big data and his role in bridging the gap to “understand where the market is and how data can be used to support that market.”
Before business users can start to analyze data and consider the next best actions to improve results, it is typically required to submit a request for the data. Depending on the backlog of requests to IT, the business user might have to wait days, weeks or more before moving ahead with analysis