As technology advances, service and pricing plans evolve, and the market becomes more saturated, telecom companies face increasing competition for customers. Telecom markets are highly competitive and churn is a huge concern. Understanding customer behavior is a key to staying top-of-mind.
The need for analytics
A survey released by Accenture shows that communication service providers are being compelled to consider revamping their operating models and adopting new transformational technologies to survive and thrive. Accenture believes that new analytic tools can help telecom operators meet their current challenges.
Telcos are flooded with Big Data each time someone simply makes a phone call, sends a text message or gets online. And now more than ever before, telecom CEOs, CTOs and CMOs are coming up with Big Data road-maps aimed at addressing 2 key success factors for increasing revenue:
• 360-degree view of their customers to provide better service
• Real-time analytics combined with current data to better understand customer-centric objectives
Telcos are working to better focus on their customers’ needs by collecting data based on age, income, geography, spending habits and other useful trends which will predict long-term revenue potential and help them develop targeted sales and marketing programs aimed at individual customers’ needs and habits.
Better Customer Service
Major wireless carriers have applied Big Data analytics to everyday cases using real-time analytics. This allowed them to make more informed decisions immediately, resulting in smarter computing and a 90% increase in capacity just from understanding their customers’ trends and behaviors using real-time analytics.
Reduce Customer Churn
While working on a project for a leading telecom service provider at Congruent, we analyzed patterns in consumer “data and voice plans”. SAS Visual Analytics tool was helpful in analyzing different formats of data collected – cost and duration of incoming calls, outgoing calls, data usage, messages, etc. Visualization, views for example – Voice revenue in Total revenue, region wise usage, etc. were designed based on the metrics to present to the end user with automatic update functionality. It was thought-provoking to know topics that touch on the advantages and monetization opportunities of analytics tools for telecom operators, including big data, business intelligence, customer experience analysis and management, business analytics and network analytics. Processing large volumes of data from various sources helped in providing recommendations on how to restructure existing market portfolio, how to target monthly offers with differential tariffs and commissions and how to identify High value customer segments.
Bottom line – Telcos hoping to create a successful business value must focus on customer-centric objectives as well as being equipped with the proper Big Data technology capable of producing near real-time analytics. Both of these elements will ultimately result in less customer churn and better customer service, allowing for company advancement and revenue growth. Churn will continue to be a problem as will the ability to hold on to and maximize the value of high value customers