Telecoms’ offer includes a wide and growing range of services. Data comes from mobile devices location, browsing, texting, email, social media and more. This diverse volume of data is a wonderful source of customer insights, and can guide product development and marketing, network operations, sales and risk management.
Big data can help you understand better how your networks are used, and how efficient that usage is.
Crossing network (frequencies, switching, load, type of traffic and service consumption) with location data will help capacity and infrastructure planning.
Breakdown anticipation improves troubleshooting and customer satisfaction.
Keeping a customer is not as costly as getting a new customer – or winning the customer back.
Accurately diagnosing churn and getting alerted for possible imminent defection are critical in handling customer dissatisfaction. By looking at multiple clues like social media comments and significant usage change, you can predict defection and do something about it before it’s too late.
DataSonar helps bring together in real time customer transaction data and communication streams to show how you’re faring with your customers.
You can protect your customers by monitoring for fraud attempt. The ability to analyze great amounts of data, whether regarding usage, location or account, will enable telecoms to accurately determine what “normal” behavior is, and real-time capabilities will promptly identify potentially fraudulent situations that break those patterns. Fraud detection can be applied in areas like network security or profitless resource consumptions, but both are a major contributor to prevent financial losses.
DataSonar can build predictive models with high volumes of multi-source data to identify accurate patterns and correlations, and give real-time alerts when abnormal activity is in progress.
Analyzing customer clickstreams lets you understand better their preferences and how inclined they are to buy. In a win-win, you can see a rise in revenue; they can have a better experience.
From targeted promotions to optimized web pages, speed and accuracy are key. DataSonar ingests data and processes data faster, and reaches the right customers more effectively.
You can optimize QoS if you can improve your real-time analysis of multiple network traffic data sources, and respond to demand, reallocate bandwidth, and reroute traffic as needed. Forecasts will enable companies to optimize network investment plans, and anticipate necessary network changes ahead of demand.
Use DataSonar to identify and resolve bottlenecks, manage capacity, predict network usage and demand, assess infrastructure needs and maintain QoS.
This is an area that, instead of focusing primarily on patterns and established trends, benefits from identifying data that doesn’t fit – anomalies. If telecom companies are able to understand why they exist, those insights may be a great contribution for product development. With the capacity of analyzing both structured and unstructured data across the organization’s many sources, emerging trends can be detected, as well as unknown customer preferences or problems that a new product might solve.
DataSonar can further analyze usage patterns to suggest individual offers.
Telecoms can maximize the value of their huge data stores in two main ways, both of which require integrating subscriber transaction, interaction, reaction and location data. Data Monetization in Telecoms can be done either (or both) internally or externally. Upselling is the basis of internal data monetization, where telecom companies analyze network and customer data to identify opportunities, besides increasing satisfaction and retention. Although limited to existing subscribers, this growth tactic can increase revenue per subscriber. Externally, on the other hand, data monetization is achieved through selling data insights. Demographic and location data are among the most useful information external parties can get from telecoms, who have here a great revenue-generating opportunity.
Patterns and correlations from multi-source, high-volume data identified through DataSonar can provide great insights for data monetization.
Now that you know Big Data Telecoms solutions, see DataSonar solutions for Oil & Gas (upstream).