The focus of telecom operators have shifted from reducing cost to delivering a superior customer experience over their networks. Providing a greater customer experience every time is vital for limiting customer churn and building loyalty. With the advent of big data analytics and deep learning applications, the telecom sector has realized that data has become of the most strategic assets for their business success.
Operators today are occupied with unprecedented amounts of data sources that include– customer profiles, device data, network data, customer usage patterns, location data, apps downloaded and clickstream data and so on. Given this abundance of data at their fingertips, they are not only sitting on a goldmine of information but, are also in a great position to capitalize on these valuable data sets. In telecom industry, data analytics is best described by the emerging requirements for more real-time information and breaking down data as per problem areas.
Why monetize the data?
By definition, data monetization is a process of generating revenue from various data sources available to the business or the real time streamed data, by instituting the discovery, capture, storage, analysis, dissemination and mobilizing use of that data. It is meant to leverage data generated through business operations as well as data associated with individual users as they interact with their product and services.
Data monetization is essential as:
- It provides a process-led transformation in the business value chain.
- It makes use of digitization and emerging technologies such as cloud computing and machine intelligence to serve and automate the business functions better used in daily operations.
- Takes an integrated approach in bringing and reinstating the change.
- It integrates outside data with internal information and develops analytics to gain powerful insights into customer behavior and supplier capabilities to create new products and services.
Industry practices for data monetization
Needless to say, most operators are investing vigorously in big data. In return, the technology has created quite a stir in the industry and has impacted measures like churn reduction, loyalty management, customer acquisition and retention, generating new revenue streams, risk management, accelerated troubleshooting and network optimization.
- Targeting: Target products and marketing efforts using big data in order to increase loyalty and personalize the user experience aligned to the customer’s needs.
- Optimizing: Network generated data and other IT data can be used to inject into operational efficiencies and improving the effectiveness of customer experience management. Upon knowing how to optimize the network, operators are able to identify the telecom service areas to invest in new capacities, when is the right time to make telecom traffic-boosting offers and how to serve telecom customers more efficiently, etc.
- Innovating:This strategy is where the true potential of the business is unlocked, enabling new business models in place. This goldmine is capable of affecting the whole of telecom service value chain, making it a comprehensive and integrated strategy in use. This way the operators can swiftly move away from being just network infrastructure providers and become more than willing to invest in their partners for continuous innovation in service delivery.
How operators monetize big data
- Probes: This process is focused on collecting information solely to deliver it to the solutions capable of analyzing it.
- Appliances: There are devices put in place, that are capable of both aggregating and scrutinizing the data, thereafter, only a finished intelligence is required to be carried out.
- Real-time Analytics: These systems are able to create an exact measurement of jitter and delay in the networks allowing operators to improve customer experience significantly. Additionally, they are now able to reduce data packet loss which occurs during network overload.
- Advanced Software: The enhanced software used by operators today, help them to show how their services are being used. They are now able to capture the minutest of data about consumption, say how much of video an average user accesses on a daily basis, to keep operators informed about leveraging their service assets like multiplexers, optical fiber transmission, bandwidth and content.
- API Enablement: Application Programming Interface (API) enablement allows operators to bring in customers via a new application. This gives insight on which applications are used, how are they used and who are using it, enabling operators to cash more as per the usage need of the user and providing charging him on his preferences.
Key business areas where Big Data has proved its worth:
- Decision making
- Network congestion control
- Location-based services
- Personalized advertising
- Targeted marketing
- Offer optimization
- Churn prediction
- SNA analysis
- Operational efficiency
- Customer care (IVR)
- Network ROI analysis
- Cell-site optimization
- Intelligent business model
- Payment data for increased sales
- Match demand with supply
- Data exposure and API enablement
- Customer experience management
- Dynamic customer profiling
- Improved customer segmentation
- Clickstream analysis
The Road Ahead
With the convergence of telecom services and big data-enabled solutions, every operator leverages the power of data analytics and predictive analysis and it is here to stay for long by impacting other performance areas in the near future, like:
- Revenue assurance and fraud
- Precise marketing and campaign management
- Preemptive service assurance
- Package design for specific OTT
- Multi-SIM prediction
- Accurate capacity planning
- Subscriber centric wireless offload
Conclusion:
The ultimate goal of big data is to combine and correlate every information source to foster a holistic, transparent, end-to-end view of all the interactions every subscriber has with the operator. But to really leverage big data, operators must radically modify how they gather, verify, learn from, and make use of the information available at their disposal. Because in an industry like telecom it’s not the intrinsic value in the data that matters, it’s what operators do with it, counts.
