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Advancing the Telecom Industry through Network Experience Analytics

Advancing the Telecom Industry through Network Experience Analytics
In a competitive Telco environment where subscribers can easily change their service provider, mobile network operators (MNOs) need to provide a quality of experience (QoE) that minimizes possible churn drivers. Improving QoE can provide a strong competitive advantage and garner huge gains in customer satisfaction and loyalty.

In a world where cellphones are the most important gadgets that people own, telecom operator customers and their demands have evolved sharply. Operators are providing a variety of services. The market is getting competitive and the competition is extremely intense. Today, we see telecom operators providing best in class data service and emerging into well-established financial services and Internet of things (IOT) service providers, while still maintaining the provisioning of standard call and SMS service.

However, in trying to build a larger base of services, enhancing the existing ones and trying to get ahead of the competition, sometimes the core of the business model goes to the backdrop. Everything is provided and consumed through a network of cell site infrastructure. The heart of any operator service is the quality and consistency of its network. A service as simple as making a call becomes impossible if the network is facing congestion, resulting in revenue losses. Therefore, Network Experience Analytics in the form of:
 
  • ​consistent & up-to-date visibility and monitoring;
  • comprehensive & integrated analytics capability;
  • actionable insights & predictive problem solving;
becomes a necessity. Teradata has developed a comprehensive analytics solution that has immense business value to Telecoms:

Data Transformation from Detailed to Summarized Data

Level 5 Most network planning and management teams concentrate on each activity on a cell site and its countless reason codes.
Level 4 Few consolidate these counters to form Successful, Failed and Total Activities.
Level 3 Some aggregate them even further to generate and monitor Level 3 KPIs or KQI. For example, Outgoing Call Quality is the Percentage of Total Outgoing Calls that were successful.
Level 2 In industry it’s rare to see network quality being depicted in the form of four key areas. These areas are Call, SMS and Data.
Level 1 It’s probably nonexistent that any operator has the capability to boil billions of network activities done by millions of customers down to a single number called Network Experience Index, sitting right there at Level 1.

Managing such high volume and high velocity data and unlocking its business value by integrating it with existing business context such as Location, Devices, Segments has now become the recommended approach to manage customer experience.
Image-File-(KQI-Level).png

Use Cases

Effective Churn Prediction:
  • Incorporating NE KPIs in Churn Prediction Model has proven to increase the prediction accuracy that results in avoiding customer and revenue churn.
Customer Satisfaction:
  • Exposing NEA visualizations based on this information can enable front end channels to handle complaints more efficiently.
Network Availability & Service Assurance:
  • Network Availability and Service Assurance can be guaranteed by predicting unplanned and unforeseen network outages beforehand and taking remedial measures, thus preventing bad experiences.
Network Performance & Optimization (Content Wise):
  • Network configuration parameters can be altered such as throughput when you take in to account the content being used by customer during specific hours and specific routes.
Network Performance & Optimization Differentiated Experience:
  • Without making further investments in network infrastructure, you can provide differentiated experiences to customers based on demographics, segments, devices and revenue associated with customers.
Smart Investment Planning:
  • Analyze existing information available in warehouse along with network experience data to identify which new cell site location serves your business goals the most.
Customer Level 360 Network Analytics:
  • Using NEA, Network operators can take giant steps forward and accomplish goals to provide 360-degree Customer Analytics and provide contextual offers to customers with bad network experience.
Effective Campaign Management:
  • Inclusion of this data can result in Effective Campaign Management by more targeted campaigns, better uptakes and customer centric sales activity.
Device Analytics:
  • Network Experience can be analyzed across devices and their features. The devices that are receiving a bad experience can be identified, as compared to other devices in the same location, thus allowing you to take a corrective course of action.

NEA on Teradata:

Network Experience Analytics is a Teradata solution and has been developed using Teradata’s tools and technologies. Its real power -- the data -- resides in the Teradata database. The solution involves landing source data on to the Teradata landing server. The architecture design has been mapped on Communication Analytical Schemas. The presentation layer has been developed on Microsoft Power BI.

NEA on Vantage:

Network Experience is the new brand in today’s era. This solution can be deployed on Teradata Vantage and Vantage’s Machine Learning engines will then outline and predict certain use cases. Teradata Vantage is Teradata’s flagship analytic platform offering, which evolved from our industry-leading Teradata Database.
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Portrait of Wajiha Hassan

(Author):
Wajiha Hassan

Wajiha Hassan is a Business Intelligence Consultant for Teradata. She advocates the value of data and derives insights from it. Having worked in the Telecom industry, she has direct knowledge of its problem areas. She has designed and implemented solutions in her domain. Wajika graduated in Software Engineering and has worked in the IT industry for more than six years. Wajiha has expertise in data modeling, data warehouse, decision support and customer management and analytics. View all posts by Wajiha Hassan

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