[Editorial] Enhancing Quality of Experience (QoE) with Big Data in the Era of Mobile Video

Our lives have fundamentally changed with the widespread use of mobile devices. Mobile users on average spend more than 2 hours each day using their devices across dozens of different applications. Thanks to the wide coverage of mobile broadband networks these days, people are able to continually use mobile phones and tablets to communicate with friends, work while traveling and enjoy their lives.

When we look at the content people enjoy on their mobile phones, we find that end users enjoy video content more and more. As a result, 40 to 60 percent of total mobile traffic comes from video. As end users are getting more dependent on video content and have less patience when they cannot enjoy smooth video experience because of repetitive buffering and stalling issues due to network congestion, it is getting critical for mobile service providers (MSPs) to ensure the best quality of experience (QoE) in video for their customers.

MSPs have tried to prepare for a tsunami of data usage on their networks by having a wider network spectrum, expanding backhaul and clustering networks. However, MSPs, which are under tremendous competitive pressure, continuously focus on cost efficiency while pursuing customer retention through innovation programs, such as customer experience management and revenue growth.

Big Data Activities in Mobile Networks

Mobile networks adopt Big Data for several purposes. For example, MNOs provide personalized services, targeted mobile advertisement, and more, combining customer profiles with data like location, time, network conditions and device capabilities. They can also collect data from sensors and gateways including telematics data in cars, vending machines, smart meter readings, patient data, and more. Service providers can also include services like data storage and management.

Recently, MNOs are beginning to introduce Big Data to improve their network quality, supply chain management and operational efficiency. In addition to these moves, the use of advanced analytics technology is becoming increasingly more important for intelligent network operations and service optimization.

To minimize CAPEX/OPEX, MNOs need to implement initiatives in sales and marketing, network operations, customer service and administration. In network operations, this can include deployment of small cells and Wi-Fi offloading, data traffic optimization and consolidation of OSS/BSS systems. In addition, MNOs should increase their use of business intelligence and analytics to improve customer service through automation and proactive care. To enhance operational efficiency in systems deployment and services, mobile networks are encouraged to improve churn and maintenance predictions and optimize network traffic.

The customer data collected from MNOs offers a great deal of insight about customers, such as their spending habits. Such information has become important for MNOs and will give marketing departments more opportunities to do highly effective personalized campaigns. In recent years, MNOs are showing great interest in exploring new uses with their customer data not only for operational efficiency but also for external business opportunities.

There are a variety of new revenue opportunities that can be explored. Those avenues can include customer experience management, direct marketing, cross-selling, fraud detection, customer retention and more. MNOs have a great opportunity to generate new revenue by delivering personalized services. Expertise in advanced analytics will be required to identify the appropriate tools.

Big Data Activities of Network Equipment Vendors

Network equipment vendors (NEPs) have focused on introducing innovative and advanced analytics technology while also developing cost-effective network equipment. Advanced technology in measuring analytics is the most important competitive feature among network vendors. Network equipment vendors provide predictive maintenance, traffic monitoring, security, and better QoE services. NEPs are in a unique position to provide differentiation by offering real-time, advanced analytics that combine radio and service optimization. Leveraging recent progress in Big Data, network optimization and root-cause analysis is possible on an unprecedented scale.

MNOs are increasingly taking advantage of predictive maintenance to help them achieve success. Maintenance and repairs pose substantial logistical challenges to service providers in remote areas and in high-density areas with small-cell (picocell or femtocell) deployment. But through predictive maintenance, service providers can reduce the cost of their maintenance services. This would cause less disruption to service and would help to quickly identify when equipment would fail. Predictive maintenance also offers service providers a great tool to take proactive measures in controlling OPEX.

But when does predictive maintenance matter? When used properly, predictive maintenance helps to prevent many other difficulties. For example, in cases when equipment cost is high, predictive maintenance can keep costs down. In mission-critical services or in scenarios with high technical or environmental complexity, this type of maintenance helps to protect businesses and makes sure that the network is up and running properly. Difficult-to-reach locations also benefit from predictive maintenance by reducing travel cost.

Using network analytics involves software monitoring and analyzing historical and real-time data running across networks, cloud service providers, and enterprises. Network analytics not only enhance customer engagement but also customer experience. It’s an opportunity for MNOs to provide premium services with dynamic pricing plans.

Video, Video and Video

Among those services, Samsung has focused on advanced analytics technology to improve video services.

When end users only use the voice service on their mobile phones, service providers only need to satisfy the voice quality of that service. With widespread use of smartphones and affordable data pricing offers, applications such as web surfing and video are becoming more important. MNOs need to ensure web and video service quality is sustainable as well. Hence, it is critical for MNOs to have powerful tools to ensure an enjoyable data experience.

MNOs have been monitoring the quality of data services by conducting test drives with smartphones. They take their smartphones in their car and test the smartphone’s data experience. However, not only is this not cost effective in terms of time and human resources, but it is also inaccurate because it limits the test to the device itself instead of the network as a whole. A recent study shows that mobile video experience is tightly linked to Net Promoter Score, which is a key metric in predicting customer churn. The mobile industry should instead work on improving the legacy of QoE tools.

Easy and Simple Network Operation: Self Optimization of Services

Samsung has developed a groundbreaking solution that analyzes video quality on networks. It analyzes buffering and stalling time of individual video services and enables comprehensive real-time video QoE optimization. Furthermore, root-cause analysis based on data mining automates troubleshooting for any service quality degradation.

After implementing the world’s first LTE technologies, Samsung incorporated important aspects when developing such tools, so that MNOs can provide the most optimal user experience to their customers. Samsung strives to provide effective network support solutions to service providers, empowering them to meet and exceed the expectations placed on them in an ever-evolving, connected world. At this year’s Mobile World Congress (MWC), Samsung will demonstrate CognitiV Analytics, a tool that is an essential part of Samsung’s OSS solutions, which works to enhance Samsung’s professional service capabilities.