MVNO Business Analytics: MVNOs can take control of their business in the age of the IoT from predictive to prescriptive analytics
An interview with Jacob Howell, Director of R&D, Innovation and Implementation, TEOCO.
Today, there are over 150 mobile virtual network operators (MVNOs) in the U.S. This translates to 36 million customers, representing approximately ten percent of wireless subscribers. These MVNOs typically support traditional subscribers using their wireless phones for voice, text, and data – but the profile of a ‘typical’ MVNO is about to change.
In this interview, Jacob Howell, Director of R&D, Innovation and Implementation for TEOCO, explains the challenges and benefits of obtaining MVNO business analytics.
Q: From a data and customer insight perspective, what are some of the current challenges for today’s MVNOs?
Jacob Howell: From a customer insight perspective, I believe that MVNOs are operating somewhat with one hand tied behind their back. Typically, MVNOs will just get call records and the billing information from their mobile network operator (MNO) to understand how customers are using their services. But this only gives them part of what is really a much bigger picture. For example, the MVNO doesn’t know where their customers are traveling on their service provider’s network, what kind of quality of service they are experiencing, such as dropped calls or if their videos are buffering. The MNO, on the other hand, is capturing an abundance of metrics about all network users – whether they are their own subscribers, or the MVNO’s.
The MNO can see what cell tower a subscriber is closest to, and which ones they are pinging most often – and where they travel throughout the month in any given region. This information provides a much more complete view of each subscriber.
Q: How can MVNOs overcome this to gain a more complete view of their subscribers?
JH: It’s in the MNO’s best interest to deliver network data and insights to the MVNOs. When an MVNO benefits – so does the MNO. However, the true value comes when MVNOs can to analyze the network and the device data together, to really derive a complete representation of the subscriber, the applications they use, and their quality of experience.
The addition of network data to an on-device measurement approach that captures customer experience analytics and service performance insights, delivers immediate visibility into how subscribers use services to the MVNO – down to the application level. For example, the MVNO will have access to the number of sessions a subscriber has opened, the throughput of the different applications, and the quality of voice, data, and video – all coming directly from the subscriber’s smart device.
With this enriched data set, advanced analytics with machine learning capabilities can be leveraged to identify trends to recognize specific types of customer segments. Who are the mobile gamers? Who are the soccer moms? Who are the telecommuters? With this complete profile MVNOs will be able to better tailor their network, services and marketing campaigns to these specific types of customers and others.
Q: Once the MVNO has access to all this data, what can they do with it? What are the use cases?
JH: One of the more interesting use cases is the ability to predict what we refer to as Subscriber Life Expectancy. With machine learning, MVNOs can look back at each customer’s experience and predict what they are going to do in the future. Will they upgrade their device, add a new line, or downgrade their service? We’ve found that within just a few days of activation, there are some key indicators that predict when a subscriber is going to churn. This information is valuable to MVNOs across their entire organization. For example, finance teams use this data to forecast revenue streams and aid in their investment decisions. Marketing will use this information to develop targeted marketing or customer retention campaigns to promote products and prevent churn.
With enough granular data, MVNOs will even be able to identify the devices or applications that consistently deliver a lower quality of service. This is where MVNOs can target outreach campaigns to users with problematic devices; curtailing churn risk by offering attractive upgrade plans and incentives.
Q: An MVNO wouldn’t typically have access to this level of data and network insights. Do you feel that if a network provider – the MNO – can deliver this type of information it becomes a competitive advantage and will attract more MVNO partners?
JH: It absolutely is a differentiator. It helps attract more MVNO business to a specific MNO. Not all MVNO’s are exclusive to one MNO. If you, as a MNO, are able to give your MVNO customer some additional insights, then you immediately become significantly more attractive. You will attract more MVNO business versus your competitors, because they receive greater value from the relationship-information that they can use to grow their business more efficiently and intelligently.
Q: With more IoT devices connecting to the network, what are the types of insights tomorrow’s MVNOs will need?
JH: The MVNO of the future will not be offering voice minutes and data exclusively. They may be an MVNO that caters to a specific industry – such as oil and gas, collecting smart meter readings from oil wells that are distributed across the country. So MVNOs need to be prepared for a future where they may be capturing oil gauge readings in addition to call detail records or apps. This is where machine learning and predictive analytics capabilities will really come to the fore as this new breed of IoT MVNO will require insight into the future of their business – to their ‘devices’ and ‘subscribers’ – even if those devices and subscribers are substantially different than we define them today.
About Jacob Howell:
Jacob is responsible for research & development, innovation and new product implementation for TEOCO’s Business Analytics line of solutions. Prior to joining TEOCO, Jacob designed and implemented big data, revenue assurance, fraud management, and subpoena compliance systems for The Walt Disney Company, Time Warner Telecom, and XO Communications. Jacob holds an MBA in international business and bachelors’ degrees in international finance and human resource management from Brigham Young University. Jacob is certified as a data scientist and an enabler of IOT technologies. He is also a Certified Communications Security Professional (CCSP) and the Board Secretary of the Communications Fraud Control Association (CFCA) where he has authored the CFCA’s global telecom industry fraud loss survey since 2007.