Today’s digital transformation means wireless companies are pulling out all the stops to differentiate their offerings by creating an ecosystem of digital content and services that help set them apart, machine learning being one of them. Moving into adjacent businesses such as media, IoT, financial services, IT services, logistics, and even utilities in search of new opportunities and revenue streams. While it may be good for business, all this change is creating a lot more complexity, and more data.
Machine learning is applied to data to help CSPs with this growing challenge. Utilizing complex data models and algorithms to find patterns in data, CSPs are able to achieve Predictive and Prescriptive Analytics to manage Quality, Cost, Revenue and company Margins faster.
With our long history in telecoms and our subject matter experts, we have developed advanced machine learning capabilities
To benefit from Predictive and Prescriptive Analytics one requires a combination of relevant experience, skills and expertise. At TEOCO we have this in abundance for the telecoms sector, being a leader in many areas. Utilizing our experience and our people we are helping hundreds of CSPs globally with our machine learning capabilities.
Some examples of how we help CSPs through machine learning include:
- Root Cause Analysis – reduction of MTTR
- Our VoLTE Analytics solution INsync categorization of every VoLTE call through machine learning for examples MOS (measure of success), MOS enables network engineers and care staff to easily identify and troubleshoot billions of VoLTE calls with low MOS.
- Our Helix Analytics solution utilizes machine learning for automatic root cause analysis of service assurance alarms. By grouping alarms into clusters, the solution significantly reduces the number of alarms that require immediate attention and facilitates fast automated resolution of network and service issues.
- Churn Prediction – retaining subscribers
- Utilizing subscriber data such as rate plan and account activity, plus network data, through Prescriptive Analytics we predict subscriber churn and help operators increase subscriber tenure.
- Encrypted Video – delivery of quality video content
- With the explosion of streaming video, delivering video insights in real time is not a simple task. Our INsync Video Analytics solution, through machine learning, detects encrypted video characteristics in near real time to measure video performance.
- App Detection – increasing subscribers & revenue
- Automatic OTT App identifies encrypted and non-encrypted Apps per user. Knowing which Apps by category are used by subscribers when and where, CSPs can understand the behavior of subscribers. These insights can then be monetized by CSPs.
To learn more about how we can help you with our Machine Learning expertise please contact us.