Where is the value for telcos in the data ecosystem?
Is it in the collected data, the platform that combines and processes data, analytics that create insights and foresights, or the compute and storage infrastructure enabling those?
All.
However, network providers - the focus here and because they own customer data, particularly consumer data - with great and advanced analytics can realize substantial benefits from increasing customer loyalty to optimizing capital investment to personalizing products to launching new offerings.
Example use cases:
- Predict customer churn rate: Use predictive analytics, search algorithms combined with machine learning techniques such as feature selection. Then take actions to reduce it, e.g. personalized promotions.
- Optimize contact center and incident management: Build a granular cross-domain network topology down to the element level, use machine learning based event management to consolidate large amount of events to fewer incidents that would accordingly lead to fewer agent-handled calls.
- Real-time network optimization: Model the network in a coherent and dynamic topology, use machine learning performance management to create life cycle management insights that optimize network planning.
- Personalize offerings and promotions to individual customers in real-time using mobile data, social media and location.
The list can extend to revenue assurance by fraud analytics, forecasting and prediction of regional demand on connectivity and discovering potential business cases based on consumer behavior.
Feel free to contact me at [email protected] if you want to share ideas or further discuss.