Artificial Intelligent applications are revolutionizing the way telecoms operate, optimize and provide service to their customers. Increasing customer demands for higher quality services and better customer experiences are pushing Telcos to adress opportunities by leveraging the vast amounts of data collected over the years from their massive customer base. This data is culled from devices, networks, mobile applications, geolocations, detailed customer profiles, services usage and billing data.
Telcos are harnessing the power of Neumann’s solution to process and analyze these huge volumes of Big Data in order to extract actionable insights to provide better customer experiences, improve operations and quality of service, and increase revenue through new products and services.
From a subscriber perspective, Neumann allows operators to collect, store and analyze data from across an operator’s entire customer base to achieve real-time behavioral insights. This information can be used for a variety of scenarios, such as personalized offers, advertisements and services to the subscriber at the right time. Insights collected by our platform are essential for operators to achieve better utilization of network resources, allowing the network to adjust services based on user needs, environmental conditions and business goals resulting in better network optimization.
Use cases that allow Telecom operators to build more revenues and stronger customer relationships by bringing marketing to the next level. On the other hand, we can help improving their productivity and reduce the cost of the network maintenance.
Customer and corporate behavior:
- Customer Lifetime Value/Survival Analysis
- Product Bundles Analysis
- Affinity Bundles and Products Analysis
- Airtime Utilization Rate by channel
- Revenue KPIs
- Location Based Ad Service
- Subscriber cost and profitability
- Churn rate and customers scoring
Credit Scoring for B2C and B2B:
- Segmenting the customers per category, activity, number of employees, channel, etc.
- Showing profitability and achievement vs. target
- Prediction models based on AI analyzing the previous data
- Simulation dashboards helping to evaluate revenue if/when the business acquired more customers in different departments
- For existing and new customers
Predictive Maintenance for landline:
- Building Data Lake
- Data ingestion
- ML Models
- Alerts and Notifications