NIx CEM
Advanced Customer Experience Management
NIx CEM Advanced Customer Experience Management
NIx CEM
Transform network performance data into actionable customer insights with our intelligent CEM platform, delivering end-to-end visibility across service assurance, customer journeys and experience optimisation.
NIx CEM:
network intelligent customer experience management
NIx CEM:
network intelligent customer experience management
Future Connections’ NIx CEM platform revolutionises how network operators understand and optimise customer experience. By correlating network performance with customer behaviour, device insights and service quality metrics, NIx CEM enables proactive customer experience management and data-driven business decisions.
Our comprehensive NIx CEM platform provides deep visibility into customer journeys, service quality indicators and experience drivers across all network domains, empowering operators to deliver exceptional customer experiences while optimising network investments and operational efficiency.
Key NIx CEM features
Key NIx CEM features
- Multi-domain experience correlation - Link network performance with customer satisfaction across RAN, core and transmission domains
- Real-time customer journey analytics - Track and analyse customer interactions across all touchpoints and services
- Advanced device intelligence - Device-specific performance analysis and optimisation recommendations
- Predictive churn analysis - AI-powered churn prediction based on service degradation patterns
- Proactive issue resolution - Automated customer contact triggers before service complaints arise
- Revenue assurance integration - Correlation between network performance and billing accuracy
- Customer value segmentation - Next-Intelligent customer segmentation based on experience and value metrics
- GenAIOps integration - Natural language insights and autonomous customer experience optimisation
Service assurance insights
Service assurance insights
The NIx CEM provides comprehensive insights across multiple dimensions of customer experience,
from infrastructure performance to individual customer analytics.
Network analysis insights
Infrastructure-focused monitoring for engineering effectiveness and operational visibility
- Real-time network performance monitoring
- Visualisation of configuration changes
- Node-level metrics and analytics
- Infrastructure capacity planning tools
Device
insights
Comprehensive device performance analysis for optimal user experience and strategic planning
- Device performance benchmarking
- Connection quality analysis by device model
- Firmware version impact analysis
- Data-driven hardware recommendations
Network operations insights
Operations team enablement with impact-based prioritisation and predictive capabilities
- Impact-based issue prioritisation
- Root cause analysis tools
- Service degradation prediction
- Automated fault isolation capabilities
Customer analysis insights
Support specialist empowerment with rapid diagnostic capabilities for customer enquiries
- Quick access to customer history
- Service quality indicators per customer
- Historical issue pattern recognition
- Guided troubleshooting recommendations
Interconnect
insights
Revenue assurance through cross-network communications monitoring
- Partner quality metrics tracking
- Billing discrepancy identification
- Routing optimisation analytics
- SLA compliance monitoring
Corporate
insights
Business-oriented dashboards for account management and client relationship optimisation
- Client-specific performance metrics
- Service utilisation trend analysis
- Exportable client review reports
- SLA adherence tracking
Special events
insights
Comprehensive event management and correlation analysis capabilities
- Chronological event browsing
- Advanced event search capabilities
- Customisable event filtering
- Correlation analysis between events
Global mobility insights
International services optimisation for enhanced traveller experience
- International partner quality rankings
- Billing irregularity detection
- Traffic routing effectiveness analysis
- Global service experience metrics
Customer experience management use cases
Customer experience management use cases
Objective
Segment customers by value and experience to create personalised offers and retention strategies
Use case
Target high ARPU customers with poor network experience for premium service packages
Key metrics
- Customer Experience Index
- Data Streaming Quality
- VoLTE Performance
Objective
Build predictive models based on service degradation patterns to identify at risk customers
Use case
Target retention offers to customers showing early churn indicators from network issues
Key metrics
- Overall Performance Score
- Service Quality Metrics
- Customer Experience Index
Objective
Trigger proactive outreach and prioritise service responses based on network performance impact
Use case
Automate customer contact when network anomalies are detected before complaints arise
Key metrics
- Anomaly Detection Score
- Service Quality Metrics
- Customer Satisfaction Index
Objective
Improve customer satisfaction ratings through targeted network quality improvements
Use case
Correlate NPS feedback with network performance metrics to drive targeted infrastructure investments
Key metrics
- Customer Experience Index
- Overall Performance Score
- Service Quality Metrics
Objective
Identify problematic cells and congestion points impacting customer experience
Use case
Direct field engineers to highest impact locations based on customer experience degradation
Key metrics
- Throughput
- Packet Loss
- PRB Usage
- CQI
- Customer Impact Score
Objective
Optimise device portfolio recommendations based on network performance analysis
Use case
Recommend devices that deliver optimal performance on your specific network infrastructure
Key metrics
- Recommend devices that deliver optimal performance on your specific network infrastructure
- Network Compatibility Score
- Throughput by Device
Objective
Promote specific services in areas with optimal network performance and customer experience
Use case
Offer premium video streaming packages in coverage areas with consistently high throughput and low latency
Key metrics
- Throughput Performance
- Data Streaming Quality
- Service Availability
Objective
Design new services based on network capabilities and customer experience patterns
Use case
Identify target markets for high bandwidth services based on network capacity and customer demand
Key metrics
- Network Capacity
- RTT Performance
- Resource Utilisation
- Customer Adoption Patterns
Objective
Segment customers by value and experience to create personalised offers and retention strategies
Use case
Target high ARPU customers with poor network experience for premium service packages
Key metrics
- Customer Experience Index
- Data Streaming Quality
- VoLTE Performance
Objective
Build predictive models based on service degradation patterns to identify at risk customers
Use case
Target retention offers to customers showing early churn indicators from network issues
Key metrics
- Overall Performance Score
- Service Quality Metrics
- Customer Experience Index
Objective
Trigger proactive outreach and prioritise service responses based on network performance impact
Use case
Automate customer contact when network anomalies are detected before complaints arise
Key metrics
- Anomaly Detection Score
- Service Quality Metrics
- Customer Satisfaction Index
Objective
Improve customer satisfaction ratings through targeted network quality improvements
Use case
Correlate NPS feedback with network performance metrics to drive targeted infrastructure investments
Key metrics
- Customer Experience Index
- Overall Performance Score
- Service Quality Metrics
Objective
Identify problematic cells and congestion points impacting customer experience
Use case
Direct field engineers to highest impact locations based on customer experience degradation
Key metrics
- Throughput
- Packet Loss
- PRB Usage
- CQI
- Customer Impact Score
Objective
Optimise device portfolio recommendations based on network performance analysis
Use case
Recommend devices that deliver optimal performance on your specific network infrastructure
Key metrics
- Recommend devices that deliver optimal performance on your specific network infrastructure
- Network Compatibility Score
- Throughput by Device
Objective
Promote specific services in areas with optimal network performance and customer experience
Use case
Offer premium video streaming packages in coverage areas with consistently high throughput and low latency
Key metrics
- Throughput Performance
- Data Streaming Quality
- Service Availability
Objective
Design new services based on network capabilities and customer experience patterns
Use case
Identify target markets for high bandwidth services based on network capacity and customer demand
Key metrics
- Network Capacity
- RTT Performance
- Resource Utilisation
- Customer Adoption Patterns
GenAIOps – Intelligent customer experience automation
GenAIOps – Intelligent customer experience automation
NIx CEM integrates advanced GenAIOps capabilities to revolutionise customer experience management. Our AI-powered co-pilots provide natural language-based customer insights, predictive experience analytics, autonomous issue resolution and personalised customer engagement strategies.
NIx CEM integrates advanced GenAIOps capabilities to revolutionise customer experience management. Our AI-powered co-pilots provide natural language-based customer insights, predictive experience analytics, autonomous issue resolution and personalised customer engagement strategies.
Intelligent CEM agents for autonomous operations
NIx CEM’s agentic architecture includes specialised AI agents designed for autonomous customer experience management – from predictive analytics to personalised customer service automation.
The specialised agents leverage natural language processing to transform customer experience data into actionable business insights, automate proactive customer outreach based on network performance patterns, predict and prevent customer churn through early intervention strategies, and provide personalised customer service recommendations. The system continuously learns from customer interactions and network performance patterns, enabling increasingly sophisticated customer experience optimisation.
