Use Case
Pinnacle’s next Generation Customer and Network Analytics platform offers ready-to-go use cases that can be leveraged by Marketing, Service Delivery and Network Teams. These use cases help in swift revenue enhancement, customer profiling , customer experience insights, predictive and prescriptive insights and analytics driven operational efficiency.
The Impact
Functions/Beneficieries
Our SPECTA™ product suite helps major stake holders of Communication Service Providers to take data driven actions to maximize revenue, deliver network efficiency and customer experience.
Usage driven analytics
Usage insights for enhancing up- selling and cross-selling opportunities to generate additional revenue, identify deviations in subscriber usage patterns, minimize usage vs penetration gaps, launch new plans
Device Insights
Real time visibility on entire device base, segment devices ( based on ARPU and data consumption ) ,target subscribers with device based promotions, device performance insights
Retention Analytics
It can be five times more expensive to attract a new customer, than to keep an existing one. Use the SPECTA’s customer analytics for 360-degree customer insights to develop actionable strategies for customer retention
Micro-segmentation
of Customers
Machine learning based algorithms incorporated for micro segmentation of customers based on their browsing preference like Streamer, Gamer, browser, Chatter etc. Target each customer segment with a bespoke approach rather than a one size fits all technique.
Customer Profiling
Create a portrait of your customers to help communication service providers make better product offerings and develop an effective strategy to optimize the marketing budget and improve return on investment.
Acquisition Analytics
Track a subscriber’s journey after their acquisition over multiple services to know if they are happy or not. Know the best and worst preforming geographies for targeted action.
Application Analytics
Use Inhouse developed Deep Packet Classification to customize offering to customers based on applications used, extent of usage- frequency and consumption etc. Monetize customer insights to generate alternate revenue streams by extracting revenue from 3rd party, data based adv etc.
Customer Experience Index for each Customer
Know the experience of each customer across different Access types, Geographies, Content, Devices and many more services.
Customer Care Insights
Real time assessment of customer complaint. Validate the customer complaint and speak with the actual data . It increases fast time resolution , reduces repeat calls and enhances customer confidence
Complaint Prediction
Be one step ahead and know in advance the customers which have the highest probability of lodging a complaint and under what category of complaint.
Churn Prediction
Identify customers most likely to churn through advanced Machine Learning based algorithms. Uses intelligence from platform derived churn pointers along with other traditional data sources as input.
Real-time Insights for Network Performance
Real time insights of network performance parameters enables communication service providers to take quick action and deliver superior experience
Quick Demarcation of Issues
Quick demarcation of issues in network performance, co-relate with other activities like Change Request, Network upgrade, outage etc. for faster resolution and generate real time alerts for degradation of KPIs
Predictive Capacity Planning
Identify cell nodes that are going to hit peak provisioned capacity in the next 1, 3, 6 months .Takes historical usage trends, device growth, sales forecasts into consideration for prediction
Network Constraint Analytics
Quick identification with drill down functionality to find the source of the congestion in a single window on any network like GGSN/PGW, SGSN/SGW, NodeB, eNodeB
Smart Network Planning
Smart Network planning through SPECTA derived analytics output along with conventional planning inputs for priority based planning and faster ROI
Predictive Network Fault Incidents
Ensure continuity and reliability of service through early detection of faults and predict percentage failure probability of the equipment across different network elements