Customer-Centric Network KPIs via Call Detail Records
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Solution Overview
Problem
Network providers face challenges in identifying key performance indicators (KPIs) that are valuable to stakeholders such as customers, as they primarily rely on network-centric data, which may not accurately reflect customer experience or network performance issues.
Innovation Solution
The system generates customer stats tables (CSTs) by aggregating call detail records and other data sources to determine KPIs that are customer-centric, allowing for the identification of suboptimal network components and pain points, providing more granular insights into network performance and customer experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network providers use network-centric data to measure KPIs, then they can obtain network operation data from base stations and cells, but they cannot accurately reflect customer experience or identify network performance issues from the customer perspective
Solution Approach 1:
The patent inverts the traditional network-centric measurement approach by implementing a customer-centric measurement system. Instead of measuring network performance from the network side (base stations, cells), the system measures performance from the customer side by analyzing data from customer devices, including mobile devices and IoT devices. This inversion enables accurate reflection of actual customer experience while maintaining network performance measurement capabilities.
2Loss of information
If network providers rely on traditional network-centric KPIs, then they can maintain simple measurement systems, but they cannot identify suboptimal network components or provide granular insights into network performance
Solution Approach 1:
The patent segments the measurement system into multiple components: customer devices (mobile devices, IoT devices), data collection modules, data processing modules, and analysis modules. Each segment performs a specific function - customer devices generate measurement data, collection modules aggregate data from multiple sources, processing modules clean and validate data, and analysis modules generate insights. This segmentation enables granular network performance insights while managing system complexity through modular architecture.
Solution Approach 2:
The patent introduces intermediary components including data collection modules that act as mediators between customer devices and the analysis system, and data processing modules that mediate between raw data and actionable insights. These intermediaries buffer and structure the data flow, enabling granular measurement capabilities without directly exposing the complexity of the underlying measurement infrastructure to end users.
3Reliability
If network providers implement customer-centric measurement systems, then they can identify pain points and suboptimal network components, but they need to aggregate and process large volumes of data from multiple sources
Solution Approach 1:
The patent implements preliminary action by pre-configuring measurement parameters on customer devices, pre-establishing data collection protocols, and pre-processing data in near-real-time as it is generated. Data from customer devices is collected and初步 processed before being aggregated into the central system, reducing the burden of processing large volumes of raw data and improving overall data processing efficiency while maintaining accurate network performance assessment.
Data Source
AI summary
Systems and methods are described herein for analyzing the performance of a communications network (e.g., a mobile telecommunications network) using customer-centric and/or subscriber-centric data and information. In some embodiments, the systems and method may determine key performance indicators for a communications network by accessing call detail records from multiple communications network sources, generating a database of one or more customer stats table (CSTs) based on the accessed call records, wherein the CSTs include records for each individual customers of the communications network, and determining one or more key performance indicators (KPIs) for the overall network based on the records stored by the one or more customer stats tables.