Semantic CRM Triple Store for Unstructured Call Data
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Solution Overview
Problem
Current Customer Relationship Management (CRM) systems lack the infrastructure to effectively utilize the vast amount of data they collect, leading to inefficient customer interaction and relationship management.
Innovation Solution
The implementation of a semantic CRM system that uses speech-enabled devices, triple servers, and graph databases to parse and store customer interactions as semantic triples within an enterprise knowledge graph, enabling real-time dynamic scripting and improved data retrieval and inference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional CRM systems collect and store customer data, then data quantity increases, but data utilization efficiency deteriorates
Solution Approach 1:
The patent transforms customer interaction data from unstructured text to structured semantic triples with defined schemas, changing the data representation parameters to enable efficient querying and analysis while maintaining data quantity
Solution Approach 2:
The patent introduces a semantic layer with triple stores and knowledge graphs as intermediaries between raw CRM data and analytical applications, enabling efficient data utilization without reducing data quantity
2Loss of information
If CRM systems aggregate data from multiple communication channels, then information completeness improves, but system complexity increases
Solution Approach 1:
The patent segments multi-channel customer interaction data into standardized semantic triples with consistent schemas, dividing complex heterogeneous data into manageable structured units that maintain information completeness while reducing processing complexity
Solution Approach 2:
The patent creates a universal semantic triple representation that can handle data from multiple communication channels (website, telephone, email, live chat, social media) through a single unified model, reducing system complexity while maintaining information completeness
3Measurement precision
If CRM systems implement comprehensive data tracking and analysis, then customer insight quality improves, but processing time increases
Solution Approach 1:
The patent performs preliminary structuring of customer interaction data into semantic triples during data ingestion, preparing data in advance for efficient querying and analysis, thereby improving customer insight quality without increasing processing time during retrieval
Data Source
AI summary
Customer relationship management (“CRM”) implemented in a computer system, including parsing a word, from call notes of a conversation between a tele-agent of a call center and a customer representative, into a parsed triple of a description logic; determining whether the parsed triple is recorded in a semantic CRM triple store of the computer system; if the parsed triple is not recorded in the semantic CRM triple store, recording the parsed triple as a call note in the semantic CRM triple store.