Customer Profile Semantic Analysis System
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Solution Overview
Problem
Existing systems struggle to effectively process and integrate customer communication data from various sources, leading to incomplete customer profiles and missed opportunities for personalized service and revenue growth.
Innovation Solution
An electronic computing device is designed to receive, analyze, and derive relationships from customer data, updating profiles and identifying remedial actions or predictive behaviors, while also visualizing customer relationships and recommending tailored services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If customer data is collected from multiple sources and stored on different computer systems, then the quantity and variety of customer information increases, but the ability to process and integrate this information effectively deteriorates
Solution Approach 1:
The patent merges data from multiple sources (telephone logs, emails, electronic documents, banker's notes) into a unified customer profile stored in a centralized database. This consolidation allows the system to process and integrate information effectively despite the diverse origins and formats of the data, resolving the contradiction between data quantity and processing complexity.
Solution Approach 2:
The patent introduces an intermediary processing system that uses natural language processing and semantic analysis to extract meaning from unstructured data. This intermediary layer translates various data formats into a standardized structure, enabling effective integration without requiring complex custom processing for each data source.
2Adaptability or versatility
If customer communication data is stored in different formats on different systems, then the adaptability of data storage increases, but the precision of information retrieval and processing deteriorates
Solution Approach 1:
The patent applies parameter changes by converting unstructured data (text, voice, email) into structured formats with standardized parameters. The system extracts key entities, relationships, and attributes from various data sources and stores them in a consistent schema, maintaining adaptability to different input formats while ensuring precise retrieval through uniform data structure.
Solution Approach 2:
The patent segments customer data into distinct components (customer information, interaction history, preferences, behavioral patterns) and stores each segment with appropriate metadata. This segmentation allows the system to handle diverse data types adaptably while enabling precise retrieval of specific information segments when needed.
3Device complexity
If manual processing of customer communications is used, then the complexity of the system remains low, but the productivity of profile updates and customer insights deteriorates
Solution Approach 1:
The patent implements self-service through automated natural language processing that extracts information from customer communications without human intervention. The system automatically updates customer profiles, identifies relationships between grammatical elements, and generates insights, eliminating the need for manual data entry and processing while significantly improving productivity.
Solution Approach 2:
The patent replaces manual mechanical processing with automated computational systems. Natural language processing algorithms, machine learning models, and database automation substitute for human analysts, enabling high-volume processing of customer communications with improved accuracy and speed, despite increased system complexity.
4Reliability
If comprehensive customer data is analyzed to create detailed profiles, then the quality of personalized service improves, but the time required for data processing increases
Solution Approach 1:
The patent applies preliminary action by continuously processing and storing customer data in real-time as it becomes available, rather than batch-processing later. The system maintains updated customer profiles by incrementally integrating new information, so that when analysis is needed, the data is already prepared and structured, reducing processing time while maintaining comprehensive profile quality.
Data Source
AI summary
An electronic computing device includes a processing unit and system memory. The system memory includes instructions which, when executed by the processing unit, cause the electronic computing device to receive data associated with one or more customers of an institution. The data is received from one or more other electronic computing devices. The received data is analyzed to identify grammatical elements in the data. Relationships are derived between a plurality of the grammatical elements. At least one derived relationship is used to update a profile for a customer. At least one derived relationship is used to identify a customer for which a remedial action is warranted.