Intent Messaging System for Relevant Response Matching
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Solution Overview
Problem
Current systems lack an effective method to facilitate relevant responses from brands and users to customer intents, leading to inefficiencies in communication and information retrieval.
Innovation Solution
A computer-implemented method and system that processes customer intents, identifies relevant users or brands, solicits responses, evaluates their relevance, and presents them to the customer, utilizing machine learning models for intent extraction, matching, and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a framework is implemented to identify and match relevant users to customer intents, then response relevance and customer satisfaction improve, but system complexity increases
Solution Approach 1:
The system segments the intent processing into distinct modules: intent extraction module that analyzes customer messages, intent classification module that categorizes intents into predefined groups, user identification module that matches intents with relevant users/brands, and response evaluation module that assesses response quality. This segmentation allows each module to specialize in one function, improving overall reliability while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary intent processing system that acts as a mediator between customers and users/brands. This intermediary automatically performs intent extraction, classification, and user matching, eliminating the need for customers to manually search for relevant users. The intermediary evaluates responses before presenting them to customers, ensuring relevance without requiring complex customer-side processing.
2Reliability
If multiple users are solicited for responses to each intent, then response quality improves, but information processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-classifying intents into categories and pre-identifying relevant users/brands associated with each intent type. When a customer submits an intent, the system quickly matches it against pre-established categories and retrieves responses from pre-identified relevant users, rather than searching through all users. This preliminary organization significantly reduces processing time while maintaining response quality.
Solution Approach 2:
The system changes the parameter of user selection from exhaustive search to targeted retrieval based on intent classification. By transforming the selection criterion from 'all users' to 'users matching specific intent category,' the system reduces the number of users to contact while maintaining response quality. The evaluation parameter also changes from accepting all responses to filtering based on relevance criteria.
3Loss of information
If all received responses are presented to the customer, then information completeness improves, but information retrieval efficiency decreases
Solution Approach 1:
The system extracts and presents only the most relevant responses from the set of all received responses. The response evaluation module assesses each response against the original intent and customer preferences, extracting only those that meet relevance thresholds. This extraction process eliminates irrelevant information while preserving complete relevant information, improving retrieval efficiency without sacrificing completeness of useful data.
Solution Approach 2:
The system applies different quality standards to different responses based on their relevance to the specific intent. Rather than treating all responses uniformly, the system evaluates each response locally against the intent characteristics and customer profile, presenting responses with high local relevance quality first. This localized quality assessment ensures complete relevant information is provided while filtering out irrelevant content that would reduce efficiency.
Data Source
AI summary
Disclosed embodiments provide a framework to assist customers in obtaining relevant responses from brands and other users to the intents communicated by these customers. In response to obtaining an intent, an intent messaging service identifies one or more users that can be provided with the intent to solicit responses to the intent. The one or more users are selected based on characteristics of the intent. The intent messaging service evaluates the responses to the intent from the one or more users to identify relevant responses that can be presented to the customer. The intent messaging service provides the relevant responses to the intent to the customer, which can determine which users to interact with to address the intent.