Website Intent Parsing for Faster Contact Center Query Routing
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Solution Overview
Problem
Contact centers face challenges in automating the processing of end-user queries due to the difficulty in manually identifying the diverse range of intents with which users access the system, leading to inefficiencies in query handling.
Innovation Solution
An intent identification engine parses the code of online pages associated with the entity to automatically generate a set of intents, which are then reviewed and refined by administrators before being stored in an intent data repository for matching user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of intents is used, then accuracy of intent identification can be maintained, but productivity and time consumption deteriorate due to the diverse range of intents
Solution Approach 1:
The system performs preliminary action by automatically generating a comprehensive set of intents from website content before the contact center operations begin. This pre-generated intent library covers diverse user queries in advance, eliminating the need for manual identification during operations and enabling high-speed automated query routing while maintaining accuracy through the pre-established intent framework
2Adaptability or versatility
If manual identification of intents is used, then comprehensive coverage of diverse intents can be achieved, but loss of time increases due to the extensive manual effort required
Solution Approach 1:
The system implements self-service by enabling the contact center system to automatically generate and update its own intent library by parsing and analyzing website content. This self-updating mechanism ensures comprehensive coverage of diverse intents across different website sections while eliminating manual time investment, as the system autonomously expands its intent knowledge base
3Productivity
If automated intent identification is implemented, then productivity and time efficiency are improved, but device complexity increases due to the need for parsing and processing systems
Solution Approach 1:
The system applies universality by designing a multi-functional parsing and processing system that simultaneously performs multiple tasks: extracting intents from website content, categorizing them by website sections, generating structured intent data, and updating the contact center knowledge base. This consolidated multi-functional approach reduces overall system complexity compared to having separate specialized systems for each function
Data Source
AI summary
A server identifies information related to offerings associated with an online page. The server identifies intents based on the information, at least a portion of the intents corresponding to at least one of headers or menu items of the online page. The server updates the intents based on supplemental information accessible via a hyperlink associated with the online page. The server stores the intents in an intent data repository.