Automated Answer Routing for Contact Center Inquiries
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Solution Overview
Problem
Supporting open-ended communication channels in contact centers is challenging due to the need for highly skilled agents, which increases costs and makes it difficult to maintain consistency and accuracy in responses.
Innovation Solution
A system that analyzes customer inquiries to generate automated answers, using text processing and historical data to determine the best routing of customer contacts, selecting suitable agents based on answer complexity and probability, and optimizing responses through dynamic feedback loops and metrics such as success rate and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If highly skilled agents are used to handle open-ended customer inquiries, then response quality and accuracy are improved, but operational costs increase
Solution Approach 1:
The system segments customer inquiries by analyzing attributes such as complexity, sentiment, and topic classification. Automated responses handle simple, routine inquiries while complex inquiries are routed to appropriately skilled human agents, creating a segmented handling approach that reduces reliance on highly skilled agents for all inquiries
Solution Approach 2:
An automated response generation system acts as an intermediary between customer inquiries and human agents. The system generates draft responses, analyzes their quality, and routes them for human review only when necessary, reducing the direct burden on highly skilled agents while maintaining response quality
2Reliability
If highly skilled agents are deployed to handle diverse customer inquiries, then response accuracy is improved, but resource availability decreases
Solution Approach 1:
The system applies local quality by matching specific inquiry characteristics with agent skill sets. Instead of requiring all agents to be highly skilled across all domains, the system identifies specific attributes of each inquiry (complexity, topic, sentiment) and routes to agents with relevant local expertise, improving overall resource utilization
Solution Approach 2:
The automated response generation system provides universal capability across all inquiry types. It can generate responses for any customer inquiry regardless of topic or complexity level, allowing human agents to focus on specific complex cases rather than requiring all agents to be universal experts
3Productivity
If automated response systems are implemented, then operational cost is reduced, but response quality and consistency deteriorate
Solution Approach 1:
The system implements feedback loops where generated automated responses are analyzed for quality attributes, routed based on confidence scores, and continuously improved through learning from human agent corrections and customer interactions. This feedback mechanism ensures response consistency while maintaining quality
Solution Approach 2:
The system performs preliminary analysis of customer inquiries to determine appropriate response strategies before actual response generation. By pre-classifying inquiries and preparing routing decisions based on analyzed attributes, the system ensures consistent quality standards are applied before responses are finalized
Data Source
AI summary
A system can determine a best routing of a customer contact based on analysis of one or more automatically generated answers. A customer may provide an inquiry through a social media contact. The contact center can analyze the inquiry to generate one or more automated answers. The system then analyzes the automated answers. The analysis may include studying various attributes of the answer, either in relation to the inquiry or based in historical data. From the analysis, the system can modify the answers and/or provide a different or improved pool of agents to handle the contact. Thus, an improved set of answers and agents is provided for managing the contact.