Query Prioritization System for First Call Resolution
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Solution Overview
Problem
Companies face challenges in efficiently addressing customer queries on social media and contact centers, particularly in achieving high 'first call resolution' rates, as new questions often arise during initial interactions, and existing knowledge bases may not provide satisfactory answers, leading to urgency in handling these queries.
Innovation Solution
A system utilizing a processor to access and prioritize user queries by identifying insufficiently addressed queries, estimating their priority based on criteria such as frequency, answer quality, and urgency, and providing a ranked list for effective handling, which includes consulting a query database, determining answer quality, and classifying queries for subsequent prioritization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If companies use existing knowledge bases to answer customer queries, then response time is reduced, but the ability to address new or complex questions is limited
Solution Approach 1:
The system enables automated self-service by having the query handling system automatically search for similar queries in the knowledge base, determine answer quality, and prioritize new queries without requiring manual intervention. This allows the system to efficiently handle both existing and new queries autonomously.
Solution Approach 2:
The system performs preliminary actions by proactively searching for similar queries in the knowledge base before handling new queries, and by pre-classifying queries based on answer quality thresholds. This preliminary processing enables faster response times while maintaining adaptability to new questions.
2Reliability
If companies aim for high first call resolution rates, then customer satisfaction is improved, but the complexity of handling queries increases
Solution Approach 1:
The system incorporates feedback mechanisms by automatically determining the quality of existing answers and using this information to prioritize queries. The feedback loop ensures that high-quality answers are identified and prioritized, improving first call resolution rates while the automated nature reduces operational complexity.
Solution Approach 2:
The system introduces an intermediary layer of automated query classification and prioritization between incoming queries and the knowledge base. This intermediary process simplifies the overall complexity by handling the triage function automatically, enabling agents to focus on complex cases that require human intervention.
3Productivity
If companies manually prioritize queries, then resource allocation is optimized, but processing time and labor requirements increase
Solution Approach 1:
The system performs self-service prioritization by automatically estimating priority levels for queries based on criteria such as answer quality and similarity to existing queries. This eliminates the need for manual prioritization while optimizing resource allocation, significantly reducing processing time and labor requirements.
Solution Approach 2:
The system changes the parameters of query handling by automatically transforming unstructured queries into prioritized items based on calculated priority levels. This parameter transformation enables efficient resource allocation without manual intervention, reducing both processing time and labor costs while maintaining high productivity.
Data Source
AI summary
Methods and arrangements for handling user queries. Submitted queries are accessed, and there are identified queries as being insufficiently addressed. A priority is estimated for the identified queries, and the identified queries are ordered based on the estimated priority. A priority-ordered list of queries is provided as output.