Outgoing Message Text Analysis for Automated Quality Routing
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Solution Overview
Problem
Organizations face challenges in maintaining consistent and high-quality outbound communications due to variations in customer service representatives' (CSRs) conversational skills, leading to errors and inappropriate tone in messages, which can be costly and resource-intensive to correct.
Innovation Solution
A method and system for intercepting and analyzing outgoing messages using a Text Analytics Service (TAS) unit, which assigns an analytical score based on factors like spelling, grammar, sentiment, and tone, and routes messages for correction if they exceed a quality threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual quality assurance processes are used to review outgoing messages, then communication quality is improved, but organizational cost and resource consumption increase
Solution Approach 1:
The system enables self-service quality assurance by having the outgoing message analyze itself through automated text analysis. The message is scored based on its own characteristics (spelling, grammar, tone) without requiring external human review, thus improving reliability while eliminating the resource cost of manual QA staff.
Solution Approach 2:
The patent replaces the mechanical human review process with an automated computer-based text analysis system. The TAS unit automatically evaluates message quality using algorithmic scoring, substituting the manual mechanical process of human reading and judging with automated computational analysis.
2Reliability
If dedicated QA staff are employed to review outgoing messages, then communication quality is improved, but productivity of other operations is reduced
Solution Approach 1:
The quality assurance function is transferred to the message itself through automated self-analysis. The TAS unit independently evaluates each outgoing message without requiring dedicated QA staff time, allowing other operational activities to proceed at full productivity while maintaining communication quality standards.
Solution Approach 2:
The system performs quality assessment in advance before messages are sent out. By analyzing and scoring messages preliminarily through automated text analysis, the system identifies quality issues before they reach the customer, eliminating the need for post-completion review by dedicated staff.
3Loss of energy
If automated text analysis is implemented, then resource consumption is reduced, but message quality control complexity increases
Solution Approach 1:
The quality assessment system is segmented into distinct, manageable scoring categories such as spelling, grammar, tone, and content appropriateness. Each dimension is evaluated independently by the TAS unit, making the complex quality control process modular and easier to implement and maintain despite the automated nature of the system.
4Reliability
If manual review of each message is performed, then communication quality is improved, but time for customer interactions is delayed
Solution Approach 1:
The manual mechanical process of human reading and reviewing each message is replaced with automated computer-based text analysis that operates instantaneously. The TAS unit processes message quality assessment in seconds without human intervention, maintaining high communication quality while eliminating the time delay associated with manual review.
Solution Approach 2:
The automated text analysis system operates continuously and concurrently with message composition, providing immediate quality feedback without interrupting the customer interaction flow. Unlike manual review which creates sequential delays, the automated system maintains continuous operation throughout the message sending process.
Data Source
AI summary
The present invention allows text analysis and routing of an outgoing message. The system intercepts outgoing messages for analysis by a TAS software module. The module assigns an analytical score to the message, then compares the score to a threshold. If the score is below the threshold, the message is transmitted to its ultimate destination. If not, the message may be routed for correction by the message's composer or quality assurance staff. After such correction, the message new analytical score is generated and compared, and, if necessary, the process repeats again.