Call Visualization with Keyword Waveform Markers
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Solution Overview
Problem
Current call center technologies fail to effectively address at-risk business opportunities, maximize the value of client calls, and improve the quality of information exchanged during merchant-consumer interactions.
Innovation Solution
A system and method for call visualization that records, annotates, and evaluates telephone calls by identifying business-value-specific keywords, displaying call data as a waveform with markers indicating keyword occurrences, and determining a business value based on spoken keywords, allowing for timely follow-up on lost opportunities and improved training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional call monitoring tools are used, then call recording is achieved, but the ability to timely identify and capitalize on business opportunities is insufficient
Solution Approach 1:
The patent extracts and highlights only the most critical information from call recordings - specifically keywords related to business opportunities, customer intent, and actionable insights. By pulling out these essential elements and presenting them prominently in the UI, the system enables rapid identification of business opportunities without requiring analysts to review entire call recordings.
Solution Approach 2:
The system performs preliminary analysis of call recordings by automatically transcribing audio, identifying keywords, and tagging calls with business value indicators before the user views them. This pre-processing allows users to immediately see which calls contain business opportunities without having to manually analyze each recording first.
2Measurement precision
If detailed call analysis is performed, then call quality improvement is achieved, but time consumption increases
Solution Approach 1:
The patent segments call analysis into multiple levels: automatic keyword extraction for all calls, selective detailed analysis for flagged calls, and hierarchical presentation of findings. This segmentation allows rapid processing of large volumes of calls while maintaining detailed analysis capability for high-priority cases, balancing speed and accuracy.
Solution Approach 2:
The system applies different analysis depths to different calls based on their characteristics. High-value calls receive comprehensive analysis with multiple keywords and detailed annotations, while routine calls receive streamlined processing. This local quality approach optimizes resource allocation and reduces overall analysis time while maintaining precision where it matters most.
3Measurement precision
If manual keyword annotation is performed, then annotation accuracy is improved, but productivity decreases
Solution Approach 1:
The system enables self-service keyword annotation through automatic speech-to-text transcription and AI-powered keyword extraction. The automated system performs the annotation work that would otherwise require manual human effort, dramatically increasing throughput while maintaining acceptable accuracy through continuous refinement and user feedback mechanisms.
Solution Approach 2:
The system incorporates feedback loops where user corrections to automatically extracted keywords improve the accuracy of future extractions. This iterative feedback mechanism allows the system to learn from user interactions, progressively improving annotation accuracy while maintaining high automated processing speeds.
Data Source
AI summary
Merchant/consumer calls may be recorded and evaluated according to a variety of criteria. The call recordings and analyses thereof, as well as consumer tracking information, may be displayed in a user interface of a web-based online portal for convenience in evaluating the use and efficacy of marketing channels as well as the quality of merchant/consumer interactions. In an aspect, the user interface provides a representation of a variety of telephone calls as an interactive keyword cloud that presents business-value-specific keywords targeted for detection during such telephone calls. The keyword cloud may depict keywords in a range of colors, sizes, and relative positioning to connote varied degrees of significance, such as a relative rate of occurrence of keywords in the represented telephone calls. Each keyword in the keyword cloud may contain a hyperlink to related content such as a listing of telephone calls containing the keyword.