AI Key Moment Snippet Creation for Sales Call Coaching
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Solution Overview
Problem
Managers and team leaders in sales organizations face challenges in identifying and coaching sales representatives on impactful moments during calls to improve sales outcomes, as existing AI models require extensive manual tagging of conversation transcripts to identify key moments.
Innovation Solution
A computer-implemented method that automatically locates key moments in calls using AI models, creates snippets including the key moment and context, and allows for outputting and filtering these snippets for coaching purposes, leveraging existing AI models to identify impactful utterances and generate playable audio and text transcripts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tagging of conversation transcripts is used to identify key moments, then measurement precision of key moment identification is improved, but loss of time and productivity deteriorate
Solution Approach 1:
The system enables self-service by allowing the conversation transcript to automatically tag and identify its own key moments through AI processing, eliminating the need for manual intervention while maintaining identification accuracy
Solution Approach 2:
The patent replaces the mechanical manual tagging process with an automated AI-based system that uses machine learning models to identify key moments, substituting human labor with intelligent automation
2Productivity
If existing AI models are used to identify key moments, then productivity is improved, but device complexity increases due to extensive manual tagging requirements
Solution Approach 1:
The system segments the complex task of key moment identification into distinct functional components: AI model processing, snippet generation, filtering, and output, making the overall system more manageable and less complex despite the sophisticated algorithms used
Solution Approach 2:
The patent introduces intermediary components such as snippet generators and filters that mediate between the AI model's raw output and the final delivered results, simplifying the system architecture by breaking down complex processing stages
3Measurement precision
If manual review of calls is performed to identify impactful moments, then measurement precision of coaching relevance is improved, but loss of time deteriorates
Solution Approach 1:
The system performs preliminary action by automatically generating and pre-filtering snippets before they reach the coach, so that only the most relevant moments need manual review, significantly reducing the time required while maintaining coaching relevance
Data Source
AI summary
A computer-implemented method and system perform key moment-based snippet creation. The method comprises locating, automatically via at least one processor, a key moment of a call in a representation of the call and creating, automatically via the at least one processor, a snippet of the representation of the call based on the key moment located. The snippet includes the key moment and context for the key moment. The context includes a lead portion and a lag portion. The lead portion precedes the key moment, and the lag portion follows the key moment in the representation of the call. The key moment may be an utterance identified by an artificial (AI) model as having a positive or negative impact on an outcome effectuated by the call. The snippet, including the key moment, may serve as a learning tool to coach a user in a manner that improves an outcome of a next call. Such coaching may be referred to as AI-driven coaching.