IoT Call Assistant Real-Time Sales Guidance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Sales phone conversations are largely unanalyzed, preventing optimization for desired outcomes due to lack of accessible content for modeling, despite advances in automatic speech recognition and natural language processing.
Innovation Solution
A call-modeling system that uses automatic speech recognition, natural language processing, and machine learning to analyze voice conversations in real-time, generating features and classifiers to provide on-call guidance for improving conversation outcomes, such as increasing the chances of sales renewal or optimizing conversation duration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sales phone conversations are left unanalyzed, then the system remains simple and easy to operate, but the ability to optimize conversation outcomes is lost
Solution Approach 1:
The patent introduces an automatic speech recognition system as an intermediary that captures and transcribes conversation content, making it accessible for analysis. This intermediary layer enables outcome optimization without requiring direct complex analysis of raw conversations, thus resolving the contradiction between productivity improvement and system complexity.
Solution Approach 2:
The patent replaces manual analysis of sales conversations with automated speech recognition and natural language processing systems. This substitution transforms the mechanical process of human review into an automated computational system, enabling comprehensive analysis and optimization while managing complexity through automation.
2Loss of information
If automatic speech recognition is applied to transcribe conversations, then conversation content becomes accessible for modeling, but processing time and computational resources increase
Solution Approach 1:
The patent performs speech recognition and transcription of conversations in advance, before analysis and modeling are needed. By converting spoken conversations into text data beforehand, the system makes conversation content immediately accessible for subsequent analysis without adding processing delays during critical review periods.
Solution Approach 2:
The patent creates text copies of spoken conversations through automatic speech recognition. These textual representations serve as efficient substitutes for analyzing original audio data, enabling rapid processing and analysis while preserving all conversation content information.
3Productivity
If real-time analysis and guidance are provided to sales representatives, then conversation outcomes are improved, but system complexity and computational requirements increase
Solution Approach 1:
The patent implements a feedback mechanism that provides real-time guidance to sales representatives during conversations. The system analyzes ongoing conversations, identifies opportunities for improvement, and delivers actionable feedback, enabling representatives to adjust their approach and improve outcomes dynamically without requiring overly complex system architecture.
Data Source
AI summary
A call assistant device is used to command a call management system to perform a specified task in association with a specified call. The call assistant device can be an Internet of Things (IoT) based device, which can include one or more buttons and connect to a communication network wirelessly. When a user activates the call assistant device, e.g., presses a button, the call assistant device sends a message to the call management system to perform a specified task. Upon receiving the message, the call management system executes the specified task in association with a specified call of the user. The task to be performed can be any task that can be performed in association with a call, e.g., generating a summary of the call, bookmarking a specified moment in the call, sending a panic alert to a particular user, or generating an action item.