Voice-Based CRM Data Entry Using AI and Real-Time Audio Feedback
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Solution Overview
Problem
Current CRM technologies are inadequate for processing the growing velocity, volume, and variety of data from diverse sources, leading to inefficient data entry and limited output, particularly in real-time data tracking and accuracy, which hampers sales teams in understanding and predicting sales opportunities effectively.
Innovation Solution
An oral communication device and computing architecture that records user voice data, processes it using AI and data science algorithms, and combines internal and external data to provide real-time outputs as audio or visual feedback, enabling more intelligent and timely sales opportunity information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional CRM systems with keyboard and mouse input are used, then data entry can be performed, but the process is complex, difficult and time consuming
Solution Approach 1:
The patent replaces mechanical input methods (keyboard and mouse) with voice-based oral communication. The oral communication device captures spoken data directly, eliminating the need for manual typing and form filling, thereby simplifying the interaction process and reducing time consumption.
Solution Approach 2:
The system enables self-service data entry through voice commands where the user simply speaks the information needed. The oral communication device and processing system automatically capture, structure, and input the data without requiring manual navigation through complex interfaces or forms.
2Productivity
If conventional computing architectures are used, then data processing can be performed, but they are not suitable for ingesting the growing velocity, volume and variety of data
Solution Approach 1:
The patent implements a dynamic computing architecture that can adapt to varying data velocities, volumes, and types. The system processes oral data in real-time and can scale its processing capabilities to handle different data sources including machine-to-machine communication, user-oriented devices, and Internet of Things devices.
Solution Approach 2:
The computing architecture is designed to be universal, capable of ingesting and processing data from multiple diverse sources simultaneously. The system handles various data types and formats from different devices and communication protocols through a unified processing framework.
3Manufacturing precision
If predetermined input forms are used, then data can be structured, but they limit the type of data being inputted
Solution Approach 1:
The system performs preliminary processing of oral data to identify and structure key information before full data entry. The oral communication device captures speech and the processing system pre-structures the data by identifying entities, relationships, and contextual information, allowing flexible accommodation of various data types while maintaining proper structure.
Data Source
AI summary
Typical graphical user interfaces and predefined data fields limit the interaction between a person and a computing system. An oral communication device and a data enablement platform are provided for ingesting oral conversational data from people, and using machine learning to provide intelligence. At the front end, an oral conversational bot, or chatbot, interacts with a user. On the backend, the data enablement platform has a computing architecture that ingests data from various external data sources as well as data from internal applications and databases. These data and algorithms are applied to surface new data, identify trends, provide recommendations, infer new understanding, predict actions and events, and automatically act on this computed information. The chatbot then provides audio data that reflects the information computed by the data enablement platform. The system and the devices, for example, are adaptable to various industries.