Retail Purchase Intent Detection With Sales Rep Matching
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Solution Overview
Problem
Current human-computer interaction methods lack efficient two-way communication systems that can determine user intent to purchase and automatically identify the appropriate sales representative in real-time, especially in retail environments.
Innovation Solution
A distributed data processing environment that includes a Centralized System (Csys) server, item tags, retail devices, and cognitive servers, which facilitate two-way communication between users and items, determine user intent through natural language processing and facial recognition, and alert appropriate sales representatives via a network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional human-computer interaction methods are used, then system simplicity is maintained, but user intent detection accuracy and sales representative identification efficiency deteriorate
Solution Approach 1:
The system is divided into distinct functional modules: a communication module for two-way interaction, an intent determination module for analyzing user responses, and a sales representative identification module for matching users with appropriate representatives. This segmentation allows each module to specialize in its function, improving overall accuracy while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary system that acts as a bridge between users and sales representatives. This intermediary automatically processes communications, determines purchase intent through analysis of user responses, and identifies appropriate sales representatives, thereby improving detection accuracy without requiring direct complex interactions between users and representatives.
2Productivity
If automated intent determination is implemented, then sales completion efficiency is improved, but communication system complexity increases
Solution Approach 1:
The communication system performs self-service by automatically determining user intent through analysis of user responses without requiring manual intervention. The system autonomously processes communications, evaluates responses against predefined criteria, and generates intent determinations, thereby improving sales completion efficiency while keeping the automation architecture manageable.
Solution Approach 2:
The system performs preliminary actions by pre-defining intent criteria and sales representative matching rules before actual user interactions occur. This allows the automated intent determination to proceed efficiently during actual sales interactions, as the framework for evaluation and matching is already in place, improving productivity without proportionally increasing operational complexity.
3Ease of operation
If manual sales representative assignment is used, then system simplicity is maintained, but customer satisfaction and sales efficiency deteriorate
Solution Approach 1:
The system implements feedback mechanisms where user responses during communication are continuously analyzed to determine intent. This feedback loop allows the system to dynamically assess customer needs and automatically identify the most appropriate sales representative based on real-time interaction data, thereby improving customer satisfaction through more accurate matching while maintaining reasonable automation levels.
Solution Approach 2:
The patent utilizes parameter changes in user responses during communication to dynamically adjust intent determination. By monitoring changes in communication parameters such as response content, tone, and engagement level, the system can accurately gauge purchase intent and automatically identify suitable sales representatives, improving ease of operation through better customer matching without excessive automation.
Data Source
AI summary
The method includes receiving a location of a client device and one or more items of interest to a user of the client device. The method further includes determining that the location of the client device is within a threshold distance of an item of the one or more items of interest. The method further includes generating a communication with the user of the client device. The method further includes receiving a response from the user of the client device. The method further includes determining if the received response indicates an intent to purchase the item. In one embodiment, the method further includes identifying a sales representative to assist the user of the client device, responsive to determining that the received response indicates an intent to purchase the item.