Gesture-Based Customer Referral Score Detection
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Solution Overview
Problem
The difficulty in calculating customer referral scores due to declining survey response rates and unwillingness to provide feedback makes it challenging to determine client satisfaction effectively.
Innovation Solution
A human gesture-based system using computer vision algorithms to detect customers through cameras at business locations, prompting them to provide gestures indicating their experience, and automatically determining a customer referral score, which can be aggregated in real-time with previous scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional surveys are sent to customers to calculate referral scores, then customer satisfaction can be measured, but response rates are declining and customers are unwilling to provide feedback
Solution Approach 1:
The patent replaces the mechanical survey system (questionnaires, emails, forms) with a computer vision-based gesture recognition system. Cameras capture customer gestures automatically, and algorithms interpret these gestures to determine referral intent, eliminating the need for customer participation in surveys while maintaining measurement capability
Solution Approach 2:
The system allows customers to provide feedback through natural gestures without active participation. The gesture recognition system automatically detects and interprets gestures, enabling the measurement process to occur passively as customers naturally move through the business premises
2Loss of information
If surveys are used to determine customer referral scores, then feedback can be collected, but the process is time-consuming and delays score calculation
Solution Approach 1:
The gesture recognition system operates continuously as customers move through the business, capturing gestures in real-time without interruption. This eliminates the discrete, time-delayed nature of survey collection and enables ongoing, immediate feedback accumulation
Solution Approach 2:
The system captures gestures at the moment of customer experience (in-store), before customers leave. This preliminary capture of feedback intent eliminates the delay inherent in post-experience survey completion, allowing scores to be calculated based on immediate reactions
3Reliability
If manual survey processing is used, then customer feedback can be analyzed, but the system complexity and operational burden increase
Solution Approach 1:
The patent replaces manual survey processing with automated computer vision and machine learning systems. Cameras and algorithms automatically detect, classify, and interpret gestures, eliminating manual data collection and analysis while improving measurement reliability through consistent, objective interpretation
Solution Approach 2:
The system introduces computer vision algorithms and gesture recognition models as intermediaries between customer behavior and referral score calculation. These intermediaries automatically translate physical gestures into meaningful feedback data, reducing operational burden while maintaining measurement accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method increases the efficiency of customer referral score determination by engaging customers at the point of service or exit, providing real-time feedback that reflects their willingness to refer the business, thereby improving the accuracy and timeliness of client satisfaction metrics.
Implementation Method 1
identifying the gesture through the camera using computer vision algorithms
Data Source
AI summary
Embodiments of the disclosure provide a method, apparatus, system and computer program product for human gesture-based customer referral score determination. In an embodiment of the disclosure, the method includes detecting a customer through a camera installed at a location of the business and prompting the customer in a display at the location of the business to provide a gesture indicating whether the customer had a good experience and thereby likely to be willing to refer the business to others. The method further includes identifying the gesture through the camera using computer vision algorithms and responsive to identifying the gesture, automatically determining a customer referral score for the customer.