Retail Display Space Valuation Using Sensor-Based Traffic Density
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Determining the value of display space in different regions of a retail store is challenging due to the lack of reliable, accurate, and unbiased methods, making it difficult to quantify the value of display space based on customer traffic.
Innovation Solution
Measuring traffic density in retail store regions using sensors that capture spatial information, including customer presence, interaction time, and product engagement, to provide a quantitative metric for determining the value of display space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to estimate display space value, then the process is simple, but the reliability and accuracy of the value determination is poor
Solution Approach 1:
The patent replaces traditional mechanical/manual estimation methods with sensor-based automated measurement systems. Sensors detect customer presence, movement, and interaction with display spaces, converting physical behaviors into digital data for accurate traffic density calculation and display space valuation.
Solution Approach 2:
The patent introduces sensors as intermediary devices between customers and the display space valuation system. These sensors act as mediators that collect spatial information about customer behavior and transmit it to the processing system, enabling objective and accurate measurement without direct human intervention.
2Reliability
If sensor-based traffic density measurement is implemented, then the accuracy of display space valuation is improved, but the device complexity increases
Solution Approach 1:
The patent employs multi-functional sensors that can detect multiple aspects of customer behavior (presence, movement, interaction) simultaneously. This universal approach allows a single sensor system to gather comprehensive data for traffic density calculation, reducing the need for multiple specialized devices and thereby managing complexity while improving reliability.
Solution Approach 2:
The sensor system automatically performs data collection, processing, and analysis without requiring manual intervention. The system self-manages the entire measurement process from detecting customer spatial information to calculating traffic density and determining display space values, reducing operational complexity while maintaining high reliability.
3Measurement precision
If comprehensive spatial information is collected from sensors, then the accuracy of traffic density measurement is improved, but the quantity of data to be processed increases
Solution Approach 1:
The patent extracts only the essential spatial information features needed for traffic density calculation from the comprehensive sensor data. By selectively extracting relevant parameters such as customer presence duration, movement patterns, and interaction frequency, the system maintains high measurement precision while reducing the volume of data requiring processing and storage.
4Ease of operation
If manual estimation of customer traffic value is used, then the system is easy to operate, but the objectivity and unbiased nature of the measurement is compromised
Solution Approach 1:
The sensor-based system automatically performs all measurements and calculations without requiring human operators. The system self-collects spatial data, processes it through predefined algorithms, and generates objective traffic density values, eliminating subjective biases while maintaining ease of operation through automated workflows.
Solution Approach 2:
The patent implements a feedback mechanism where sensor data continuously informs the traffic density calculation and display space valuation. This closed-loop system provides real-time, objective feedback based on actual customer behavior, ensuring unbiased measurements while simplifying operation through automated decision-support.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Computer-implemented systems and methods for determining the value of display space in a retail store are provided. These values of display space are determined based on measured traffic densities in the retail store. Traffic density is used as a metric for real-world customer activity and customer patterns in the retail store. To determine traffic density, measurements are obtained from one or more sensors in the retail store, where the measurements include spatial information pertaining to a region of the retail store. Traffic density can provide a quantitative, accurate and unbiased metric with which to determine a value associated with displaying products in a region of the retail store.