Anonymous Shopper Panel via Multi-Modal Sensor Fusion

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Solution Overview

Problem

Traditional methods for analyzing shopper behavior in retail environments suffer from low sample sizes, manual operations, and artificial biases due to voluntary participation, failing to create a truly anonymous and large-scale shopper panel that accurately captures dynamic in-store behavior.

Innovation Solution

A multi-modal sensing system using a combination of vision and mobile signal sensors to detect, track, and associate shopper behavior data, forming shopper profiles without explicit participation, enabling the creation of an anonymous shopper panel with larger sample sizes and improved data accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If traditional shopper panels are used where members voluntarily identify themselves, then demographic information and purchase history can be collected, but the sample size remains small and artificial bias is introduced

Engineering Contradiction:

Improvesample sizeVSAvoiddata accuracy

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The patent replaces manual self-reporting mechanisms with automated sensor-based tracking systems. Sensors detect shopper trajectories, product interactions, and purchase behaviors objectively without requiring shopper participation or self-identification, thereby eliminating artificial bias while enabling large-scale data collection

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables shoppers to be studied passively without their active participation. The sensing system automatically collects and analyzes shopper behavior data through environmental sensors, allowing the shopper panel to serve itself without voluntary identification or manual input from shoppers

Inventive Principle:

Principle #25Self-service

2Quantity of substance

If sensors are used to monitor shopper behavior unobtrusively, then large-scale anonymous data can be collected, but the system complexity increases

Engineering Contradiction:

Improvepanel scaleVSAvoidsensing system complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent employs multi-modal sensors that perform multiple functions simultaneously. The same sensor system tracks shopper trajectories, identifies products of interest, monitors time spent in zones, and records purchase behaviors, thereby managing complexity through functional integration rather than proliferation of specialized devices

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system combines multiple sensing modalities (vision sensors, mobile signal sensors, weight sensors) into a unified sensing network. By merging these complementary sensors, the system achieves comprehensive shopper behavior tracking while sharing infrastructure and processing resources, thereby managing overall system complexity

Inventive Principle:

Principle #5Merging (Combining)

3Measurement precision

If multi-modal sensor fusion is implemented for accurate trajectory tracking, then measurement precision improves, but device complexity increases

Engineering Contradiction:

Improvetrajectory tracking accuracyVSAvoidsensor fusion system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces a centralized data fusion server that acts as an intermediary between multiple sensing modalities. This server receives raw data from vision sensors, mobile signal sensors, and weight sensors, performs fusion processing, and outputs integrated trajectory information, thereby managing complexity through centralized mediation rather than distributed coordination

Inventive Principle:

Principle #24Intermediary (Mediator)

4Reliability

If anonymous shopper panels are created without voluntary participation, then artificial bias is eliminated, but household information must be estimated from collected data

Engineering Contradiction:

Improvedata objectivityVSAvoiddemographic information accuracy

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The system shifts from direct measurement of demographic parameters (through self-reporting) to indirect estimation through behavioral parameter analysis. By analyzing shopping patterns, product preferences, trip frequency, and time-of-day behaviors, the system infers demographic characteristics with improved objectivity, trading direct measurement precision for elimination of subjective bias

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11354683B1Method and system for creating anonymous shopper panel using multi-modal sensor fusion

Publication Date: 2022.06.07 VIDEOMINING CORP

AI summary

A method and system for creating an anonymous shopper panel based on multi-modal sensor data fusion. The anonymous shopper panel can serve as the same traditional shopper panel who reports their household information, such as household size, income level, demographics, etc., and their purchase history, yet without any voluntary participation. A configuration of vision sensors and mobile access points can be used to detect and track shoppers as they travel a retail environment. Fusion of those modalities can be used to form a trajectory. The trajectory data can then be associated with Point of Sale data to form a full set of shopper behavior data. Shopper behavior data for a particular visit can then be compared to data from previous shoppers' visits to determine if the shopper is a revisiting shopper. The shopper's data can then be aggregated for multiple visits to the retail location. The aggregated shopper data can be filtered using application-specific criteria to create an anonymous shopper panel.