Retail Store Behavior Tracking for Personalized Shopping
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Solution Overview
Problem
Brick-and-mortar retailers face challenges in providing personalized and relevant shopping experiences due to limited consumer data prior to point-of-sale, leading to showrooming and reduced in-store sales, while online retailers leverage data-driven practices to influence purchasing decisions effectively.
Innovation Solution
A retail store system utilizing MAC address tracking, user eye tracking, object identification, and interactive displays with demographic intelligence to analyze consumer behavior in real-time, enabling personalized marketing and advertising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If brick-and-mortar retailers use traditional monitoring methods (POS data, focus groups, traffic counting), then implementation cost and complexity are low, but consumer purchasing data prior to sale is insufficient leading to inability to provide personalized marketing
Solution Approach 1:
The system performs preliminary tracking and analysis of consumer behavior before the point-of-sale moment. By monitoring consumers as they enter the store and tracking their movements, product interactions, and dwell times in advance, the system builds a profile of purchasing intent before the actual purchase decision is made, enabling proactive personalized marketing interventions.
Solution Approach 2:
The patent introduces mobile devices as intermediaries between the consumer and the retailer's monitoring system. The mobile device captures consumer data (with permission), tracks location and behavior, and serves as a bridge that enables detailed monitoring without requiring complex infrastructure changes in the store itself.
2Adaptability or versatility
If brick-and-mortar retailers implement comprehensive real-time monitoring systems to gather consumer data, then personalized marketing capability is improved, but system complexity and implementation cost increase significantly
Solution Approach 1:
The system leverages the consumer's own mobile device to perform much of the data collection work. The mobile application on the consumer's device handles location tracking, product scanning, and behavior monitoring, effectively making the consumer serve their own monitoring needs while providing valuable data to the retailer without requiring extensive retailer-side infrastructure.
Solution Approach 2:
The mobile device serves multiple functions simultaneously: it acts as a product scanner, location tracker, information display device, purchase recorder, and marketing communication channel. This multi-functionality consolidates what would otherwise require multiple separate systems into a single platform, reducing overall system complexity.
3Loss of information
If retailers use mobile devices to provide product information in-store, then consumer information access is improved, but consumers are directed to competitor sites leading to showrooming and loss of in-store sales
Solution Approach 1:
Instead of directing consumers to external websites for product information (which leads them away from the store), the system inverts the approach by bringing all necessary product information, reviews, pricing, and marketing content directly to the consumer's mobile device within the store. This keeps the consumer engaged in the physical retail environment while providing comprehensive information.
Solution Approach 2:
The retailer-controlled mobile application serves as an intermediary that provides product information without requiring consumers to visit competitor sites. The app delivers reviews, specifications, pricing, and promotional content directly to the consumer's device, eliminating the need to externalize for information while maintaining in-store engagement.
4Adaptability or versatility
If online retailers use data-driven practices to provide optimized messaging, then purchasing influence is improved, but brick-and-mortar retailers lack this ability despite similar data needs
Solution Approach 1:
The system collects and analyzes consumer behavior data in real-time as consumers move through the store, enabling optimized messaging similar to online retailers. By tracking which products consumers view, how long they spend at each location, and their movement patterns, the system builds behavioral profiles that inform personalized marketing messages delivered via mobile devices throughout the shopping experience.
Data Source
AI summary
Method and systems for shopping in a retail store. The methods and systems include using information monitoring devices to identify a person at a retail store, using the information monitoring devices to gather shopping information of the person at the retail store (including traffic information, product interaction information, and object identification information of the person), analyzing by the system the gathered shopping information to generate and maintain a list of the products that the person retained while shopping, using the information monitoring devices to track the first person to a point-of-sale area of the retail store, in response to the person being tracked to the point-of sale area, interfacing the system with a payment system for payment by the person of the list of the products, and transmitting a receipt to the person after payment.