Retail Behavior Tracking for Real-Time Personalized Product Marketing

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Solution Overview

Problem

Brick-and-mortar retailers face challenges in providing personalized and relevant marketing to customers due to limited data on consumer behavior prior to purchase, 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 demographic intelligence to analyze consumer behavior in real-time, enabling personalized digital experiences through interactive displays and automated customer assistance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If brick-and-mortar retailers use traditional POS data and focus groups to understand consumer behavior, then they can obtain some purchasing information, but they lack real-time data on consumer behavior prior to purchase

Engineering Contradiction:

Improveconsumer behavior data prior to purchaseVSAvoidreal-time data availability

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system performs preliminary tracking and analysis of consumer behavior before the actual purchase occurs. By monitoring consumers as they enter the store and tracking their movements, product interactions, and dwell times in advance of the purchase decision, the system captures behavioral data that traditional POS systems miss, providing retailers with predictive insights rather than retrospective information only

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback loops where consumer behavior data is collected in real-time through tracking devices, analyzed by machine learning algorithms, and immediately fed back to personalize marketing messages and adjust pricing dynamically. This closed-loop system allows retailers to respond to consumer actions as they happen, bridging the information gap between traditional POS data and real-time decision-making

Inventive Principle:

Principle #23Feedback

2Ease of operation

If brick-and-mortar retailers provide generic marketing messages to all customers, then they can simplify operations, but they cannot personalize marketing to influence purchasing decisions effectively

Engineering Contradiction:

Improvemarketing delivery simplicityVSAvoidsales conversion rate

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system dynamically adjusts marketing messages based on real-time consumer behavior data. As consumers move through the store and interact with products, the system modifies pricing, promotions, and messaging on digital signage and mobile devices to match their demonstrated interests and purchasing intent, transforming static generic marketing into adaptive personalized communication without requiring complex manual intervention

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system enables automated personalization where machine learning algorithms independently analyze consumer behavior patterns and generate personalized marketing content without human intervention. The system self-adjusts pricing strategies, selects relevant product recommendations, and delivers customized messages based on tracked consumer actions, reducing operational complexity while enhancing marketing effectiveness

Inventive Principle:

Principle #25Self-service

3Productivity

If online retailers use data-driven practices to provide optimized messaging, then they can influence purchasing decisions effectively, but brick-and-mortar retailers lack this ability

Engineering Contradiction:

Improvepurchasing decision influenceVSAvoidsystem infrastructure requirements

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system creates a universal platform that combines multiple functions: consumer tracking, behavior analysis, dynamic pricing, personalized messaging, and inventory management into a single integrated system. This multi-functional approach allows brick-and-mortar retailers to achieve online-level data-driven marketing capabilities without implementing separate complex systems for each function, reducing overall infrastructure complexity while enhancing purchasing decision influence

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250390897A1Methods for personalized marketing and advertising of retail products

Publication Date: 2025.12.25 ALPHA MODUS CORP

AI summary

Method for personalized marketing or advertising of products for purchase from retail stores. Generally, the method includes utilizing information monitoring devices to gather activities of the persons, including product interaction information, to obtain an information analysis about the consumer activities of the persons, further includes tracking the persons utilizing information monitoring devices, and further includes providing the persons a communication to a retailer location at which the persons can purchase related products. Such communication to the persons further includes product communications regarding the product, such as price, placement, marketing/advertising information, coupons regarding the products and related products, and purchase options regarding the products.