Mobile Purchase Offer Verification for Real-Time In-Store Personalization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies fail to provide personalized and relevant in-store purchase offers to consumers based on their shopping behavior and interest, and lack real-time validation mechanisms for customers to redeem these offers.
Innovation Solution
A system and method that utilizes a control system to generate personalized purchase offers on a consumer's mobile device based on event data, including historical shopping behavior and data from other devices, and provides an optically readable code for real-time validation at the point of sale.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If QR codes are used to direct customers to social media or product information, then customer engagement and information access are improved, but the system cannot capture real-time in-store shopping behavior data
Solution Approach 1:
The patent introduces a mobile device application as an intermediary between the customer and the retail system. This intermediary captures shopping behavior data (product scans, dwell time, basket additions) and transmits it to the server, enabling real-time personalized offer generation without disrupting the customer's natural shopping experience.
Solution Approach 2:
The system implements a feedback loop where customer shopping behavior is continuously monitored, analyzed, and used to generate personalized offers that are pushed back to the customer's mobile device in real-time. This closed-loop feedback enables dynamic adaptation to customer preferences and shopping patterns.
2Productivity
If personalized purchase offers are provided based on shopping behavior, then customer loyalty and sales conversion are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system architecture is segmented into distinct modular components: mobile device application for data collection, communication module for data transmission, server for data processing and offer generation, and display module for presenting offers. This segmentation allows each component to be optimized independently and simplifies maintenance and scaling.
Solution Approach 2:
The system enables self-service personalization where the automated server analyzes customer behavior patterns and generates personalized offers without requiring manual intervention from store staff. This reduces operational complexity while maintaining high levels of personalization.
3Reliability
If real-time validation and verification mechanisms are implemented for purchase offers, then fraud prevention and offer security are improved, but transaction processing time and operational complexity increase
Solution Approach 1:
The system performs preliminary validation by pre- verifying customer eligibility, offer availability, and product inventory status before the purchase transaction occurs. The mobile application receives and validates purchase offers in advance, so that at the point of sale, verification is already complete or can be quickly confirmed.
Solution Approach 2:
The system creates a digital copy of the purchase offer and validation data that can be quickly transmitted and verified between the mobile device, server, and point-of-sale system. This digital copying enables rapid verification without requiring physical document handling or complex manual checks.
4Measurement precision
If comprehensive event data is collected from mobile devices, then offer personalization accuracy is improved, but customer privacy concerns and data security requirements increase
Solution Approach 1:
The system processes and analyzes customer data locally on the mobile device where possible, and only transmits aggregated or anonymized data to the server. Sensitive personal information remains on the customer's device, while the server receives only the minimum necessary data for offer generation, reducing privacy risks.
Solution Approach 2:
The system transforms raw customer behavior data into anonymized statistical parameters and patterns that retain the information needed for personalization while removing personally identifiable information. This parameter transformation maintains measurement precision for offer accuracy while mitigating privacy concerns.
Data Source
AI summary
The present invention relates to systems, methods and computer program products for providing in-store purchase offers. A control system is configured to receive event data from a mobile device and provide purchase offers based on obtained event data. An optically readable code for verifying that the customer is authorized to take advantage of a purchase offer is displayed on the customer's mobile device in response to an identified event. The consumer is provided with a purchase offer including at least a second product different from the first product associated with an image acquired by the mobile device.