Receipt-Based Consumer Profiling for Targeted Content Delivery
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Solution Overview
Problem
Content providers face challenges in effectively distributing targeted advertisements and content to individuals based on their consumption habits, as existing methods rely heavily on demographic and performance data, which may not accurately predict future consumer behavior.
Innovation Solution
A system that analyzes information from users' receipts to create profiles that predict consumer behavior, allowing for the selection and delivery of targeted content, such as advertisements, by associating user accounts with profiles based on purchase history and preferences, while ensuring user privacy through anonymous identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If demographic information and performance information are used for content distribution, then content can be distributed to selected recipients, but the accuracy of predicting future consumer behavior is insufficient
Solution Approach 1:
The patent changes the parameter used for consumer profiling from demographic and performance information to transactional information (purchase history, product categories, brands). This parameter change enables more accurate prediction of future consumer behavior by using actual purchase data rather than indirect demographic proxies.
Solution Approach 2:
The system continuously updates consumer profiles based on new transactional data from receipts, creating a feedback loop where past purchase behavior directly informs future content distribution decisions. This feedback mechanism allows the system to adapt to changing consumer preferences more accurately than static demographic data.
2Measurement precision
If transactional information from receipts is collected and analyzed, then content targeting accuracy is improved, but user privacy protection becomes more challenging
Solution Approach 1:
The patent extracts only the necessary transactional information (product categories, brands, prices, dates) from receipts while leaving out personally identifiable information. This extraction approach enables accurate content targeting based on purchase patterns without exposing user identity or sensitive personal data.
Solution Approach 2:
The system uses an intermediary processing layer that analyzes transactional data to create consumer profiles and purchase preferences, then uses these aggregated insights for content distribution without directly exposing the raw transactional data or user identity to content providers. This intermediary layer protects privacy while enabling targeting.
3Object-affected harmful factors
If generic profiles with pre-determined membership criteria are used, then user privacy is protected through anonymous identifiers, but the ability to identify specific users is limited
Solution Approach 1:
The patent creates a copy of user behavior patterns through aggregated transactional data and generic profiles, which can be used for content distribution without containing actual user identity information. These profile copies capture purchasing patterns while maintaining anonymity, allowing targeted content delivery without exposing personal identifiers.
Data Source
AI summary
Content providers can target individuals for receipt of selected content based, at least in part, on profiles associated with users. The associations between the users and the profiles are determined based on analysis of receipts for transactions completed by the users. These receipts contain information that is indicative of the individuals' spending habits. Electronic correspondence associated with the users is scanned to identify the receipts and information is extracted from the receipts for use in the analysis. The individuals can opt-in to receive content targeted to the profiles associated with their accounts without allowing the content providers to have direct access to their receipts or their identity. The individuals can also opt-out if they no longer want to receive targeted content.