UI Orchestration via Predictive Recommendations and Clean Room Storage
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Solution Overview
Problem
Existing user interface payment flows rely on static logic, providing non-customized results, and are challenged by the decline of tracking cookies due to privacy concerns, necessitating an improved approach for targeted and consent-based analytics, recommendations, and coupon delivery.
Innovation Solution
An improved approach for orchestrating user interface journeys using computer-generated predictive recommendations, which are generated based on user behavior, profile data, and population-level characteristics, and are computationally instantiated as triggered data objects to enhance the user experience with personalized offers and coupons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tracking cookies are used for analytics and targeted advertising, then user behavior tracking precision is improved, but user privacy protection deteriorates
Solution Approach 1:
The patent introduces a trusted intermediary system (clearinghouse) that acts as a mediator between data collectors and data subjects. This intermediary verifies consent, manages anonymization, and controls data access without requiring direct trust between collecting parties and users, thus enabling tracking while protecting privacy through a neutral third party.
Solution Approach 2:
The patent creates anonymized copies of user data that can be shared and analyzed without exposing identifiable information. By working with copied and transformed data rather than raw personal data, the system enables behavioral tracking and targeted advertising while preventing direct identification of individual users.
2Device complexity
If static logic is used for user interface payment flows, then system complexity is reduced, but personalization capability deteriorates
Solution Approach 1:
The patent transforms static payment flows into dynamic, adaptive systems that automatically adjust based on user behavior, preferences, and contextual factors. The system dynamically generates personalized offers, recommendations, and payment options without requiring complex manual configuration, achieving adaptability through automated decision-making algorithms.
Solution Approach 2:
The system enables self-service personalization where the automated platform independently analyzes user data, generates personalized content, and adjusts payment flows without human intervention. This self-organizing capability provides high personalization while keeping operational complexity manageable through automation.
3Measurement precision
If comprehensive user data is collected for predictive recommendations, then recommendation accuracy is improved, but data storage security requirements increase
Solution Approach 1:
The patent creates and distributes anonymized copies of user data to multiple authorized parties through a trusted clearinghouse. This enables comprehensive data utilization for accurate recommendations while distributing storage responsibilities and reducing the security burden on any single entity, as no single party holds the complete sensitive dataset.
Solution Approach 2:
The trusted intermediary (clearinghouse) secures the central repository of user data and manages controlled access for authorized entities. This centralized secure storage with controlled access pathways enables high recommendation accuracy while concentrating security management in a dedicated, auditable system rather than分散 across multiple storage locations.
Data Source
AI summary
There is provided a computer system and method for orchestrating user interface, the method include: obtaining a first data set representative of intercepted data communication messages between a user interface of a user and a merchant hosting server; obtaining a second data set representing an instruction set for loading visual elements on the user interface provided from the merchant hosting server; analyzing the first data set to obtain one or more user-specific characteristics; determining if the user-specific characteristics associated with the user satisfy a trigger condition associated with a current resource offering; and responsive to a positive determination: injecting, into the instruction set for loading the visual elements on the user interface provided from the merchant hosting server, code corresponding to an interactive visual element corresponding to the current resource offering.