Offer Interface Platform for Multi-Provider Ad Aggregation
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Solution Overview
Problem
Organizations face inefficiencies when outsourcing targeting to a single third party, as they can only utilize recommendations from that one provider, limiting the diversity of offers presented to customers.
Innovation Solution
A system and method for providing offer interface platforms, which involves a centralized recommendation engine that requests offers from multiple offer providers based on customer context, ranks these offers, and caches them for display on mobile devices, ensuring a uniform customer experience across multiple channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If only one third party is used to provide targeted recommendations, then a uniform customer experience is maintained, but the diversity of offers presented to customers is limited
Solution Approach 1:
The system segments the recommendation functionality by separating the offer aggregation layer (multiple third-party providers) from the customer interaction layer (uniform interface). The patent implements this by creating a modular architecture where different offer providers can be independently integrated through standardized interfaces, allowing diverse offers to be collected without increasing customer-facing complexity.
Solution Approach 2:
The patent introduces an intermediary recommendation engine that sits between multiple offer providers and the customer interface. This mediator aggregates offers from multiple third parties, standardizes their formats, and presents them through a unified interface, thereby maintaining simplicity for customers while enabling diverse offer sources.
2Adaptability or versatility
If multiple offer providers are queried for offers, then the diversity and quality of offers improve, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching offers from multiple providers in advance, before they are actually needed for customer presentation. The patent implements offer caching mechanisms that store previously retrieved offers, allowing the system to serve customers quickly without querying all providers in real-time, thus reducing processing time while maintaining offer diversity.
Solution Approach 2:
The patent applies partial action by selectively querying only the most relevant offer providers based on customer context, rather than always querying all available providers. The system can dynamically adjust the number and type of providers queried based on factors like customer preferences, context relevance, and current performance metrics, optimizing the balance between offer diversity and processing time.
3Speed
If offers are cached for faster retrieval, then the response time improves, but the freshness and relevance of offers may decrease
Solution Approach 1:
The system implements periodic action by establishing time-based expiration policies for cached offers and periodically refreshing them. The patent defines cache validity periods after which offers must be re-queried from providers, ensuring that cached content is periodically updated to maintain freshness while still benefiting from caching performance during valid periods.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor offer performance, customer interactions, and temporal relevance. This feedback informs dynamic cache management decisions, such as extending cache duration for high-performing offers or triggering premature refreshes for time-sensitive offers, thus balancing response time and offer freshness based on actual performance data.
Data Source
AI summary
A method may include a centralized recommendation engine computer program receiving a request for content to display on a mobile electronic device from an ad framework, and requesting offers for the customer based on the customer context from an offer interface platform; the offer interface platform querying a plurality of offer providers for offers, receiving a plurality of ranked offers and an offer identifier for each ranked offer from each of the plurality of offer providers and caching the plurality of ranked offers and an offer identifier for each ranked offer; the centralized recommendation engine computer program receiving the offer identifiers for the ranked offers and providing the offer identifiers for the ranked offers to the ad framework. The ad framework requests content for the ranked offers associated with the offer identifiers from the offer interface platform and generates a webpage with the content in the spaces.