Personalized Search Engine Results Using Reward Program Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current search engines provide generic, non-customized search results that do not account for individual consumers' reward program memberships, leading to inefficiencies in identifying and acquiring relevant items, as consumers must manually sift through results to find discounted or free options.
Innovation Solution
A framework that aggregates reward program data to generate personalized search engine results by integrating machine learning algorithms to identify redeemable rewards and prioritize search results based on consumer preferences, allowing for streamlined item acquisition and reward redemption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generic search results are provided to all consumers, then the search system is simple and fast, but the search results do not match individual consumer preferences and require more review time
Solution Approach 1:
The system performs preliminary actions by aggregating reward program data and determining consumer preferences before generating search results. This allows the search results to be pre-customized according to each consumer's reward preferences, eliminating the need for manual filtering and improving item acquisition efficiency without requiring complex real-time processing during the search itself
Solution Approach 2:
The system enables self-service by automatically matching search results with consumer reward program benefits without requiring consumer intervention. The service provider autonomously determines which rewards are redeemable for each search result and prioritizes results accordingly, allowing consumers to efficiently acquire items that align with their rewards without manually searching or filtering results
2Loss of time
If search results are customized based on consumer preferences, then item identification is faster, but data processing complexity increases
Solution Approach 1:
The system determines consumer preferences and aggregates reward program data in advance, before generating search results. This preliminary processing allows the system to quickly retrieve and display pre-customized results without requiring complex real-time analysis during the search operation, reducing review time while managing data processing complexity through pre-computation
Solution Approach 2:
The system introduces an intermediary layer that aggregates reward program data from multiple sources and translates it into preference-based search result prioritization. This intermediary processing layer simplifies the overall system architecture by handling data aggregation and preference matching separately from the core search functionality, reducing both review time and processing complexity
3Productivity
If reward program data is aggregated and integrated into search results, then reward utilization is optimized, but system complexity increases
Solution Approach 1:
The system merges reward program data aggregation, preference determination, and search result generation into a unified framework. By combining these functions into a single integrated system, the patent reduces overall complexity compared to having separate systems for each function, while optimizing reward utilization through seamless integration of reward data with search results
Solution Approach 2:
The service provider system performs multiple functions including reward program data aggregation, consumer preference determination, search result generation, and reward redemption facilitation. This multi-functional approach consolidates what could be separate complex systems into a single versatile platform, optimizing reward redemption efficiency while managing complexity through functional integration
Data Source
AI summary
Managing reward program memberships and corresponding rewards for generating personalized search engine results pages is described. A service provider may receive a search query associated with an item and access a plurality of search results associated with the search query. Each search result may correspond to a listing associated with the item. The service provider may access reward program data including data associated with rewards available from a plurality of reward programs and may determine a reward is redeemable for listing corresponding to a search result of the plurality of search results. The service provider may generate a personalized search result based at least partly a determination that a reward is redeemable for the listing and may generate a personalized search engine results page to be presented via a device.