Page Type-Based Ad Matching for E-Commerce
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Solution Overview
Problem
Current e-commerce advertising systems, such as Google Adsense, rely on keyword-based advertising which can lead to increased bounce rates on retailer websites and fail to optimize ad performance for different page types, resulting in suboptimal ad relevance and revenue generation.
Innovation Solution
A system and method for page type-based advertisement matching on e-commerce websites that merges customer, page type, item, inventory, and competitor data to tailor ads for each page type, using a module selection and ranking engine to provide contextually relevant sponsored product listings and optimize ad performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If keyword-based advertising (Google Adsense) is used, then ad revenue can be generated, but bounce rates increase and ad relevance deteriorates
Solution Approach 1:
The system changes the fundamental parameter of ad matching from keyword-based to context-based matching. By analyzing page type, user behavior, and product attributes, the system dynamically determines ad relevance rather than relying on static keyword matching, thereby reducing bounce rates while improving ad relevance
Solution Approach 2:
The patent introduces an intermediary ad matching system that sits between the user/page and the advertisement. This intermediary analyzes multiple factors including page type characteristics, user behavior patterns, and product attributes to mediate the selection of relevant ads, preventing direct mismatches that cause bounce rates
2Device complexity
If generic advertising is used across all pages, then system complexity is reduced, but ad performance for different page types deteriorates
Solution Approach 1:
The system segments the website into different page types (homepage, category pages, product detail pages, etc.) and creates specific ad matching strategies for each segment. This segmentation allows the system to optimize ad performance for each page type without requiring complete system redesign, managing complexity through modular segmentation
Solution Approach 2:
The patent creates a universal ad matching framework that handles multiple page types through a common system architecture. The system uses a unified approach of analyzing page characteristics, user behavior, and product attributes across all page types, providing multi-functional capability while maintaining manageable system complexity
3Ease of operation
If advertisers use bid prices to increase product reach, then ad visibility improves, but ad performance optimization deteriorates
Solution Approach 1:
The system implements feedback mechanisms that track ad performance metrics including clicks, conversions, and bounce rates. This feedback is used to continuously optimize ad matching, allowing the system to balance bid-based reach control with performance optimization by adjusting ad placement decisions based on actual performance data
Data Source
AI summary
A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more computer processors and perform configuring one or more advertisements for a sponsored product customized to fit a page type associated with a page format of a website; analyzing one or more inputs to create merged data; generating a respective rank of the advertisements of the sponsored product using a conversion probability; adjusting the respective rank the one or more advertisements of the sponsored product as a function of the merged data; automatically designating one of the one or more advertisements of the sponsored product that is ranked higher than other advertisements to be positioned closest to a predefined portion of a webpage; and sending instructions to display the one of the one or more advertisements closest to the predefined portion of the webpage of the website. Other embodiments are disclosed.