AI-Generated Search Pages for Poor Landing Page Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional search result pages often have poorly designed landing pages that are difficult to navigate, leading to a suboptimal user experience and reduced engagement.
Innovation Solution
A computing system utilizing machine-learned models to generate AI-generated pages tailored to user queries, incorporating previous search history and contextual information, with features like call-to-action buttons, product feeds, and AI chatbots, to enhance usability and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional landing pages are used in search results, then organizations can maintain their existing web presence, but user experience deteriorates due to poor navigation and usability
Solution Approach 1:
An AI-generated intermediary page is introduced between the search engine and the organization's landing page. This intermediary page aggregates content from multiple sources including the landing page, product feeds, and reviews, presenting a unified and user-friendly interface that improves navigation and usability without requiring the organization to redesign their existing landing page.
Solution Approach 2:
The AI-generated page segments and organizes content from various sources into distinct, easily navigable sections. It separates product information, reviews, and calls-to-action into structured components that improve user experience while maintaining the integrity of the original landing page content.
2Productivity
If AI-generated pages are created to improve user experience, then engagement increases, but system complexity increases due to machine-learned models and content aggregation
Solution Approach 1:
The system employs machine-learned models that automatically aggregate, synthesize, and generate content for the AI-generated pages without manual intervention. The models self-adjust based on performance metrics like conversion rates and engagement, reducing the need for complex manual system management while improving productivity.
Solution Approach 2:
The system dynamically adjusts parameters such as content weighting, layout configuration, and call-to-action placement based on learned user behavior patterns and performance metrics. This allows the system to optimize conversion rates automatically without requiring complex manual reconfiguration.
3Loss of information
If personalized content is generated based on user context, then relevance improves, but processing time increases due to contextual analysis
Solution Approach 1:
The system pre-Processes and caches content from product feeds, reviews, and landing pages before they are needed for AI-generated page assembly. Contextual information about user preferences and behavior is also pre-analyzed, allowing the system to quickly assemble relevant content without extensive real-time processing.
Solution Approach 2:
The system applies different levels of contextual analysis to different content elements based on their importance. High-priority elements like product information receive more thorough contextual matching, while less critical elements use simpler matching rules, optimizing the balance between relevance and processing time.
Data Source
AI summary
Techniques for generating an artificial intelligence (AI)-generated page for a first organization. The system can include a machine-learned model configured to generate the AI-generated page. The system can receive from a user device associated with a user account, the user query. Additionally, the system can generate a search result page for the user query. The search result page can include a first result associated with a first landing page of the first organization. The system can calculate a landing page score for the first landing page. The system can generate an updated search result page based on the landing page score exceeding a threshold value, the updated search result page having a navigation link to an AI-generated page for the first organization. The system can cause a presentation, on a display of the user device, the updated search result page.