Social Search Keyword Optimizer Using User Feedback
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Solution Overview
Problem
Businesses face difficulties in identifying unique search keywords and phrases used by consumers to find their websites through internet searches, as existing solutions only provide synonyms and common related terms, lacking the diversity and relevance provided by human input.
Innovation Solution
A method and system that leverages social networks to gather search keyword recommendations from a business's followers, ranking and presenting these keywords to the business for incorporation into their website's content or metadata, enhancing SEO by utilizing human feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing software solutions are used to generate search keywords, then the process is automated and quick, but the quality and diversity of keywords are limited to synonyms and common related terms
Solution Approach 1:
The system implements feedback loops where users interact with keyword suggestions, rating and selecting relevant keywords. This feedback mechanism allows the system to learn from user preferences and improve keyword quality over time, resolving the contradiction between automated speed and keyword relevance by incorporating human judgment into the feedback cycle
Solution Approach 2:
The patent introduces social network users as intermediaries who bridge the gap between automated keyword generation and human expertise. These users act as mediators by providing ratings and selections on keyword suggestions, transferring their domain knowledge to the system without requiring full manual keyword creation, thus maintaining productivity while improving keyword quality
2Loss of information
If manual keyword research is performed to identify unique search terms, then keyword quality and relevance improve, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system applies partial action by having users perform limited evaluation tasks rather than complete manual keyword research. Users only need to rate and select from pre-generated keyword suggestions rather than conducting exhaustive research themselves, achieving high keyword quality through partial human involvement that significantly reduces time investment compared to full manual research
Solution Approach 2:
The system performs preliminary action by automatically generating keyword suggestions and rankings before user evaluation. This pre-processing step filters and organizes potential keywords using automated algorithms, so that when users review the suggestions, they are already narrowed down to relevant options, reducing the time users need to spend on keyword research while maintaining quality
3Loss of information
If social network users are engaged to provide keyword recommendations, then keyword diversity and relevance improve through human input, but the system complexity and implementation effort increase
Solution Approach 1:
The system applies universality by utilizing the existing social network infrastructure for multiple purposes: user authentication, communication channels, and data collection mechanisms. The social network platform already provides user profiles, messaging systems, and interaction tracking, which the patent leverages for keyword recommendation collection, reducing implementation complexity by reusing established multi-functional systems rather than building dedicated infrastructure
Solution Approach 2:
The system implements self-service by allowing users to naturally provide keyword recommendations through their existing social network activities and interactions. Users don't need to be explicitly recruited or trained; their normal engagement with the platform and the business automatically generates valuable keyword data, reducing the complexity of user onboarding and data collection processes
Data Source
AI summary
Methods, systems, and computer program products for identifying search keywords for searching for an online information resource are disclosed. The method involves receiving a request, from a business, for search keywords relating to the content of the business's online information resource. The method further involves generating a post including a link to a search keyword recommendation page; and publishing, using a social network application, the post to a newsfeed in a social network. Additionally, the method involves receiving, from social network users, a plurality of search keywords relating to the online information resource's content. In addition, the method involves ranking the received search keywords; and presenting, to the business, the most popular search keywords. Further, the method involves receiving, from the business, a selection of search keywords from the most popular keywords; and publishing the business's online information resource to include the search keywords that were selected by the business.