Vertical-Specific Search Rank Scoring for Interactive Online Visibility
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Solution Overview
Problem
Existing search engine optimization (SEO) solutions do not provide an interactive way for business entities to adjust their online presence to effectively improve search engine rankings, as they focus on general factors without considering the specific aspects important to different vertical business segments.
Innovation Solution
A system and method that assesses and improves specific aspects of a business entity's online presence, including profile completeness, review metrics, review replies, website analysis, and social media integration, tailored to the vertical business segment, using a search rank score (SRS) system that allows interactive adjustment and real-time feedback on improvements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If general SEO solutions are used to improve search engine rankings, then online visibility may be improved to some extent, but the solution lacks interactivity and does not account for specific vertical business segment requirements
Solution Approach 1:
The system applies local quality by tailoring SEO strategies to specific vertical business segments (e.g., healthcare, legal, finance) rather than using generic approaches. Each segment receives customized optimization based on its unique characteristics, requirements, and competitive landscape, making the solution both adaptable and interactive.
Solution Approach 2:
The system implements dynamics by providing real-time feedback mechanisms that allow business entities to interactively adjust their online presence parameters. The system dynamically updates search rank scores and provides immediate feedback on the impact of adjustments, enabling continuous optimization rather than static one-time solutions.
2Measurement precision
If comprehensive factors are considered for search ranking (reviews, proximity, relevance, operating duration), then ranking accuracy is improved, but the system complexity increases
Solution Approach 1:
The system segments the complex evaluation process into distinct components: profile completeness assessment, review metrics analysis, website quality evaluation, and social media integration measurement. Each component is evaluated separately and then aggregated into an overall search rank score, making the complex system more manageable and interpretable.
Solution Approach 2:
The system introduces an intermediary layer that collects and processes data from multiple sources (third-party review platforms, social media sites, website analytics) before presenting a unified search rank score to the business entity. This intermediary simplifies the complexity by consolidating multiple evaluation dimensions into a single actionable metric.
3Ease of operation
If real-time feedback and interactive adjustment capabilities are added to improve user control, then ease of operation is improved, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating baseline metrics and establishing evaluation frameworks before actual adjustments are made. When business entities make adjustments to their online presence, the system can quickly compute the impact because the evaluation structure is already in place, reducing processing time while maintaining interactivity.
Solution Approach 2:
The system implements efficient feedback mechanisms that provide real-time or near-real-time updates on search rank score changes resulting from user adjustments. This feedback loop enables interactive operation without excessive processing delays by optimizing the calculation and delivery of results.
Data Source
AI summary
A system and method to improve online visibility of a business entity operating one or more processors to develop a search rank score. A plurality of categories associated with the search rank score is selected, a vertical business segment associated with the business entity is determined, and a plurality of weights is selected in accordance with the vertical business segment. Each of the plurality of weights is associated with a corresponding one of the plurality of categories. In addition, a plurality of sub-scores is developed, wherein each of the plurality of sub-scores is associated with a corresponding one of the plurality of categories. At least one of the plurality of sub-scores is developed by retrieving information regarding the business entity from a third-party server and evaluating the retrieved information. The plurality of sub-scores are combined in accordance with the plurality of weights to develop the search rank score.