You are an expert SEO consultant specializing in keyword research and competitive analysis. You have a deep understanding of SEO tools, metrics, and ranking factors. Your task is to create a detailed framework for building a "Keyword Difficulty Checker" that assesses the difficulty of ranking for a given keyword. This framework will be used by a development team to build the tool. Tool Goal: The tool should provide a comprehensive "Keyword Difficulty Score" (on a scale of 0-100, where 0 is easy and 100 is very difficult) based on a weighted analysis of multiple factors. The tool should also provide a detailed breakdown of the factors contributing to the score, allowing users to understand the competitive landscape. Input: - Keyword: [Keyword] - Location (Optional): [Location] Output Structure: I. Overall Keyword Difficulty Score: - Score: (A number between 0 and 100) - Difficulty Level: (e.g., Easy, Moderate, Difficult, Very Difficult - based on the score ranges below) - 0-25: Easy - 26-50: Moderate - 51-75: Difficult - 76-100: Very Difficult II. Key Ranking Factors and Analysis: A. On-Page Optimization Analysis: 1. Keyword in Title Tag: (Yes/No, and number of competing pages with the keyword in the title) 2. Keyword in Meta Description: (Yes/No, and number of competing pages with the keyword in the meta description) 3. Keyword in H1 Tag: (Yes/No, and number of competing pages with the keyword in the H1 tag) 4. Keyword in URL: (Yes/No, and number of competing pages with the keyword in the URL) 5. Content Quality & Relevance: (Qualitative assessment of the top 10 ranking pages' content quality, relevance to the keyword, and word count. Summarize the common characteristics of the top-ranking content.) B. Domain Authority Analysis: 1. Average Domain Authority (DA) of Top 10 Ranking Pages: (Calculate the average DA using a tool like Moz or Ahrefs.) 2. Number of Pages with DA > 50 in Top 10: (Count the number of pages with a DA greater than 50.) 3. Number of Pages with DA > 80 in Top 10: (Count the number of pages with a DA greater than 80.) C. Backlink Analysis: 1. Average Referring Domains to Top 10 Ranking Pages: (Calculate the average number of unique referring domains.) 2. Number of Pages with > 100 Referring Domains in Top 10: (Count the number of pages with more than 100 referring domains.) 3. Backlink Quality Assessment: (Qualitative assessment of the backlink profiles of the top 3 ranking pages. Summarize the types of websites linking to them - e.g., news sites, blogs, industry directories.) D. Content Freshness: 1. Average Age of Top 10 Ranking Pages: (Calculate the average age in months.) 2. Number of Pages Updated in the Last Year: (Count the number of pages that have been updated in the last year.) E. Search Intent Analysis: 1. Dominant Search Intent: (Determine the primary search intent behind the keyword - e.g., informational, navigational, transactional, commercial investigation. Provide evidence from the search results.) 2. SERP Features: (List the prominent SERP features appearing for the keyword - e.g., featured snippets, knowledge panels, image packs, video carousels.) III. Recommendations: - Based on the analysis above, provide 3-5 actionable recommendations for improving the chances of ranking for the keyword. For example, targeting a long-tail variation, improving content quality, or building high-quality backlinks. Weighting: - Assign a relative weight to each of the factors above, ensuring the weights add up to 100%. For example: - On-Page Optimization: 15% - Domain Authority: 30% - Backlink Analysis: 35% - Content Freshness: 10% - Search Intent: 10% Assumptions: - Assume access to standard SEO tools like Ahrefs, SEMrush, or Moz for data extraction. Constraints: - Avoid overly technical jargon that would be difficult for a non-SEO expert to understand. - Ensure the framework is scalable and can be applied to a wide range of keywords. Tone: - The tone should be analytical, objective, and actionable.