AEO/GEO Expert needed to film work in steps

Looking for AEO/GEO audit and optimization of a website and social media and for it to be filmed to be used to train others. You must be able to clearly articulate actions in 6 steps, approximately 45-60 minutes each, with either written and/or clear verbal instruction so learners can do the same thing to any other website/online presence. Must include but not limited to below: A. Full SEO/AEO/GEO Audit B. Complete steps for website: Step 1: Open the Technical Doors to AI Crawlers: Audit your ⁠robots.txt⁠ file: Ensure you are not accidentally blocking the major AI bots. Open access explicitly to:  ⁠GPTBot⁠ (ChatGPT) ⁠Google-Extended⁠ (Gemini) ⁠ClaudeBot⁠ or ⁠Claude-Web⁠ (Claude) ⁠PerplexityBot⁠ (Perplexity) Create an ⁠llms.txt⁠ file: Place a markdown-down file. Use this file to provide a clean, high-level summary of your website's purpose, key pages, and core offerings so AI scrapers can understand your site instantly. Deliver clean HTML: Avoid burying your core information inside complex, client-side JavaScript. Ensure your primary text, product specs, and answers are fully rendered in the raw HTML DOM so text-based scrapers can grab them easily.  Step 2: Restructure Content for "Bottom Line Up Front" (BLUF) LLMs parse pages looking for immediate answers to synthesize. If your value proposition or answer is buried under paragraphs of introductory fluff, the bot will move on.  Lead with a TL;DR or summary block: Start high-value pages with a concise, 1 to 2 sentence summary of the core insight or solution.  Write question-based headers: Use ⁠tags that mimic the exact natural-language questions users type into an AI prompt. Format one clear answer per paragraph: Keep paragraphs short (2 to 4 sentences). State the definitive answer immediately following the header, then use the rest of the paragraph to expand on it.  Rely heavily on tables and bullet points: When presenting numbers, comparisons, prices, or steps, use clean Markdown or HTML tables. LLMs favor highly structured data structures when generating comparative summaries for users.  Step 3: Optimize for the "GEO" Citation Ranking Boost Princeton University research into Generative Engine Optimization (GEO) demonstrates that specific writing adjustments can increase a website's visibility in AI search responses by 30% to 40%.  Incorporate precise statistics: Include exact percentages, numbers, and data points within your content. Verifiable data signals authority to an LLM.  Cite authoritative secondary sources: Link out to recognized industry studies, academic research, or primary data sources. Backing up your claims makes your text more trustworthy during the model's evaluation phase.  Include expert quotations: Weave in direct quotes from verified industry professionals with clear attribution.  Integrate exact technical terminology: Use precise domain-specific language rather than broad, generic descriptions. AI models rely on exact terminology to map out conceptual relationships accurately. Step 4: Inject Robust JSON-LD Schema Markup Structured data acts as a direct, machine-readable translation layer for LLMs, removing any ambiguity about who you are and what you do.  Deploy Organization and Person schema: Clearly define your brand, official names, headquarters location, and key leadership team members.  Implement FAQPage schema: Mark up your question-and-answer sections so search engines utilizing AI features can instantly extract your answers into conversational interfaces.  Use Product and Offer schema: Include explicit attributes, current pricing, and real-time availability for products or services to keep real-time shopping agents accurate. Validate the code: Test your implementation using structured data testing tools to ensure there are no formatting errors or missing required fields.  Step 5: Build a Distinct Off-Page Entity Footprint When answering brand recommendations or comparison queries, LLMs look for a web-wide consensus. They cross-reference your site against third-party platforms to form an unbiased opinion. Maintain third-party directory profiles: Keep consistent, accurate organizational details on foundational databases like Crunchbase, LinkedIn, G2, Trustpilot, and Yelp.  Cultivate positive brand sentiment: Actively manage user reviews. When an LLM evaluates options, it analyzes user sentiment across the web to decide which companies to recommend.  Earn mentions in authoritative media: Focus on digital PR to secure placements and citations in reputable news publications and industry blogs. These high-authority backlink profiles serve as critical trust anchors for an LLM's knowledge graph.  Participate in community discussions: Ensure your brand is naturally discussed in community spaces like Reddit, Quora, and niche forums, as these platforms are heavily weighted by modern conversational engines looking for genuine human recommendations.  Step 6: Benchmark and Monitor Your Visibility AI optimization requires continuous tracking to see where your brand is successfully appearing and where gaps remain.  Establish a baseline metric: Choose 20 to 50 conversational prompts that your target audience would ask an AI assistant.  Test platforms manually or systematically: Query ChatGPT, Gemini, and Claude regularly with these prompts to evaluate your brand's "Share of Model" visibility.  Track citations and sentiment: Document whether your company is explicitly named, if your website is listed as a source link, and whether the overall tone of the AI response is accurate and positive. Update stale content quarterly to maintain freshness. C. Complete social media and web presence steps. D. Complete rest of previously created list of 50 tasks to increase AEO/GEO relevancy: Technical & Crawl Readiness 1. Deploy an ⁠llms.txt⁠ file: Create a clean, markdown-formatted ⁠/llms.txt⁠ file at your root directory to give AI models a high-level summary of your site structure.  2. Grant explicit bot access: Ensure your ⁠robots.txt⁠ file allows access to primary AI crawlers like GPTBot, Google-Extended, ClaudeBot, and PerplexityBot. 3. Optimize crawl budget: Keep your XML sitemap highly accurate and strictly limited to high-value, indexable pages.  4. Implement canonicalization: Maintain one clear canonical URL per piece of content to eliminate citation ambiguity for the LLM.  5. Clean up your HTML structure: Use clean, predictable semantic HTML tags so parsing algorithms can extract text without getting tangled in messy code.  6. Resolve redirect chains: Ensure internal links point directly to final destinations, minimizing the computational effort needed for a bot to follow your links.  7. Improve page loading speed: Optimize your backend infrastructure to pass Core Web Vitals, because fast-loading text is grabbed more efficiently by real-time scrapers.  8. Secure your domain: Use HTTPS protocols consistently, as modern AI engines prioritize secure links when compiling citations.  9. Audit for broken links: Fix 404 errors regularly to prevent crawlers from hitting dead ends during deep site evaluations.  10. Leverage a headless or flat architecture: Keep your text content highly accessible in the DOM rather than burying it inside complex client-side JavaScript. Content Structure & Extractability 11. Lead with a clear summary: Place a TL;DR summary or a direct answer at the top of long pages to serve as an instant, extractable snippet.  12. Design modular, chunkable sections: Organize content into self-contained blocks focused on a single specific subtopic.  13. Write question-shaped subheadings: Use clear H2 and H3 tags formatted as real questions that matching user prompts would look like.  14. Ensure contextual independence: Avoid using phrases such as "as mentioned above," because LLMs frequently analyze individual text fragments out of order. 15. Use data tables for facts: Present statistics, pricing, and specs in clean markdown or HTML tables to give the machine structural clarity.  16. Build clear lists: Use bullet points and numbered lists to help models identify sequential steps or grouped concepts quickly.  17. Keep paragraphs short: Restrict paragraphs to short text blocks to reduce the cognitive load for human readers and processing systems alike.  18. Keep sentences concise: Target a sentence length of 15 to 20 words to make language clear and easy to parse.  19. Define terms early: Provide plain-language definitions within the first 100 words of an introductory section.  20. Add descriptive alt text to data imagery: Include explicit descriptions for charts, graphs, and process diagrams in the image alt attributes.  Semantic Depth & Entity Clarity 21. Mention your brand alongside claims: Tie your company or product name directly to specific insights in the body text so the relationship is clear when the text fragment is pulled.  22. Maintain entity consistency: Use identical spelling and formatting for your brand, founders, and core product lines across every page. 23. Incorporate relevant synonyms: Mention industry standard variations and common aliases for your services near the primary keywords.  24. Map out topical clusters: Group related pages together using a logical internal linking web to showcase complete mastery over a subject.  25. Link out to primary sources: Connect your claims to high-authority ⁠.gov⁠, ⁠.edu⁠, or recognized research institutions to establish your credibility. 26. Include precise technical terminology: Use the exact technical terms relevant to your domain to signal deep expertise to the engine.  27. Offer multi-perspective coverage: Present balanced viewpoints or pros-and-cons lists when discussing complex industry topics.  28. Build self-comparison matrices: Publish honest, clear tables comparing your brand directly with alternative options on the market.  29. Answer the follow-up questions: Anticipate what a user will ask next and address those subsequent layers directly within the same page architecture.  30. Avoid vague fluff words: Strip out empty corporate speak and hyperbolic marketing claims that add text weight without adding concrete information.  Schema & Structured Metadata 31. Implement Organization schema: Use comprehensive JSON-LD to outline your brand name, official logo, official address, and social links.  32. Deploy Product and Offer schema: Include exact pricing, current availability, and product attributes for e-commerce or software systems.  33. Utilize FAQPage schema: Mark up your question-and-answer sections to make them perfectly readable for immediate answer engine placement.  34. Use TechArticle schema: Apply specialized technical schema to whitepapers and deep-dive documentation to attract research-focused engines like Perplexity.  35. Add Author and Publisher schema: Explicitly attribute your content to real people with verified backgrounds to fulfill credibility requirements.  36. Maintain accurate date stamps: Include clear "datePublished" and "dateModified" metadata to prove the freshness of your data.  37. Leverage BreadcrumbList schema: Clearly define your site's hierarchy using breadcrumb structured data. 38. Eliminate validation errors: Run your structured data regularly through schema validation tools to ensure there are no missing required fields.  39. Map out local business attributes: Fill out local business schema completely if you operate a brick-and-mortar storefront. 40. Keep schema perfectly aligned with on-page text: Ensure that the data hidden in your code matches what a user actually sees on the screen. Off-Page Authority & Ecosystem Footprint 41. Monitor your "Share of Model": Regularly test relevant prompts across top tools to track how often your brand is mentioned or cited.  42. Secure listings in primary directories: Maintain updated and accurate company listings on high-profile platforms like Crunchbase, LinkedIn, and Yelp.  43. Pitch for authoritative media coverage: Earn backlinks and editorial mentions from reputable news sites, because LLM training sets rely heavily on major media databases.  44. Encourage genuine user reviews: Cultivate positive ratings on third-party sites, as sentiment across review platforms directly shapes AI sentiment evaluations.  45. Publish original, citable research: Produce unique data sets and surveys that other creators will link to, turning your site into an authoritative root source.  46. Engage in community spaces: Build a presence on platforms like GitHub, Reddit, or specialized forums where AI crawlers frequently sample conversational context.  47. Optimize executive profiles: Ensure your leadership team has clear, consistent professional profiles across the web to reinforce organizational credibility. 48. Keep Wikipedia and Wikidata updated: If your company is notable enough, ensure your public data records are accurate, as these networks form the backbone of major knowledge graphs. 49. Refresh your old content: Keep statistics updated within a rolling 12-month window to maintain authority in current search contexts.  50. Analyze referral traffic sources: Track visitors coming directly from AI platforms inside your analytics dashboards to find out which pages are performing best. E. Must have at least 3 excellent refer-able reviews of similar work. Must have excellent quality screen filming capabilities and English.