Home Optimization Tools
🔧

Optimization Tools

Schema optimizer, LLM readiness audit, and action center to improve your AI visibility.
By Hello Airankia
• 3 articles

Using the AI Schema Creator

Using the AI Schema Creator Schema markup is the #1 technical SEO factor for AI visibility, influencing 19.7% of ranking signals. AI Rankia's Schema Creator generates LLM-optimized structured data that you can copy-paste directly into your pages. Why schema matters for AI search AI models don't read your website like a human. They rely on structured data to understand what your page is about. Schema markup (Schema.org) tells AI engines: - What type of content is on the page (product, article, FAQ, person) - Key attributes (price, rating, author, date, features) - Relationships between entities Pages with proper schema are significantly more likely to be cited by AI models and appear in Google AI Overviews. How to use the Schema Creator 1. Go to GEO Tools → AI Schema Creator in the sidebar 2. Enter the URL of the page you want to generate schema for 3. Select the schema type: Product, Blog/Article, Author, FAQ, or LLM-optimized 4. AI Rankia analyzes your page content and generates complete JSON-LD schema 5. Copy the output and paste it into your page's HTML <head> section Schema types available | Type | Best for | What it includes | |------|----------|------------------| | Product Schema | E-commerce, SaaS product pages | Name, description, price, rating, availability, brand, features | | Blog/Article Schema | Blog posts, content pages | Headline, author, datePublished, dateModified, description, images | | Author Schema | Team pages, about pages | Person name, credentials, job title, social profiles (E-E-A-T) | | FAQ Schema | FAQ pages | Question/Answer pairs for Google Rich Results | | LLM-Optimized | Any page | Enhanced schema with extra signals for LLM comprehension | Product Schema is critical for AI Shopping results in ChatGPT, Perplexity, and Google AI Mode. If you sell products or services, start here. Author Schema establishes E-E-A-T (Experience, Expertise, Authoritativeness, Trust). AI models weigh author authority when deciding what to cite. Real example: what you get When you enter a URL, the Schema Creator returns ready-to-use JSON-LD like: <script type="application/ld+json"> { "@context": "https://schema.org", "@type": "SoftwareApplication", "name": "AI Rankia", "applicationCategory": "BusinessApplication", "offers": { "@type": "Offer", "price": "29", "priceCurrency": "USD" }, "aggregateRating": { ... } } </script> Copy this entire block into your page's <head> section. After generating schema 1. Copy the JSON-LD code from the output 2. Paste it inside your page's <head> HTML 3. Validate at Google's Rich Results Test 4. Re-run your monitored prompts after 2-3 weeks to check if citation rates improve Credit cost 30 credits per page. This generates production-ready markup you can implement immediately. Start with your most important pages — homepage, top product pages, and highest-traffic blog posts. For context: 30 credits = monitoring 6 prompts across 5 models for one week. The schema you generate is permanent and improves visibility across every AI model.

Last updated on Mar 19, 2026

LLM Readiness Audit

LLM Readiness Audit 67% of websites block AI crawlers without realizing it. The LLM Readiness Audit checks 12 technical factors on your site that affect whether AI models can access, understand, and cite your content. How to run an audit 1. Go to GEO Tools → LLM Readiness Audit in the sidebar 2. Enter your website URL 3. AI Rankia runs 12 automated checks against your site 4. You get a pass/fail scorecard with specific recommendations for each issue What the audit checks The audit evaluates your site across these areas: Crawl access: - Is your robots.txt blocking AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended)? - Do you have an llms.txt file that helps LLMs understand your site structure? - Are important pages accessible without JavaScript rendering? Content structure: - Does your content use clear heading hierarchy (H1, H2, H3)? - Are pages structured with semantic HTML? - Is content comprehensive enough for AI models to cite (word count, topic coverage)? Schema and metadata: - Do you have Schema.org structured data? - Are Open Graph and meta description tags properly set? - Is your sitemap up to date and accessible? Technical performance: - Is your site fast enough for AI crawlers? - Are there broken links or redirect chains? - Is HTTPS properly configured? Reading the results Each check shows: - Pass (green) — this factor is correctly configured - Warning (yellow) — partially configured or could be improved - Fail (red) — this is actively hurting your AI visibility and should be fixed The audit prioritizes issues by impact, so fix red items first. Common issues found The most frequent problems are: 1. Robots.txt blocking AI bots — many sites still have rules blocking GPTBot or ClaudeBot from their old SEO configurations 2. Missing Schema markup — the single highest-impact fix for most sites 3. No llms.txt file — a simple text file that helps AI models understand your site (similar to robots.txt but for LLMs) 4. Thin content — pages with too little text for AI models to extract useful information Credit cost The LLM Readiness Audit costs 3 credits — one of the cheapest tools. Run it first, fix the issues found, then invest in the more expensive optimization tools.

Last updated on Mar 19, 2026

Action Center

Action Center The Action Center is where AI Rankia turns data into a to-do list. Instead of interpreting dashboards yourself, the Action Center generates prioritized tasks based on your monitoring data. How it works 1. Go to Action Center → Tasks in the sidebar 2. AI Rankia analyzes your prompt monitoring results, brand mentions, citation gaps, and audit findings 3. It generates specific, actionable tasks ranked by impact, effort, and urgency 4. Each task is assigned a quadrant: Quick Win, Major Project, Fill In, or Thankless Real task examples from the platform Here are actual tasks AI Rankia generates for users: | Task | Category | Quadrant | Impact | Effort | |------|----------|----------|--------|--------| | Check if brand domain is crawlable by AI bots | Technical | Quick Win | 5/5 | 1/5 | | Analyze competitor's AI citation strategy — #1 with 3 mentions | Digital PR | Quick Win | 4/5 | 1/5 | | Add Organization schema with sameAs links to strengthen entity signals | Schema | Fill In | 3/5 | 2/5 | | Monitor additional prompts covering brand's actual business vertical | Content | Fill In | 3/5 | 2/5 | | Create content hub targeting competitor keyword gaps | Content | Major Project | 4/5 | 4/5 | Each task includes a detailed description explaining exactly what to do and why. Tasks marked Quick Win (high impact, low effort) should be your first priority. Task categories Tasks fall into these categories: - Technical — robots.txt fixes, schema markup, crawl access issues - Content — new pages to create, existing content to strengthen - Schema — structured data additions and improvements - Digital PR — outreach targets, citation opportunities Using the Action Center effectively The Action Center works best when you have active monitoring data. Recommended workflow: 1. Set up prompt monitoring with 5-10 prompts (Phase 1) 2. Run an LLM Readiness Audit — 3 credits 3. Enrich your top prompts with Query Fan-Out — 5 credits each 4. Check Mentions Opportunities — 50 credits 5. Open the Action Center — it now has rich data to generate meaningful tasks Credit cost 1 credit per action plan generation. One of the cheapest tools — run it after every monitoring cycle for fresh recommendations.

Last updated on Mar 19, 2026