How to Run an LLM SEO Audit: Process and Priorities

AI search is changing how your audience finds you. Google SEO measures where you rank on results pages. LLM SEO measures whether your brand shows up when users ask AI questions. An audit reveals this gap.

Most guidance is locked behind agency walls or tool signup forms. This guide walks you through a self-service audit. Learn how to set a baseline, check your standing across ChatGPT, Gemini, and Perplexity, find out what signals LLMs care about, and pick which fixes to do first.

At a Glance

A baseline audit means testing 15 to 20 prompts across three platforms and writing down if you appear, where you appear, how you're framed, and what other brands show up. Three core audit areas matter: tech access which includes robots.txt rules, JavaScript rendering, and schema markup; content signals which include direct answers, author info, and fresh content; and what other brands are doing. Use a three-step fix plan: tech fixes first, content fixes second, brand building third. Re-audit every three months, after big content updates, and after model changes.

What Does an LLM SEO Audit Actually Evaluate?

Google audits check if your pages can be found, read, and ranked well. An LLM SEO audit asks a new question: do AI systems mention your brand when users ask questions about your work?

AI visibility is not just yes or no on a results page anymore. It comes in shades. Does your brand show up at all? Where in the answer? How does the AI frame your brand? What other brands appear with you?

Your audit should track four things for each test:

• Mention present: Did the AI name your brand?
• Where it appears: First choice or one of many?
• How it's framed: Good, neutral, or with caveats?
• Other brands named: What competitors appear?

This baseline data helps you track your progress later.

How Do You Measure Your Brand's Current Visibility in AI Search?

Start with a baseline audit that takes 4 to 6 hours and costs nothing.

Pick 15 to 20 test prompts that sound like real user questions. Match your main services to how people ask AI:

• "What is marketing automation and how does it work?"
• "How do I pick a marketing automation tool?"
• "What is the difference between marketing automation and email?"

People ask AI in plain language so your prompts should sound natural.

Test on all three main platforms for the full picture. Run each prompt on ChatGPT, Gemini, and Perplexity because they train on different data and have different habits. You need all three to see the real story.

Write down what you find in a simple way. For each prompt on each platform, note:

• Prompt: [what you typed]
• Platform: ChatGPT / Gemini / Perplexity
• Mention present: Yes / No
• Where: First choice / One of several / Not there
• Tone: Positive / Neutral / With limits
• Other brands: [list them]

After 15 to 20 prompts on three platforms, you will have 45 to 60 data points. Count how many times you appear. Do the math on your baseline score. Note which competitors show up most often. Many brands shock themselves by how low this number is, even when they rank high on Google.

What Content and Technical Signals Do LLMs Check?

LLMs learn from old web text and pick which sources to trust in answers.

LLMs favor specific content choices:

• Start with a direct answer to the main question because burying your answer means LLMs skip it
• Use real stats or studies to back claims because this shows you are trustworthy
• Put author info and links right on the page so AI knows a real expert wrote this
• Add dates like "Last updated: June 2026" to posts that don't go out of date

Tech access matters because AI has to read your pages:

• Check your robots.txt file and make sure it lets GPTBot, ClaudeBot, and PerplexityBot in
• Test key pages without Java to confirm they show up right and complete
• Add FAQ schema to Q&A sections and Company schema to your main site

See what your rivals do to find gaps:

Test the same prompts with competitor names added. Where they show up often, you have a gap. Write similar content to match them.

How Do You Prioritize Fixes After an Audit?

Use a simple three-step plan that sorts work by what's urgent and what helps most.

Step 1: Tech access fixes take days to weeks and open the door. Fix robots.txt to allow AI bots in. Rebuild pages that need Java to show properly. Add missing schema tags. These changes let AI systems read your site at all.

Step 2: Content fixes take weeks to months and boost your chances. Rewrite top paragraphs to lead with direct answers. Add stats and study links. Build out FAQ sections with clear question pairs. Write author bios. Add "Last updated" dates. These changes raise the odds that AI will use your content.

Step 3: Brand building takes months to years and builds long-term trust. Get mentions from big name sites. Build links from sites in your field. Write early posts on new topics. These changes build your reputation over time.

Fix your most vital pages first like main service pages. Fix tech blocks before you polish secondary content.

Frequently Asked Questions

How often should you re-audit your baseline?

Re-audit after you publish big new posts or do major rewrites. Re-audit when AI tools roll out new models, which happens every three months or so. At minimum, re-audit every three months because models shift fast and your old data gets stale.

Do you need to buy a tool to run an audit by hand?

You can start by hand using free access to ChatGPT, Gemini, and Perplexity. If you want to track 50 plus prompts over time, a tool like SEO Site Checkup's LLM tracker saves hours. But run your first hand audit this week with free tools.

What do you do if a rival shows up in every answer?

You have a content gap or a trust gap to fix. See what topics they cover that you don't. Look at the pages AI picks from them and note what makes them work: length, structure, dates, author bios. Build the same kind of content and re-audit in 60 to 90 days.

Should you optimize the same way for all three platforms?

Focus on where your users search most based on your audit. But know that basics like depth, trust, and tech access work on all three so your work spreads across them all naturally.

What if you rank great in Google but not in AI?

This happens a lot now because Google and AI don't pick content the same way. You may need to fix things just for AI. Run this audit to see what gaps are unique to AI search.

How do you know your audit results are real?

Test 15 to 20 prompts across your main service areas. If every test shows the same gap, that's real. If results bounce around, test 25 to 30 prompts. Variety often means you are strong on some topics and weak on others and need to focus.

Can your own team do this audit?

Yes, your team can run the audit and do most fixes without outside help. An agency helps more if you want ongoing track, large scale checks, or help with priorities. But the first audit and most fixes you can do yourself with clear steps.

How long before you see results after you make fixes?

Tech fixes show results in days. Content rewrites take 2 to 4 weeks to kick in. Link building takes months. Plan for 30 to 60 days before your next audit shows real change.

What Are Your Next Steps in LLM SEO Strategy?

An audit is your first step toward AI search wins. After you find your gaps, learn more about how LLM SEO works in practice to grasp the rules that drive AI picks. Then read about what LLM SEO means for your brand to tie this into your larger plan.

Brands that win in AI search start with audits, learn their score, and build step by step plans. Start with this free audit and build your three step roadmap from what you learn.