Audit your brand visibility on LLMs, step by step

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TL;DR:

  • Test your brand across 5 LLMs with a fixed prompt set. Capture answers and sources.
  • Check citations and facts. Fix missing or wrong data at the source.
  • Strengthen entity signals with Organization schema, sameAs, and clean About pages.
  • Claim or improve profiles that LLMs read, like Wikidata and trusted directories.
  • Monitor AI Overviews and Bing. Track changes monthly and after major releases.

Large language models now answer brand questions at scale. Users ask for the best tools, quick bios, and price checks. If models miss you, you lose reach. If they cite weak sources, trust slips.

This guide shows how to test, score, and improve your brand visibility on models like ChatGPT, Claude, Gemini, Copilot, and Perplexity. It works for B2B, B2C, and nonprofits.

All steps are current as of September 29, 2025.

What “visibility on LLMs” means

Visibility has three layers.

  1. Recall. The model mentions your brand for the right queries.
  2. Accuracy. Facts match reality, like pricing, founders, or HQ.
  3. Attribution. The model cites high quality pages. These drive clicks and trust.

Your audit checks all three.

The quick start plan

You will run a fixed set of prompts on five models, capture outputs, grade them, then fix issues at the source.

Tools you need

  • A shared spreadsheet or doc.
  • Accounts for ChatGPT, Claude, Gemini, Microsoft Copilot, and Perplexity.
  • Access to Google Search Console and Bing Webmaster Tools for your site.

Step 1: Build your prompt set

Use the same prompts for each model to compare results. Copy these, then add category specific ones.

Brand basics

  • What is {Brand}?
  • Who founded {Brand}? When and where?
  • Where is {Brand} headquartered?
  • What is {Brand} pricing?
  • Who are {Brand} competitors?

Commercial

  • Best {category} tools for {use case}.
  • {Brand} vs {Rival}.
  • Alternatives to {Brand}.

Step 2: Test across top LLMs

Run each prompt on:

  • ChatGPT with browsing.
  • Claude with web access.
  • Google Gemini and check how AI Overviews present your pages for the same queries. Google explains how AI features work in its Search docs. Use that lens while you review sources.
  • Microsoft Copilot which relies on Bing index and structured data. Check your site in Bing Webmaster Tools.
  • Perplexity which always shows citations. Note which sources it uses and if they are current.

Export or paste the full answers and the link list for each prompt into your sheet.

Step 3: Score recall, accuracy, and attribution

Create three columns per prompt:

  • Recall score, 0 to 2
    0 = not mentioned, 1 = named but low detail, 2 = well covered
  • Accuracy score, 0 to 2
    0 = wrong, 1 = mixed, 2 = correct
  • Attribution score, 0 to 2
    0 = no citations or poor sites, 1 = some OK, 2 = strong sources you control or endorse

Add notes for wrong facts, missing products, and low trust citations.

Step 4: Find and fix source problems

Models pull from what they can crawl and what search engines understand.

4.1 Strengthen your entity signals

Add or improve Organization structured data on your homepage. Include name, logo, description, contact, founding date, address, and sameAs links to your official profiles. Google and Bing use this data to understand and disambiguate brands.

Checklist, Organization JSON-LD minimums:

  • @type: Organization or LocalBusiness
  • name, url, logo
  • description in plain language
  • sameAs: sitewide official profiles like LinkedIn, X, GitHub, YouTube, App stores, Crunchbase
  • foundingDate, founder, address if relevant
  • contactPoint for sales and support

Also keep an About page with the same details in readable text.

4.2 Claim or create key knowledge entries

Many answers come from structured hubs.

  • Wikidata. Create or improve your item with solid references if you meet notability. Keep labels, aliases, headquarters location, and official site current.
  • Trusted directories. For software, enrich G2, Capterra, and app marketplaces. For local brands, use local business listings with consistent NAP.
  • Press coverage. Secure a few independent articles that state what you do, who leads it, and where you are based.

Guides on notability and setup can help your team plan edits and avoid removals.

4.3 Tighten Bing signals

Copilot depends on Bing’s index. Verify your site, submit sitemaps, fix crawl errors, and validate markup in Bing Webmaster Tools.

4.4 Watch Google AI Overviews

Google’s AI Overviews can feature your content, or push it below the fold. Keep guides fresh, add clear answers near the top, and structure your pages well. Reviews note that citations matter for inclusion. Use this when updating pages you want cited.

Step 5: Tune for accurate facts

List every wrong fact you saw in your audit. For each one, ask:

  • Do we have a clear, crawlable source on our site?
  • Is a trusted third party saying the old thing?
  • Does our schema match our page text?
  • Is the sitemap updated and linked in robots.txt?

Fix pages first, then update schema, then request reindexing in Search Console and Bing Webmaster Tools.

Step 6: Improve the citations you earn

You want models to cite sources you control or endorse.

  • Publish a one page factsheet. Name, description, pricing tiers, integrations, leadership, HQ, and date formats that match your schema.
  • Write solid comparison pages. “{Brand} vs {Rival}” with fair, sourced claims.
  • Refresh reviews page. Link to recent reviews on credible platforms.
  • Add FAQs that answer the exact prompts you tested.

Per model runs, track which of your pages get cited. Raise their quality until they become the default citation.

Step 7: Set and refine crawler controls

Decide which AI crawlers you allow for training, and which you only allow for real time answering. Policies and behaviors differ.

  • OpenAI crawlers. OpenAI lists its bots and how they honor robots.txt. Adjust your robots.txt if you want to allow or block.
  • Anthropic bots. Anthropic states its bots honor industry standard robots.txt directives. Use that to set allow or disallow rules.
  • Perplexity crawlers. Perplexity documents its bots and robots.txt tags. Independent reports have also alleged stealth crawling, which Cloudflare and other outlets have covered. Plan controls and monitoring with that in mind.

Step 8: Re run the audit and set a cadence

After fixes, re run your prompt set. Compare scores and citations.

Set a schedule:

  • Monthly checks for top 10 prompts.
  • Quarterly deep audit across all prompts and models.
  • After large model releases or site changes.

A compact audit template

AreaWhat to checkToolPass rule
RecallBrand appears in top 3 model answersPrompt set80 percent of prompts
AccuracyFacts match site and docsPrompt set + site95 percent correct
AttributionCites your site or trusted pagesPrompt set2 of 3 models cite you
SchemaOrganization JSON-LD validRich results testNo errors
Knowledge hubsWikidata complete and referencedWikidataItem exists and is current
BingSite verified, sitemap, no major errorsBing WMTAll green
Google AI featuresPages eligible, recent updatesGSC + manual checksTarget pages cited

Common mistakes to avoid

  • Only checking your brand name. Test generic and “alternatives” prompts too.
  • Outdated About and pricing pages.
  • Schema that does not match page copy.
  • Fragmented identities. Social links and app listings do not match the brand name or domain.
  • Blocking crawlers without a plan to still earn citations from trusted sites.

Why it matters

Models shape discovery. If they skip your brand, you lose pipeline. If they cite a third party that misstates your pricing, support complains. A light monthly audit keeps your brand present, accurate, and cited.

Appendix: where LLM answers come from

  • Search systems and structured data. Google explains that AI features use information from across the web and benefit from clean structured data. Bing also uses schema to understand pages.
  • Crawlers and policies. OpenAI, Anthropic, and Perplexity publish crawler details, while some reports highlight policy gaps or stealth crawling. Use both robots.txt and network rules.
  • Knowledge bases. Wikidata items help search engines connect your brand to the right facts and profiles.

Sources:

Perplexity Docs, Perplexity crawlers and robots.txt, https://docs.perplexity.ai/guides/bots, accessed September 29, 2025