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OpenAI Optimization

ChatGPT SEO: Get Your Brand Recommended by ChatGPT

With over 100M weekly users, ChatGPT is now a primary search channel. Learn how to optimize your brand to appear in ChatGPT responses and capture this massive audience.

What is ChatGPT SEO?

ChatGPT SEO is the practice of optimizing your brand and content to be recommended, mentioned, and accurately represented when users ask ChatGPT questions related to your industry or products.

As ChatGPT becomes a go-to source for recommendations, reviews, and information, brands that master ChatGPT SEO will capture significant mindshare and traffic.

  • Appear when users ask 'What is the best...'
  • Get cited as a trusted source in responses
  • Ensure accurate brand representation
  • Outrank competitors in AI recommendations

ChatGPT Query Examples

What is the best CRM software for small business?
Can you recommend a project management tool?
What are the top brands in [your industry]?
Compare [your product] vs [competitor]
Is [your brand] good for [use case]?

ChatGPT SEO Best Practices

Strategies to improve your brand's visibility and accuracy in ChatGPT responses.

Create Authoritative Content

ChatGPT sources from indexed web content. Create comprehensive, well-cited articles that establish your expertise and brand authority.

Build Brand Mentions

Earn mentions on authoritative sites, reviews, and comparison articles that ChatGPT is likely to reference.

Optimize for Questions

Structure content around the questions users ask ChatGPT about your industry. FAQs and how-to guides work well.

Ensure Accuracy

Keep brand information consistent across all platforms so ChatGPT has accurate data to reference.

ChatGPT Optimization

Track Your ChatGPT Performance with Pranas

ChatGPT AI Score & Mention Rate

See exactly how often and how prominently ChatGPT mentions your brand in relevant queries.

Ranking Analysis

Track your position when ChatGPT lists or compares brands in your space.

Perception Tracking

Monitor how ChatGPT describes your brand attributes and sentiment.

Source Attribution

Discover which sources ChatGPT cites when mentioning your brand.

Gap Analysis

Find where ChatGPT's perception differs from your intended positioning.

Content Recommendations

Get AI-generated content suggestions to improve your ChatGPT presence.

Which crawler feeds which AI answer

Optimising for AI search starts with knowing which crawler each assistant depends on. Block the wrong user agent in robots.txt and you disappear from that surface entirely.

AI surfaces, the crawlers they depend on, and the practical implication for site owners.
AI surfaceUser agents to allowWhat the crawler doesPractical implication
ChatGPTGPTBot, OAI-SearchBot, ChatGPT-UserModel training, search index, and live in-chat retrievalBlocking the search agent removes you from ChatGPT answers even if training access is allowed
Gemini and Google AI OverviewsGoogle-Extended, GoogleOtherAI training crawl on top of the standard search indexStandard search indexing still applies; the AI opt-out is a separate control
PerplexityPerplexityBot, Perplexity-UserIndex crawl plus live retrieval at answer timeLive retrieval means content changes can show up quickly
ClaudeClaudeBot, Claude-WebTraining crawl and live web retrievalBoth agents need to be allowed for full coverage
Copilot and other assistantsbingbot, plus assistant-specific agentsRetrieval from a general web indexVerify the site and submit a sitemap so the index stays current

The Pranas AI Search Audit reports the allowed or blocked state of these agents from your live robots.txt.

robots.txt checklist

  • Remove blanket Disallow rules copied from a template.
  • Decide training access and retrieval access separately.
  • Confirm no path prefix hides your product or docs pages.
  • Reference your sitemap from robots.txt.

After you change access

  • Flush any CDN cache so crawlers see the new file.
  • Re-run the audit to confirm every agent reads as allowed.
  • Re-run the same AI Scan prompt set to measure the effect.
  • Expect retrieval-based surfaces to update before training-based ones.