Blog / LLM Optimization

I Rewrote One Sentence on My Landing Page. ChatGPT Started Recommending Me.

By Delulu Agency, Reddit GEO Specialists| March 10, 2026
I Rewrote One Sentence on My Landing Page. ChatGPT Started Recommending Me.
TL;DR
LLMs read your landing page differently than humans. They extract structured information, look for clear positioning statements, and struggle with marketing fluff. Optimizing for LLMs means being specific, structured, and quotable without sacrificing human conversion.

Your landing page exists for two audiences now.

The first is human visitors who need to understand what you do and why they should care. The second is AI systems crawling the web, building knowledge graphs, and deciding whether to recommend you.

Most landing pages fail the second audience completely. If your product is already invisible to ChatGPT, your landing page could be part of the problem.

How LLMs Read Landing Pages

LLM Content Extraction
The process by which AI systems parse web pages to extract structured information about products, services, and companies. LLMs look for clear statements, structured data, and consistent messaging across sources.

When an LLM encounters your landing page, it’s trying to answer:

  1. What exactly does this product do?
  2. Who is it for?
  3. How is it different from alternatives?
  4. What are the key features?
  5. What do users say about it?

Marketing-speak makes these questions hard to answer. Specificity makes them easy.

The Landing Page Audit

Before optimizing, audit your current page:

LLM Landing Page Audit
How to evaluate your page's LLM readability
Extract Your Claims
Read your landing page and list every specific claim it makes. “We help teams work better” is not specific. “Project management for engineering teams of 10-50 people” is specific. Count how many specific versus vague statements you have.
Test LLM Comprehension
Copy your landing page text. Paste it into ChatGPT. Ask: “Based on this text, what does this product do, who is it for, and what makes it different?” Evaluate the accuracy of the response.
Check Structured Data
View page source. Look for schema.org markup, semantic HTML, and meta tags. LLMs use these signals to understand page structure.
Compare to Competitors
Do the same audit for 2-3 competitors. Who has clearer positioning? Who has better structure? This shows where you stand.

Optimization Principles

1. Lead with Positioning

Your headline should answer “What is this?” clearly. Not cleverly. Clearly.

Before (vague):

“Transform How Your Team Works”

After (specific):

“Project Management for Engineering Teams. Ship Faster with Async Standups.”

LLMs can extract “project management for engineering teams” and match it to queries. They can’t do anything useful with “transform how your team works.”

2. State Your Use Case Explicitly

Somewhere above the fold, explicitly state who the product is for.

Example:

“Built for: Remote engineering teams of 10-50 people who need async communication without endless meetings.”

This explicit statement creates a matchable pattern. When someone asks ChatGPT for “async tools for remote engineering teams,” this page has a better chance of being relevant.

3. List Features Clearly

Feature lists should be scannable and specific.

Before:

  • Powerful reporting
  • Team collaboration
  • Seamless integrations

After:

  • Real-time dashboards with Slack alerts
  • Async standups that replace daily meetings
  • Two-click integration with GitHub and Jira

Specific features can be matched to specific queries. Generic features cannot.

4. Include Quotable Statements

LLMs cite text that’s clear and self-contained. Write sentences that could be quoted in an AI response.

Quotable:

“The only project management tool built specifically for async engineering teams.”

Not quotable:

“We’re passionate about helping teams collaborate more effectively through innovative solutions.”

The first can be directly cited. The second says nothing citable. For a deeper dive into writing content that LLMs can extract and recommend, see our guide on creating AI-friendly content.

5. Use Semantic HTML

Structure matters for AI comprehension:

This structure helps LLMs understand content hierarchy.

6. Add Schema Markup

Schema.org Markup
Structured data vocabulary that helps search engines and AI understand content. For SaaS products, relevant schema types include SoftwareApplication, Organization, and Review.

Add schema.org markup for:

LLMs trained on web data recognize and weight schema-marked content.

What to Avoid

Marketing Superlatives

“Best-in-class,” “world-leading,” “revolutionary” add nothing. LLMs ignore superlatives without evidence. Humans should too.

Vague Benefits

“Save time,” “improve efficiency,” “boost productivity” are meaningless without specifics. How much time? On what tasks?

Hidden Information

Don’t hide key information behind modals, tabs, or expandable sections. LLMs may not see collapsed content. Critical positioning should be visible by default.

Inconsistent Messaging

If your landing page says one thing and your About page says another, LLMs get confused. Consistent messaging across all pages reinforces your positioning.

Balancing LLM and Human Optimization

The good news: LLM-friendly pages are often better for humans too.

Clear positioning helps visitors self-select. Specific features help buyers evaluate. Quotable statements become memorable taglines. This alignment is exactly why GEO and SEO are complementary strategies, not competing ones.

The only tension is creative marketing copy. Clever wordplay that works for humans may confuse LLMs. When in doubt, prioritize clarity over cleverness.

Testing Your Optimization

After making changes:

  1. Test with ChatGPT/Claude: Ask them to describe your product based on your URL. Is the response accurate?

  2. Check Google’s cache: Google caches pages similarly to how LLMs see them. Ensure important content appears.

  3. Monitor recommendations: Over time, track whether you appear more frequently in AI responses for relevant queries.

Does LLM optimization hurt SEO?
No. LLM optimization and SEO overlap significantly. Clear structure, specific content, and semantic HTML help both. The main difference is LLM optimization prioritizes quotability over keyword density.
How often do LLMs crawl landing pages?
It varies. LLMs are trained periodically, but systems like Perplexity use real-time retrieval. Keep pages updated and assume some systems see current content.
Should I create separate pages for LLM optimization?
No. Optimize your primary pages. Duplicate content for LLMs creates inconsistency. Your main landing page should work for all audiences.
How important is landing page optimization versus Reddit presence?
Reddit presence is more important for getting recommended initially. Landing page optimization ensures accurate descriptions when you are recommended. Both matter. Read our Reddit marketing playbook for building that external presence, and learn how to track your AI mentions to measure whether your optimizations are working.
Key Takeaways
  • LLMs extract structured information and specific claims from landing pages
  • Clear positioning statements enable AI to match your product to queries
  • Specific features beat vague benefits for LLM comprehension
  • Write quotable sentences that can be directly cited in AI responses
  • Use semantic HTML and schema markup for structure
  • Avoid marketing superlatives and vague language
  • Test optimization by asking LLMs to describe your product

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