Perplexity is eating our lunch. How do you actually get cited there?

Perplexity IS different from ChatGPT. Here’s why you might be visible on one but not the other:

The Four Criteria Perplexity Uses:

1. Credibility - Publisher authority, expert authorship, verifiable references
2. Recency - Content freshness (weighted heavily)
3. Relevance - Direct answer match to query
4. Clarity - Structured, extractable content

Key Differences from ChatGPT:

Why you might be invisible on Perplexity:

1. Recency issue - When did you last update your content? Perplexity heavily favors recent updates.

2. Extraction difficulty - Your 10K word guides might be hard to extract specific answers from. Perplexity wants clear, quotable content.

3. Robots.txt - Is PerplexityBot allowed?

4. Answer clarity - Does your content have clear first-paragraph answers, or does it build to conclusions?

You can be great for ChatGPT but wrong for Perplexity. They need different optimization approaches.

Content structure matters differently for Perplexity.

What works for ChatGPT (training data model):

• Comprehensive coverage
• Detailed explanations
• Context building

What works for Perplexity (real-time extraction):

• Clear, quotable passages
• Direct answers in first sentences
• Standalone paragraphs that make sense out of context

The problem with long guides:

Your 10K word guides might be excellent, but Perplexity struggles to extract when:

• Key answers are buried mid-article
• Information requires surrounding context
• No clear “snippet” to pull

How to optimize for Perplexity:

1. Lead with answers - First sentence should directly answer the implied question

2. Create modular content - Each section should be understandable standalone

3. Add TL;DR sections - Summary boxes that Perplexity can extract

4. Use clear heading structure - Questions as H2s help extraction

Example restructure:

Before: “When considering X, there are many factors to examine. In this comprehensive guide, we’ll explore the various dimensions…”

After: “X typically costs $Y and takes Z time. Here’s exactly how it works and what you need to know before starting…”

Perplexity needs extractable answers, not comprehensive narratives.

Technical requirements for Perplexity (often overlooked):

1. Robots.txt - Critical

Add explicit allowance:

User-agent: PerplexityBot
Allow: /

Many sites accidentally block it through catch-all rules.

2. Server-side rendering

Perplexity’s crawler has limited JavaScript execution. If your content requires JS to render, Perplexity might not see it.

Test: Disable JavaScript in your browser and load your page. What you see is what Perplexity sees.

3. Page speed

Perplexity crawlers have timeout limits. Slow pages may not be fully indexed.

Target: Under 500ms server response time.

4. Schema markup

While Perplexity doesn’t require schema, it helps with extraction:

• FAQPage schema - Maps directly to Q&A extraction
• Article schema - Helps identify publication date
• HowTo schema - Perfect for step-by-step extraction

Quick diagnostic:

1. Check robots.txt for PerplexityBot rules
2. Test page with JS disabled
3. Check PageSpeed Insights for server response time
4. Validate schema with Google Rich Results Test

Fix technical issues before worrying about content optimization.

Reverse-engineer competitors who ARE getting Perplexity citations:

Analysis framework:

For each query where competitors appear and you don’t:

1. Check their content freshness

   • Publication date
   • Last updated date
   • Recency of statistics/examples

2. Analyze their structure

   • How quickly do they answer the question?
   • What’s in their first paragraph?
   • Do they have FAQ sections?

3. Compare technical setup

   • Page speed
   • Schema implementation
   • JavaScript dependency

4. Evaluate extractability

   • Can you quote their content easily?
   • Do they have standalone sentences that make sense?
   • Are there clear data points to cite?

What I usually find:

Smaller sites beating larger sites on Perplexity often have:

• More recent content
• Clearer answer structure
• Better extractability
• Faster pages

Domain authority matters less on Perplexity than on ChatGPT. Structure and freshness matter more.

FAQ format is Perplexity’s best friend.

Why FAQs work:

Perplexity’s extraction engine loves content that’s already in Q&A format. It maps directly to how users query.

Implementation:

1. Add FAQ sections to existing guides

Don’t create separate FAQ pages. Add FAQ sections to your comprehensive guides.

2. Use FAQ schema

{
  "@type": "FAQPage",
  "mainEntity": [{
    "@type": "Question",
    "name": "How much does X cost?",
    "acceptedAnswer": {
      "@type": "Answer",
      "text": "X typically costs $Y-$Z depending on..."
    }
  }]
}

3. Write answers in extractable format

Bad: “There are several factors that affect pricing…” Good: “X costs between $50-$200. The main factors are…”

Results I’ve seen:

Adding FAQ sections with schema to existing content increased Perplexity citations by 40% within 6 weeks for one client.

Your comprehensive content is valuable. FAQ sections make it extractable.

How to measure Perplexity visibility specifically:

Manual tracking:

Create a list of 20-30 queries relevant to your content. Test them weekly on Perplexity specifically.

Track:

• Are you cited? (Yes/No)
• Citation position (footnote number)
• Which page is cited?
• What text is extracted?

Automated tracking:

Tools like Am I Cited can track Perplexity citations specifically, separate from ChatGPT or other platforms.

Key metrics:

1. Citation frequency - How often you appear
2. Footnote position - Lower numbers = more prominent
3. Content coverage - Which of your pages get cited
4. Query coverage - What percentage of relevant queries cite you

Benchmarking:

Compare yourself to competitors on the same queries. If they’re cited in 60% of relevant queries and you’re at 20%, you have a clear gap to close.

Timeline:

Track for at least 4 weeks before and after changes. Perplexity updates faster than ChatGPT but still needs time to reflect content changes.

This thread explained why Perplexity and ChatGPT need different approaches. Our ChatGPT-optimized content isn’t working for Perplexity because of structure and freshness issues.

Key insights:

1. Perplexity weights recency much more heavily
2. Long comprehensive guides need extractable sections
3. First-paragraph answers are critical for Perplexity
4. FAQ format is Perplexity’s favorite content type
5. Technical issues (robots.txt, JS rendering) can block visibility

Our action plan:

This Week (Technical):

• Verify PerplexityBot is allowed in robots.txt
• Test pages with JS disabled
• Check page speed for key content

Next 2 Weeks (Content Structure):

• Add TL;DR summaries to top 10 guides
• Create FAQ sections with schema for each guide
• Restructure first paragraphs to be direct answers

Month 1 (Freshness):

• Update statistics in all guides to current year
• Add “Last Updated” dates visibly
• Establish quarterly refresh schedule for key content

Ongoing:

• Track Perplexity citations separately from ChatGPT
• Compare our citation rate to competitors
• Iterate based on what gets cited

Key mindset shift:

Perplexity doesn’t want comprehensive - it wants extractable. Same information, different structure.

Thanks everyone for the Perplexity-specific tactics!