How do AI crawlers handle infinite scroll? Our content isn't getting indexed

Let me break down how different AI crawlers handle JavaScript:

AI Crawler JavaScript Support:

The core problem:

Infinite scroll requires:

1. JavaScript execution
2. Scroll event triggering
3. Additional HTTP requests
4. Rendering of new content

Most AI crawlers fail at step 1 or 2.

Why SSR isn’t enough:

Your SSR serves the initial page. But infinite scroll content isn’t “initial” - it loads on interaction. SSR doesn’t solve the interaction dependency.

The fundamental issue:

Infinite scroll is fundamentally incompatible with current AI crawler capabilities. You need an alternative approach.

We went through this exact problem. Here’s our solution:

The hybrid approach implementation:

// URL structure
/blog              // Infinite scroll (user default)
/blog/archive/1    // Paginated (crawler accessible)
/blog/archive/2

Key implementation details:

1. Sitemap includes only paginated URLs

   • AI crawlers find /blog/archive/* pages
   • These render full content server-side

2. Infinite scroll page loads same content

   • Uses pagination API under the hood
   • Better UX for humans

3. Internal links point to individual articles

   • Not to infinite scroll position
   • Each article has its own URL

4. robots.txt guidance:

# Let crawlers focus on individual articles
# Not the infinite scroll container
Sitemap: /sitemap.xml

Results:

• Human UX unchanged (infinite scroll)
• AI crawlers access all content via archive pages
• Individual articles all indexed
• Citation rate improved 4x after implementation

Next.js specific approach:

Using getStaticPaths + getStaticProps:

// pages/blog/page/[page].js
export async function getStaticPaths() {
  const totalPages = await getTotalPages();
  const paths = Array.from({ length: totalPages }, (_, i) => ({
    params: { page: String(i + 1) }
  }));
  return { paths, fallback: false };
}

export async function getStaticProps({ params }) {
  const posts = await getPostsForPage(params.page);
  return { props: { posts, page: params.page } };
}

Benefits:

• Static pages for each pagination
• Full content in HTML at build time
• AI crawlers get complete content
• Fast loading (static)

Then add infinite scroll as enhancement:

• Client-side infinite scroll uses same API
• Progressive enhancement approach
• Works without JS too

This gives you the best of both worlds.

Adding prerendering as an option:

Prerendering services for AI crawlers:

You can detect AI crawler user agents and serve prerendered content:

// middleware
if (isAICrawler(req.headers['user-agent'])) {
  return servePrerenderedVersion(req.url);
}

AI crawler detection:

const aiCrawlers = [
  'GPTBot',
  'ChatGPT-User',
  'Google-Extended',
  'ClaudeBot',
  'PerplexityBot',
  'anthropic-ai'
];

function isAICrawler(userAgent) {
  return aiCrawlers.some(crawler =>
    userAgent.includes(crawler)
  );
}

Prerendering options:

• Prerender.io
• Rendertron
• Puppeteer-based custom solution
• Build-time prerendering

Caution:

Not all AI crawlers identify themselves clearly. Some might be missed. This is a supplementary approach, not a replacement for proper pagination.

Testing methodology for AI crawler accessibility:

Manual tests:

1. Disable JavaScript test:

   • Open your blog in browser
   • Disable JavaScript
   • What content is visible?
   • This approximates non-JS crawler view

2. View source test:

   • View page source (not inspect element)
   • Is your content in the HTML?
   • Or is it just JavaScript placeholders?

3. curl test:

   curl -A "GPTBot/1.0" https://yoursite.com/blog/
   

   • Does the response contain actual content?

Automated tests:

4. Google Search Console:

   • URL Inspection tool
   • “View Rendered Page” shows what Googlebot sees
   • (Not AI crawlers, but similar JS rendering)

5. Lighthouse audit:

   • Check “SEO” category
   • Crawlability issues flagged

What you want to see:

• Content in initial HTML response
• Links to all pages discoverable
• No JS required for content visibility

E-commerce perspective:

We have 10,000+ products with “load more” functionality. Here’s our solution:

Category page structure:

/category/shoes                    # First 24 products + load more
/category/shoes?page=2            # Products 25-48
/category/shoes?page=3            # Products 49-72

Implementation:

1. Initial page always has pagination links

   • Even with infinite scroll enabled
   • Footer contains page 1, 2, 3… links

2. ?page= parameters are canonical

   • Each page is its own content
   • Not duplicate of main page

3. Sitemap includes all paginated URLs

   • Not just the infinite scroll base URL

4. Products have individual URLs

   • Category pagination is for discovery
   • Products are the real content

Result:

AI platforms cite our individual product pages, which they discover through the paginated category structure.

This has been incredibly helpful. Here’s my implementation plan:

Approach: Hybrid pagination

Phase 1: Add paginated routes (Week 1-2)

• Create /blog/archive/[page] routes
• SSR for full content in HTML
• Include pagination navigation
• Update sitemap to include these

Phase 2: Update existing infinite scroll (Week 3)

• Keep infinite scroll for /blog
• Use archive pages as data source
• Canonical from /blog to /blog/archive/1

Phase 3: Testing and validation (Week 4)

• Test with JS disabled
• curl tests for AI user agents
• Monitor AI citation rates

Technical implementation:

/blog                 → Infinite scroll (humans, canonical to archive/1)
/blog/archive/1       → Paginated (crawlers, canonical to self)
/blog/archive/2       → Paginated (crawlers)
/blog/[slug]          → Individual articles (main content)

Key principles:

• Content accessible without JavaScript
• Every piece of content has a direct URL
• Sitemap includes all content pages
• Infinite scroll is enhancement, not requirement

Thanks everyone for the detailed technical guidance.