We analyzed AI Overview citations across ChatGPT, Claude, Perplexity, and Google. 88% come from just 6 platforms. The other 200+ directories? Zero measurable impact.
Most directory submission services brag about submitting to 200+ directories. But Gartner Peer Insights, G2, Capterra, Software Advice, and TrustRadius account for 88% of all review platform citations in AI Overviews.
Meanwhile, Product Hunt, SiteJabber, and PeerSpot are nearly invisible in AI Overviews. And AlternativeTo, SaaSHub, and FinancesOnline? Not cited at all.
Source: SE Ranking analysis of 30,000 commercial keywords and 23 review platforms
These platforms actually get cited by ChatGPT, Claude, and Perplexity. Submit here first.
Most cited B2B review platform. Owns Capterra, GetApp, Software Advice — one strong profile cascades to all.
Claude's #1 review source. GetApp alone is 47.65% of ChatGPT's B2B review citations. Gartner-owned.
More than all directories combined. Perplexity heavily pulls from Reddit. Essential for brand mentions.
ChatGPT's go-to for company info, funding rounds, and product descriptions. Primary source for "What is X?"
Massively overrepresented in LLM training. Your protocol docs, READMEs, and code = high parametric weight.
22% of LLM training data. Long-term goal once you establish notability through other channels.
Part of the 88% review citation ecosystem. B2B focus with verified reviewer requirements.
Heavy Common Crawl presence. Strong parametric knowledge signal. Best for launches and early traction.
Enterprise-focused reviews. Part of the 88% that dominates AI Overview citations.
The llms.txt standard helps AI systems understand your site. These directories index sites adopting the standard.
The llms.txt file tells AI systems what your site is about, how to use your API, and what content matters. Sites like Anthropic, Cloudflare, Vercel, and Perplexity already use it. Getting listed in these directories signals to LLMs that you're AI-native.
Comprehensive directory with token counts. Shows llms.txt and llms-full.txt stats. Easy submission form.
Curated directory by category (AI, Developer tools, Finance, etc.). Features top adopters like Anthropic, Cursor, Vercel.
Verifies your llms.txt file, reviews for quality. Live token count monitoring. Adds within 24-48 hours.
Community-driven directory with Chrome extension, VS Code plugin, and MCP explorer. GitHub PR-based submissions.
Pro tip: Add /llms.txt to your site first, then submit to these directories.
See ours →
Cited by specific LLMs or for specific query types. Worth pursuing for targeted visibility.
84.5% of digital services citations in ChatGPT. Essential for agencies and B2B services.
DA 7521.33% of GitHub Copilot citations. Full crawler access = high training data presence.
DA 90Cited for "alternatives to X" queries in ChatGPT. Zero in AI Overviews. Mixed results.
DA 75Heavy training data presence. Show HN posts build parametric knowledge signal.
DA 92Massive training data presence. Answer relevant questions with product context.
DA 95Content platform in training data. Thought leadership and tutorials.
DA 95Good DA for traditional SEO. Zero measured LLM citation impact. These are what most services submit you to.
Reality check: These directories were not cited at all in AI Overviews despite being popular in SEO circles. They provide backlink value but won't help you get mentioned by ChatGPT or Perplexity.
"Do backlinks help with LLM visibility?"
Yes — but the mechanism has changed.
Backlinks from high-DA sites signal trustworthiness to LLMs during RAG retrieval.
When your brand appears alongside trusted sources, LLMs learn to associate them.
AI systems pull from indexed sources. Being on cited platforms = getting retrieved.
Insights from r/AISearchOptimizers on what actually works
Most companies have zero visibility into what AI says about them. Traditional SEO tools don't work — AI answers are non-deterministic.
Rand Fishkin's SparkToro study: Only 1% repeatability when running the same prompt.
Define buyer-intent prompts
"best X", "X vs Y", "is X good for ___" — not random queries
Run across multiple models
ChatGPT, Gemini, Perplexity, Copilot — behavior varies by platform
Track deltas over time
Are you recommended or just listed? Which competitors appear? What sources get cited?
"If GPTBot ignores your pricing page, you're not getting cited." Check your server logs for AI crawler activity.
"The bot recommends whoever is easiest to parse." Clean structured data = more citations. This is why llms.txt matters.
The real risk isn't that AI replaces SEO tomorrow. It's that competitors quietly gain recommendation share while you're not even measuring it.
Source: r/AISearchOptimizers • SparkToro Research • AirOps Report
LinkSwarm focuses on the platforms that actually matter. Stop wasting time on 200+ directories with zero impact.
Coming soon: AI Citation Tracker — see which directories actually drove citations for your brand.