The New SEO Frontier: Influencing ChatGPT
Summary
This presentation, led by Chris M. Walker, detailed practical strategies for optimizing content to rank within Large Language Models (LLMs) like ChatGPT. Initially skeptical, the founder of Legiit began noticing significant referral traffic from these platforms and developed a systematic approach to influence LLM recommendations. The core strategy revolves around understanding the specific search patterns of AI chatbots, creating optimized content formats, and establishing a consistent, authoritative brand presence across the web. This optimization strategy resulted in a 999% increase in referral traffic from ChatGPT.
How LLMs Search and Source Information
The key to the strategy is “watching the AI think.” The speaker demonstrated that when an LLM is asked a query (e.g., “best website to buy backlinks”), it reveals a combination of search actions, which informs the content strategy:
- Broad Terms: Searching for generic, high-level queries (e.g., “best backlink marketplaces 2025”).
- Branded Terms: Looking for specific company reviews and pricing pages.
- Data Checks: Performing site searches and traffic checks on potential sources.
Key Platforms Referenced by LLMs
LLMs frequently cite information from specific channels. Optimizing presence on these platforms is essential for visibility:
- Forums: Reddit and niche industry forums.
- “Parasites”: High-authority platforms like YouTube, Medium, and LinkedIn.
- Review Sites: Platforms such as TrustPilot.
- Brand-Owned Properties: Company websites and, significantly, support desk articles (e.g., Zendesk, Intercom), which are highly trusted by bots for factual Q&A.
Optimal Content Types and Strategy
To generate citations and traffic from LLMs, certain content formats perform exceptionally well:
Winning Content Formats
| Content Type | Strategy |
| Listicles | “Top X Products” or “Best of [Current Year]” compilations. |
| Comparison Pages | “X versus Y” format. The speaker suggested a hack: compare methodologies or concepts (e.g., “PBNs vs. guest posts vs. niche edits”) instead of only direct competitors. |
| Q&A Content | Direct answers to questions on forums and support desks. |
Canonical Source of Truth
The speaker discovered that LLMs often misstate facts about a brand. The solution is to create a definitive, structured source of information:
- Dedicated Page: Publish a specific page (150–300 words) on the company site (e.g.,
/what-is-our-brand) containing factual information, core features, launch year, and an FAQ. - Consistent Phrasing: Use near-verbatim wording for the brand description across this page and all external entities.
Entity Building and Experimentation
- Branded Profiles: Build out profiles on platforms like Wikidata, social media, review sites, and forums, all using the consistent canonical phrasing. For videos, the surrounding title and description text is crucial, as LLMs cannot interpret the video content itself.
- RLHF Experimentation: The team experimented with Reinforcement Learning from Human Feedback (RLHF) by providing feedback to ChatGPT when the brand was omitted, suggesting it be included. This showed potential, though inconsistent, results for influencing future responses.
Results and Implementation Tools
Traffic Impact
The optimization strategy yielded impressive results:
- Traffic Volume: 10,683 visitors referred directly from ChatGPT year-to-date.
- Growth: A 999% increase in ChatGPT referral traffic.
- Referral Rank: ChatGPT became the third-highest direct referral source, following only Google and Facebook.
- Conversion Potential: The traffic included visits to commercial and transactional pages, suggesting a positive sales impact.
My Take: What This Means for Solo Publishers
The 999% ChatGPT referral traffic increase Walker demonstrated is a real signal — not a fluke. For solo publishers and affiliate sites, the gap between those who understand this shift and those who don’t is only going to widen from here.
The robots.txt check is non-negotiable right now. Tavily research confirms that a surprising number of sites are still blocking OAI-SearchBot, ChatGPT-User, PerplexityBot, and ClaudeBot — sometimes from outdated security configs. If those bots can’t crawl you, none of the content optimization matters. Do this first, before anything else.
IndexNow is quietly one of the highest-leverage moves for AI visibility. Since ChatGPT’s live browsing runs on Bing’s index, you need to ping Bing the moment content goes live. If you’re on Rank Math (as I am on most sites), it’s already built in — just verify it’s enabled. Two minutes of setup that removes a major visibility bottleneck.
The comparison-methodology format is underutilized for affiliate SEO. Walker’s suggestion to compare methodologies rather than just products — think “PBNs vs. guest posts vs. niche edits” instead of “Tool A vs. Tool B” — is genuinely useful. These pages get cited by LLMs because they answer the meta-level research questions buyers are asking AI chatbots. I’ve been building more of this format based on what I covered in The Technical Framework for LLM Content Optimization — the structural patterns that make content extractable by AI systems are the same ones that make comparison pages work.
Entity consistency is the long play, and it stacks. Using near-verbatim language about your brand or niche across your site, YouTube descriptions, and high-authority platforms is something most solo publishers skip. But paired with the platform approach from Parasite SEO & LLM Domination, it compounds — the Medium and LinkedIn profiles you build for LLM visibility also feed traditional SEO signals. Two birds.
What to skip for now: The RLHF feedback experimentation (submitting corrections directly to ChatGPT about your brand) is too inconsistent to prioritize. Interesting experiment, but not worth your time over the technical basics. Also worth understanding the darker side of LLM influence — Alan CladX’s work on AI source poisoning is a useful reminder that these systems can be gamed in both directions.
For the full picture on how topical coverage drives LLM citations, see LLM-Driven SEO: The Shift to Topical Coverage and The New SEO Formula: Adapting to AI Search. The formula is becoming clearer: entity authority + structured content + technical access = AI citations. For affiliates, it’s the same fundamentals as traditional SEO — just with a different extraction layer on top.