Nathan Gotch on AI SEO, LLM Search & Brand Visibility | Marketing Stack 2025
In this session of Marketing Stack 2025, Nathan Gotch, founder of Gotch SEO Academy and CEO of Rankability, explores the evolving search landscape as Large Language Models (LLMs) redefine information discovery. He emphasises that we are moving from a world of traditional ranking factors to one where visibility no longer guarantees clicks, as AI generates answers instantly.
How are LLMs changing traditional SEO and search discovery?
Traditional SEO focuses on traffic and ranking, but LLMs prioritise generating immediate responses. Nathan notes that while 80% of success still relies on traditional SEO foundations, technical performance, deep content strategy, and link acquisition, the remaining 20% involves unique variables specific to AI platforms.
For instance, a website ranking number one in traditional search may not appear in ChatGPT or Google’s AI mode because these platforms use different signals to determine "winners".
Why is transparency and documenting SEO actions important for agencies?
Nathan argues that agencies must move away from "proprietary" secrets and embrace transparency. He distinguishes between lagging goals (traffic and revenue) and leading goals (actual inputs like landing page optimization).
By using an SEO action dashboard, agencies can document every granular action taken. This "sells the work" as much as the outcome, which is critical for client retention when results are in a "black box" or a campaign hits a plateau.
What are the ranking factors for AI search engines versus traditional Google?
Platforms vary significantly in how they retrieve data. While Google’s AI mode relies heavily on the local pack for location-based queries, ChatGPT ignores the local pack in favour of third-party platforms like Yelp, Angie, and the Better Business Bureau.
For an LLM to recommend a brand, it looks for consistent confirmation and brand association across diverse sources such as Reddit, YouTube, and LinkedIn. Furthermore, LLMs use a "whitelist" of the top 1 million most trusted websites to assign authority points during training.
How to track brand visibility and traffic from ChatGPT and other AI platforms?
Tracking AI search is difficult because referral traffic is currently small compared to traditional Google. Nathan suggests using Google Looker Studio to bucket AI platforms and monitor distribution.
He also recommends using regex formulas in Google Search Console to identify "AI-centric" queries, those over 10 words or those using command-based verbs like "suggest" or "recommend". The most vital metric, however, is Share of Voice: determining whether the brand appears in generated responses and, if so, at what position.
What is the best SEO strategy for brands in the age of AI search?
Nathan advises brands to be their own "number one advocate" by controlling their brand message through branded queries. Rather than just building a website, marketers should focus on multi-platform SEO, establishing authority on YouTube or LinkedIn, which are often indexed and ranked highly by LLMs.
Ultimately, the goal is to ensure the brand is an actual entity rather than just a keyword-rich description, which requires consistent mentions alongside other established brands
