AI Search is PRINTING (ChatGPT, GEO & Perplexity)

Geo AI Search: A Deep Dive

Key Concepts:

• Geo AI Search (AI Search): Utilizing AI, specifically LLMs (Large Language Models), to answer user queries by aggregating information from various online sources.
• AI Fanning: The process where an AI expands a user's initial query into numerous derivative queries to gather comprehensive information.
• Surface Area: The extent to which a brand is mentioned or included on the web pages that AI search engines are scraping for information.
• Purchasing Decision Time Horizon: The length of time a customer spends researching and considering a purchase.
• Listicles: Articles presented in list format, often favored by AI search engines as sources of information.

1. What is Geo AI Search and Who is it For?

• Geo AI, or more accurately, AI Search, involves users querying LLMs like Perplexity, ChatGPT, and Gemini to receive answers compiled from various sources.
• It's particularly relevant for businesses with a long purchasing decision time horizon, where customers conduct extensive research before buying.
• Two customer types that have seen success are:
  • Local service businesses: (e.g., roofing, HVAC) where customers lack regular purchasing experience and rely on research.
  • Software (SaaS) companies: Where businesses commit their entire operations to a CRM or similar tool, requiring thorough comparison of options.
• While less effective for e-commerce in general, it can work for brands with a cult following or those selling higher-ticket items that require more consideration.

2. The Mechanics of AI Search: How it Works

• When a user enters a query into a chat interface, the AI performs AI fanning.
  • The AI expands the initial query into numerous (e.g., 100) more descriptive, derivative queries.
  • These derivative queries are then searched on platforms like Google and Bing.
• The AI scrapes the top-ranking pages (e.g., the top 1000 pages) from the search results and pulls their content into its context window.
• The AI then uses this aggregated information to answer the user's original query.
• Evidence of AI fanning can be found in Google Search Console by filtering for queries exceeding 50 characters, which often appear as AI-generated and show impressions but no clicks.

3. Strategies for Winning in AI Search: Surface Area and Brand Mentions

• To succeed in AI search, businesses need to maximize their surface area within the pages that AI is scraping.
• This means getting included in listicles and securing brand mentions across relevant websites.
• The more a brand is mentioned across the scraped pages, the more likely it is to be suggested as a top result.
• The key is to identify the pages that AI is sourcing from for relevant queries and then actively seek inclusion on those pages.

4. Tools and Tactics: Building Your AI Search Stack

• Several tools can help identify the URLs being referenced by AI search engines:
  • Prompt Watch
  • AI SEO Tracker
  • Try Profound
• These tools allow you to input your product or service, generate related queries, and then discover the URLs being referenced for those queries.
• Once you have a list of URLs, the next step is to reach out to the website owners and negotiate to get your brand included.
• This can be expensive, with costs potentially reaching $500 per link.
• Negotiating affiliate commissions can help reduce costs.
• Prioritize URLs that are referenced most frequently across different queries for maximum impact.

5. The Speed of AI Search SEO

• Unlike traditional SEO, which can take months or years to yield results, AI search SEO can produce noticeable impact within 24 hours.
• This is because the AI directly aggregates information from the URLs where your brand is mentioned.
• The increasing adoption of AI search platforms like Perplexity and ChatGPT makes this a timely area to invest in.

6. Cautions and Considerations

• Be wary of services promising to create vast private blog networks to influence AI, as their sustainability and effectiveness are questionable.
• AI search relies heavily on the existing search engine infrastructure, particularly Google.
• The pages ranking on the first few pages of Google are the primary source material for AI responses.
• Therefore, focus on getting your brand mentioned on those top-ranking pages.
• AI search SEO can be viewed as a form of influencer marketing, where you're essentially paying to be included on influential lists and resources.
• Remember that AI search is just one component of a broader marketing strategy.
• Algorithm changes and new model releases can significantly impact results, so diversification is crucial.

7. Tools and Metrics: Beyond Vanity Metrics

• While tools like Prompt Watch can track brand mentions, focus on identifying the specific URLs being referenced by AI search.
• The goal is to understand where the AI is getting its information and then actively seek inclusion on those sources.
• Ahrefs and SEMrush are expected to offer similar solutions in the future.

8. Notable Quotes

• "It's just SEO. It's just like a layer on top of it." - Cody Schneider, emphasizing the fundamental connection between AI search and traditional SEO.
• "You can get platformed just like with this you can get platformed just like anything else." - Cody Schneider, highlighting the risk of relying solely on AI search due to potential algorithm changes.

9. Synthesis/Conclusion

AI search presents a significant opportunity for businesses, particularly those with longer purchasing decision time horizons. By understanding how AI search engines gather information and strategically increasing their surface area on relevant web pages, businesses can significantly improve their visibility and drive high-converting traffic. However, it's crucial to approach AI search as one component of a broader marketing strategy and to remain adaptable to algorithm changes and new model releases. The key is to focus on identifying the URLs being referenced by AI, actively seeking inclusion on those pages, and prioritizing high-impact opportunities.