How to Transform SEO into AI SEO

Key Concepts:

• AI SEO: Adapting SEO strategies for AI-powered search engines and large language models (LLMs).
• Entities: Clearly defined concepts (people, brands, places) recognized across the web.
• Knowledge Graphs: Maps connecting entities with their attributes, used by AI to understand user intent.
• AI Overviews: Summaries at the top of Google search results, curated from multiple sources.
• Search Everywhere Strategy: Ensuring brand visibility across various platforms where LLMs gather data.
• E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness – crucial signals for AI.
• Semantic SEO: Content creation focused on covering the full scope of a topic and its related concepts.
• Technical SEO for AI: Optimizing website technical aspects for AI crawlers, including structured data and server-side rendering.
• LLMs.txt: A markdown file hosted on a website to directly feed information to LLMs.
• Brand Mentions: Positive mentions of a company on reputable sites, even without backlinks.

1. Introduction to AI SEO

• The webinar focuses on transforming traditional SEO into AI SEO, highlighting the nuances required for success in the AI-driven search landscape.
• While SEO and AI SEO share similarities, adapting to AI is crucial for desired results.
• Neil Patel introduces Nikki Lamb (Head of SEO, NP Digital US) and Kira Stagger (SEO Manager, NP Digital) as co-presenters.
• NP Digital's global presence provides extensive data across various marketing sectors, including AI SEO.
• A QR code and the URL npdigital.com are provided for those seeking assistance with AI SEO.
• The Future of Marketing and AI Virtual Summit is announced (npdigital.com/summit), featuring speakers discussing strategies for the new landscape.

2. The New Rules of Search

• The shift from solely ranking on Google to getting mentioned on platforms like ChatGPT is discussed.
• While ChatGPT doesn't drive the same volume as Google, its growth is rapid (400 million to 700 million weekly active users in months).
• Being present on these platforms is essential due to their growing user base and high conversion rates.
• AI-powered search visitors are 4.4x higher in value compared to organic search visitors due to their higher qualification and engagement.
• The AI market is projected to reach $1.81 trillion by 2030.
• The webinar will cover reframing the SEO mindset, adapting to generative AI, the three pillars of AI SEO, and content formats/structure.
• Content should be created for humans but packaged for AI.

3. The Shift from Keywords to Entities

• Search engines and AI are now focused on understanding concepts (entities) rather than just matching keywords.
• An entity is a clearly defined concept (person, brand, place) recognized across the web.
• AI maps relationships between entities to understand context.
• Optimizing content with entities in mind positions brands to appear in AI-generated responses.

4. Knowledge Graphs and AI Overviews

• Knowledge graphs are maps connecting entities with their attributes, helping AI understand user intent.
• For example, a search for "best laptops" involves entities like Apple, Dell, battery life, price, and user reviews.
• AI overviews summarize information from multiple sources into a cohesive answer.
• While AI overviews may lower traditional clicks, they build trust and brand visibility.

5. Building Trust and Credibility in AI Search

• Being consistently cited across multiple AI platforms builds trust and credibility.
• Examples are given of clients gaining business due to consistent mentions on ChatGPT and other LLMs.
• A lead from a private company generating over $100 billion in revenue was secured due to NP Digital's repeated recommendations on ChatGPT and Perplexity.

6. Search Everywhere Strategy

• To win in the AI era, a "search everywhere" strategy is essential.
• Brands must show up organically on platforms like LinkedIn, YouTube, Reddit, Wikipedia, and Forbes.
• AI overviews and ChatGPT heavily cite YouTube and Reddit.
• Promoting content across these platforms is crucial.

7. The Importance of E-E-A-T

• E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is crucial for AI.
• AI leans into these signals, requiring brands to demonstrate first-person experience and verifiable expertise.
• Clear author bio pages, consistent brand presence across third-party sites, and engagement metrics are important.
• Outdated or inaccurate content should be refreshed and optimized.
• People are prioritizing the "best" solutions, making authority and reputation critical.

8. AI-Powered Content Strategy

• Creating full content ecosystems that mirror how AI connects information is essential.
• Instead of a single blog post, build a cluster of topics around a hub topic (e.g., email marketing: deliverability, tools, templates).
• Consider multimodal relevance (text, video, visuals, voice search).
• Content briefs should highlight entity relationships.
• AI can accelerate ideation, but human strategists are still needed.
• Tools like UberSuggest can surface long-tail opportunities and competitor gaps.
• Briefs should include semantic terms, credible sources, and supporting formats.

9. Rethinking Search Volume and Semantic SEO

• Value answering detailed questions over chasing high-volume keywords.
• Focus on semantic-first content to cover the full scope of a topic and its relationships.
• For example, when writing about electric vehicles, connect the term to entities like charging stations, range, tax incentives, and battery technology.
• AI tools can help structure content outlines.

10. The Human Element in AI Content

• AI can draft content quickly, but human oversight is crucial for trust and credibility.
• Editors and subject matter experts bring experience, nuance, and perspective.
• Balance AI's speed with human credibility.
• Optimize visuals with descriptive file names, alt text, and schema markup.
• Use clear captions and scripts for videos.
• Structure content in short, scannable chunks for spoken responses.

11. Technical SEO for AI

• AI crawlers collect and parse information differently than Googlebot.
• AI crawlers focus on gathering text to train their models, without a multi-layered ranking algorithm.
• Structured data is highly correlated with content ranking on LLMs.
• Use schema markup to clearly define relevant entities (people, products, events, concepts).
• Leverage AI to audit websites for broken links, indexing issues, and core web vitals.
• AI can help prioritize technical fixes.

12. Client-Side Rendering and LLMs.txt

• LLMs cannot perform client-side rendering, so key website content must appear in the initial HTML load.
• Create an LLMs.txt file to bypass HTML/JavaScript parsing limitations and directly feed information to LLMs.
• The LLMs.txt file should include links to key assets, documents, and resources.
• The LLMs.txt file should be continually updated.
• Example: A healthcare brand's LLMs.txt could list product families, surgical devices, safety data, and patient portal resources.

13. Case Study: Universal Technical Institute (UTI)

• UTI lost organic visibility due to algorithm updates.
• NP Digital overhauled their technical SEO, optimized core web vitals, and implemented structured data.
• Entity-rich content was introduced to improve AI parsing and authority.
• Brand credibility was reinforced.
• Results: 411% year-over-year growth in organic search sessions for new program expansions, 18% increase in total organic search queries, and a 20% rise in non-branded page one rankings.

14. Authority and Brand Mentions

• AI is looking at raw brand mentions (positive mentions on reputable sites) in addition to backlinks.
• Brand mentions are credibility signals scattered across the web.
• Visibility is shaped by how a brand is represented outside its own website.
• Use digital PR to target journalists and outlets aligned with the brand.
• Track brand mentions to see where to focus next.
• Secure citations by providing expert insights, proprietary data, and quotable commentary.
• Use platforms like HARO (Help a Reporter Out) to respond to journalist queries.
• Contribute data and studies to create new, fresh information.

15. Case Study: Online Marketplace

• An online marketplace struggled with keyword rankings and clicks.
• NP Digital created 58 relevant FAQs and implemented them across 11 pages with FAQ schema markup.
• Results: Immediate spike in traffic, 41% increase in clicks to target URLs, 211% increase in money keywords, and a 5% increase in conversions.

16. Building an AI SEO Roadmap

• Step 1: Track search visibility using tools like Scrunch Also Asked and Perplexity Citation Tracker.
• Take screenshots and benchmark AI responses, as they change frequently.
• Monitor entity coverage and technical readiness.
• UberSuggest will offer a free AI visibility report (August 19th for waitlist, September 15th for everyone).
• Step 2: Build a multi-channel strategy beyond on-site SEO.
• Leverage forums like Reddit and Quora, educational videos on YouTube, and structured comparison pages.
• Step 3: Train your team to think entity-first, understand the connection between content, SEO, and PR, and collaborate effectively.

17. Bonus Topics: Paid Amplification and First-Party Data

• Promote E-E-A-T optimized content across Reddit and YouTube.
• Amplify content and tools to boost authority signals.
• Build interactive tools, calculators, and quizzes to collect first-party data.
• Use first-party data to understand audience preferences and create unique content.

18. Conclusion

• Traditional SEO factors help in AI-powered search, but entity optimization, E-E-A-T signals, brand mentions, and reviews are crucial.
• Focus on multiple content strategies (blog posts, Wikipedia mentions, Reddit content, YouTube content).
• Follow the key takeaways from the presentation.
• NP Digital can assist with AI SEO in multiple languages and countries (npdigital.com).
• Upcoming webinar: How to do content marketing in an AI-first world.

19. Q&A Highlights

• AI SEO, GIO, and LLM optimization are essentially the same thing.
• Identifying high-performing entities involves external research, Google Search Console data, Wikipedia pages, and knowledge graphs.
• Getting brands mentioned on Wikipedia requires significant press coverage. Reddit engagement requires authenticity and a user-focused approach.
• SMBs can succeed in AI search, especially local businesses.
• PPC will likely integrate into LLMs, potentially using pay-per-click or pay-per-conversion models.