The New SEO: Optimizing Content for Today’s Search Landscape
Search is dead, long live Search!
Anyone using Google.com to search sees many of their queries answered by Google’s AI Overviews, those AI-generated summaries at the top of search results. Other people are abandoning Google completely for Perplexity, or just performing a search in one of the many Large Language Models (LLMs). This is a massive shift in user behavior, and another challenge for SEO professionals. Our old approach of optimizing for the top spot on the SERP must evolve to focus on becoming a cited source in AI-generated responses, requiring a deeper understanding of how AI systems select and synthesize content.
AI Overviews Impact
AI Overviews synthesize information from multiple sources, offering direct answers within Google's search results.
Despite Google’s claim to the contrary, independent studies have found that the presence of AI Overviews can significantly reduce organic traffic to websites. One study reported a 54.6% drop in organic click-through rates when an AI Overview appears for a query.
In the plus column for brands, search results also include links to the cited websites, creating a new dynamic in search visibility. Being cited as a source provides significant authority and visibility benefits for brands, in turn establishing credibility and driving qualified traffic.
Google claims to be maintaining ad revenue, but meanwhile the broader ecosystem of publishers and content creators could see reduced traffic.
Authority at the Core
Google updated its Quality Rater Guidelines by adding Experience to E-A-T (Expertise, Authoritativeness, and Trustworthiness), creating E-E-A-T in December 2022. All content produced by your business should provide unique insights relevant to specific subject areas. Skilled, human writers should write the content and have author bios that showcase qualifications, experience, and expertise in the appropriate field. This framework is particularly crucial for AI Overviews, as AI systems favor content that demonstrates first-hand expertise through case studies, original research, and expert commentary. Include detailed author credentials, cite credible sources, and provide “data provenance” (origin, creation, movement, and dissemination of data) to strengthen your content's authority signals that AI systems can recognize and validate.
Optimize for Questions
Instead of targeting specific keywords, you must create content that answers your prospects' questions. Precision in those answers matters! Structure content around common questions using clear headings and subheadings that mirror natural language queries. Create comprehensive FAQ sections and ensure content directly addresses specific user intents. Use question-based headers (H2, H3) and provide concise, scannable answers in the first paragraph below headers. Remember the old rules for Writing for the Web? Those still apply! Use bullet points, numbered lists, and tables to help the LLM with AI summarization. Your content must add value to a topic through unique expert insights and information not easily found elsewhere. Genuine information will win over generic summaries.
Good Old SEO Fundamentals
Structured data markup using schema.org standards for FAQPage, HowTo, Article, and Organization schemas to help AI systems parse content relevance and context. Prioritize Core Web Vitals, especially Largest Contentful Paint and Interaction to Next Paint, as page performance influences AI system source selection.
Develop using mobile-first optimization, as a significant portion of AI Overview triggers come from mobile searches. Maintain clean site architecture with proper internal linking, XML sitemaps, and robots.txt files. Use HTTPS-secured domains and ensure proper canonicalization to establish trust signals that AI systems recognize when evaluating source credibility and reliability.
Building Trust
In a world of AI slop, AI systems prioritize verifiable content. To strengthen credibility signals, link to peer-reviewed research, government (.gov), educational (.edu), or established media sources.
Publish original research with transparent methodology, including charts and visual evidence that AI can reference for grounding summaries. Use clear definitions, numerical data, and verifiable claims.
Press releases distributed and picked up by publications or websites are a powerful indicator of authority if you link them back to your website.
Similarly, well-crafted podcasts with domain expertise that are technically executed (with transcripts and distribution) are another strong signal of authenticity.
Publishing a book and linking to it on Amazon sends trust signals to Google. Look for similar opportunities for content created by and consumed by actual humans.
Reducing Hallucinations
AI Overviews and LLMs are known for providing inaccurate information. To cut down on this happening to your brand, provide clarity in writing and context through sound technical execution. Consider how voice search and conversational AI interfaces will further change content consumption patterns.
For words with multiple meanings, provide context within the sentence. For example, “wound” could mean “to wind” or it could mean “to hurt.” Including synonyms will increase the likelihood of inclusion because the AI can comprehend the content.
Include author names with the “Person” tag in your normal schema markup and link it to professional profiles like LinkedIn or Google Scholar. Regularly refresh content to maintain accuracy and submit feedback to Google if content is misrepresented in AI responses.
Measuring Success in the AI Overview Era
Traditional metrics require reinterpretation for AI Overview optimization success. Monitor impression share through Google Search Console's Discover and Performance Reports to track visibility in AI-generated responses. To understand user behavior patterns, measure engagement on answer-focused content using heatmaps and scroll depth analysis.
Look for terms with AI Overview potential by tracking visibility in People Also Ask boxes and featured snippets. Develop attribution methods to identify when content appears as a source in AI Overviews, potentially requiring specialized monitoring tools. Focus on measuring the quality of referral traffic from users who click through after viewing AI summaries, as this audience often demonstrates higher intent and engagement levels than traditional organic traffic.
Future-Proofing Your SEO Strategy
From what we see working right now, publishing high-quality, domain-specific content that is technically executed well is the best way to establish and hold a position of authority. Create interlinked content clusters that demonstrate deep topical knowledge and expertise to reinforce that.
Constantly build reputation through independent reviews, press coverage, and trusted backlinks, as AI models continue to use reputation signals from the broader web ecosystem to evaluate source credibility and trustworthiness.
As SEO evolves, consider a budget for paid search. While there are significant challenges for advertisers due to lower CTRs and the rise of zero-click searches, there are also new ad opportunities.
Success depends on creating authoritative, well-structured content that AI systems can effectively understand, extract, and cite while maintaining factual accuracy and user value. While metrics for measuring success continue to evolve, the core principle remains unchanged: provide valuable, accurate information that genuinely helps users find what they're seeking. As AI-powered search and LLMs become increasingly prevalent, content creators who adapt their strategies to serve both human users and AI systems will establish sustainable competitive advantages in the evolving search landscape.
