SEO Trends
What's gaining traction in search right now. Keyword trends, AI search updates, and practitioner commentary.
The SEO landscape in 2026 looks fundamentally different from even two years ago. AI search engines now process hundreds of millions of queries daily. ChatGPT, Perplexity, Claude, and Google's AI Overviews have created an entirely new discovery layer where users get synthesised answers instead of scanning link lists. For SEO practitioners, this means tracking two worlds simultaneously: traditional search rankings and AI search visibility.
Three macro trends are defining SEO in 2026. First, generative engine optimisation (GEO) has emerged as a discipline alongside traditional SEO. Brands are now optimising content to be cited by AI systems, not just ranked by Google. Second, the search engine landscape is more fragmented than at any point in the past decade. Our 100-brand ecommerce data shows ChatGPT already sends more sessions than Bing Organic. Third, Google's AI Mode and AI Overviews are reshaping click behaviour on the SERP itself, with measurable declines in click-through rates for informational queries where AI summaries appear.
This page tracks what's actually moving in search right now. The trending topics below are derived from query data across 300+ sites monitored through SEOTesting and Google Search Console. The Google Trends widgets show live search interest data. The AI Search Pulse section surfaces the latest platform updates across ChatGPT, Google, Perplexity, Copilot, and Claude. Everything is updated regularly with practitioner commentary from Lawrence Hitches, Chief of Staff at StudioHawk, Australia's largest dedicated SEO agency.
Whether you're an SEO practitioner tracking emerging opportunities, a marketing manager evaluating where to invest, or a business owner trying to understand how AI is changing search, this page gives you the signal without the noise.
Trending Topics
Search topics gaining traction this week based on query data across 300+ sites.
Google confirmed in June 2026 that Search ignores llms.txt (it neither helps nor hurts rankings), Ahrefs found 97% of published llms.txt files received zero requests in May 2026, and John Mueller called the discovery use case a dead end on Search Off the Record. Verdict: keep it as low-cost insurance for the agentic future, not a ranking or traffic lever.
Our Bing AI Search report shows 17,211 grounding citations across 313 queries. As Google clicks flatten, citation share (your percentage of citations per grounding query) is becoming the metric that matters. Track it in Bing Webmaster AI Visibility, not just GSC.
Enterprise SEO platform and tool comparison queries are the top AI grounding cluster: 2,799 citations at up to 85% share on 'best enterprise SEO platform comparison 2026'. AI assistants increasingly answer the buying question directly, so the comparison page is the asset.
Google's June 2026 spam update finished rolling out on 26 June. Sites leaning on scaled or templated content took the hardest hits. The defence is unchanged: helpful, first-hand, E-E-A-T-backed content, not volume.
Queries like 'GEO content audit' and 'audit AI search optimization' appear across the grounding report at 45 to 58% share. Auditing a site for AI citation-readiness (answer-first structure, extractable chunks, entity clarity) is emerging as its own deliverable.
'sydney seo services' remains a live commercial-intent gap: demand persists and there is still no dedicated Sydney page. The single clearest net-new opportunity on the site.
Shifting Interest
Topics seeing reduced search activity this week.
Still flat at 1 impression, down from 53 a fortnight ago. Fully captured by AI Overviews and not recovering. A clean example of an informational query absorbed by AI.
The claude.ai/referral query cluster fell roughly 79% from its spike. It was a transient URL-curiosity surge (people Googling the unfamiliar string), not durable demand. Do not build for it.
Google retired FAQ rich results in 2026. FAQ schema is now useful for AI extraction and clarity, not for Google rich results. Do not pitch FAQ schema as a SERP-feature lever.
AI Bot Crawl Leaders
Pages receiving the most visits from AI crawlers (ChatGPT-User, GPTBot, Applebot, Amazonbot) this week. High crawl volume signals agent trust — these are the pages AI systems are reading most actively.
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What SEO Ranking Factors Actually Matter in 2026
Most ranking factor lists are either opinion-based or built from a single study. This consensus is different: it layers correlation data, multi-study agreement, and what I actually see moving rankings across 300+ sites. The biggest shift in 2026 is not any single factor changing -- it is that Google now evaluates pages through layered systems, not a checklist. The sites winning are the ones strong across every layer simultaneously. And for AI search, the rules are already diverging: brand mentions matter more than backlinks, and content depth matters more than keyword placement.
How This Ranking Factor Consensus Was Built
Built by cross-referencing major ranking factor studies (Semrush 300K SERPs, Backlinko 11.8M results, Surfer SEO 1M SERPs, Ahrefs 75K brands, SE Ranking correlation data) and validated through our own client data analysis across 300+ sites monitored via Google Search Console.
Factors are grouped into tiers based on how many independent sources agree. Tier 1 factors appear in every major study. Tier 2 factors have strong but not universal support. Tier 3 factors are where the data diverges or the signal is shifting rapidly. Each factor includes the specific data points behind the consensus, how it connects to other trends on this page, and what to do about it.
Tier 1: Universal Agreement
Every major study and source lists these as top factors. The industry consensus is clear.
Content Relevance and Quality
UniversalThe data: Semrush: 0.47 correlation (highest individual factor). Validated through our own client data at 23-25% relative weight. Every study puts this #1 or #2.
Content that directly matches search intent and demonstrates comprehensive topical understanding consistently outranks content optimised purely for keywords. Semrush's 300K SERP study found text relevance correlates at nearly double the strength of any authority metric.
How it connects: This is the foundation beneath the generative engine optimisation trend. AI search engines select grounding content based on topical comprehensiveness, not keyword density. Pages ranking well in traditional search are 86% likely to appear in AI Overviews too.
What to do: Audit top landing pages for search intent alignment. Map entity coverage against competitors. Target comprehensive topical depth, not just keyword inclusion.
Backlinks and Link Authority
UniversalThe data: Backlinko: #1 results have 3.8x more backlinks than #2-#10. Our client data shows ~13-15% relative weight (declining year-over-year from ~22-27%). Still top 3 universally across every credible study.
Backlinks are declining in weight year-over-year across every study, but no credible source says they are irrelevant. The shift is from quantity to quality: referring domain diversity and topical relevance now matter more than raw link count.
How it connects: For AI search, the picture diverges sharply. Ahrefs' 75K brand study found backlinks correlate at only 0.218 for AI visibility, while unlinked brand mentions correlate at 0.664. Traditional link building still matters for Google, but AI search rewards brand authority through mentions, not links.
What to do: Prioritise topically relevant links over volume. Monitor referring domain diversity. For AI visibility, invest in brand mention strategies (digital PR, expert commentary, thought leadership) alongside traditional link building.
Search Intent Match
UniversalThe data: Every source lists intent alignment as a prerequisite for ranking. ClickRank and Semrush both position it as the gateway signal: if intent is wrong, nothing else matters.
Google evaluates whether your page satisfies what the user actually wants, not just whether it contains the right keywords. A perfectly optimised page targeting the wrong intent will not rank. This is especially true post-AI: Google's systems now understand query intent at a much deeper level.
How it connects: The rise of ChatGPT source tracking and AI referral traffic. Users arriving from AI search have already had their query interpreted by an LLM. Content that matches the intent behind the synthesised answer gets the click.
What to do: Analyse the current SERP for every target keyword before writing. What format dominates? (Listicle, guide, tool, comparison?) Match it. Check People Also Ask for intent signals.
Page Speed and Core Web Vitals
Near-universalThe data: Our client data analysis: load time r=-0.24 (strongest individual on-page factor), validated as the #1 on-page factor by weight. Pages with LCP under 1.0s rank 7.5 positions higher than those over 4.0s. INP has replaced FID as the interactivity metric.
Page speed shows the strongest individual on-page correlation with ranking position across our client data. Our analysis across 300+ sites confirms it consistently outweighs other individual on-page factors. Even conservative studies confirm it is growing in importance, not shrinking.
How it connects: Speed directly feeds into user engagement signals. Slow pages generate negative NavBoost click signals (badClicks, bounces) which compound the ranking penalty. This creates a feedback loop: slow page loses position, gets fewer clicks, loses more position.
What to do: Target full page load under 1.5 seconds. TTFB under 800ms. All Core Web Vitals green (LCP <2.5s, INP <200ms, CLS <0.1). Prioritise server-side speed before client-side optimisation.
Technical Crawlability and Indexability
Near-universalThe data: Search Engine Land frames this as the absolute prerequisite: if Google cannot crawl it, nothing else matters. Every technical SEO source lists HTTPS, clean URLs, XML sitemaps, and robots.txt as baseline requirements.
This is the unsexy factor that gates everything else. Pages that are blocked, slow to render, or riddled with redirect chains never get the chance to compete on content or links. Our client data confirms it: pages implementing more baseline structural elements consistently outperform those with gaps.
How it connects: The pagination SEO and URL redirect trends on this page. Both are technical crawlability fundamentals seeing renewed search interest as sites scale and accumulate technical debt.
What to do: Audit crawlability with Screaming Frog or Sitebulb. Fix redirect chains, orphan pages, and canonical issues. Ensure all key pages are in the XML sitemap and rendering correctly.
Tier 2: Strong Agreement
Most major studies and our own client data support these. The evidence is strong but with more nuance and debate.
E-E-A-T (Experience, Expertise, Authority, Trust)
Strong consensusThe data: Google's Quality Evaluator Guidelines treat E-E-A-T as a page quality framework, not a direct ranking signal. However, multiple studies show strong correlation between E-E-A-T indicators (author bios, citations, credentials) and rankings, especially for YMYL topics.
E-E-A-T is not a single score Google calculates. It is a framework reflected across multiple ranking systems: site quality scores, author entity recognition, consensus scoring, and trust signals. The extra 'E' for Experience (added 2022) rewards first-hand knowledge, not just credentials.
How it connects: AI search amplifies E-E-A-T signals. LLMs preferentially cite sources that demonstrate expertise and first-hand experience. This connects directly to the Claude for SEO trend: practitioners creating original analysis and unique data are more likely to be cited by AI systems.
What to do: Add author entities with credentials to key pages. Demonstrate first-hand experience (case studies, original data, screenshots). Build topical authority through depth, not breadth.
User Engagement Signals
Strong consensusThe data: Our client data: dwell time 0.84 correlation (strongest individual engagement signal). Bounce rate: -0.68 correlation. Backlinko: average time-on-site for page 1 results is 2.5 minutes. Engagement weight growing fastest year-over-year (~12% and climbing).
Google's NavBoost system measures clicks, long clicks, short clicks, and last longest clicks. The correlation data is striking: dwell time at 0.84 is the strongest individual engagement correlation we see across our client base. User engagement is no longer a tiebreaker; it is a primary signal.
How it connects: This reinforces why page speed matters so much (Tier 1). A slow page kills engagement metrics before users even see the content. It also connects to the AI search trend: if Google measures engagement on traditional SERPs to inform AI Overviews, then sites with strong engagement data have an advantage in both channels.
What to do: Improve above-the-fold content to hook users in the first 3 seconds. Add interactive elements (calculators, tools, expandable sections). Reduce bounce rate by matching intent and delivering value immediately.
Topical Authority and Niche Expertise
Strong consensusThe data: Surfer SEO: #1 on-page factor (topical coverage depth). Semrush: semantic relevance dominates their correlation data. Our client data: unique LSI vocabulary r=-0.23, validates ~13% relative weight.
Google's API leak confirmed siteFocusScore, siteRadius, and topPetacatTaxId as real signals measuring how focused a site is on its core topic. Sites that demonstrate deep expertise in a niche outperform generalist sites, even with fewer backlinks. The correlation data backs this: unique LSI vocabulary (a proxy for topical depth) is one of the top 3 correlated on-page factors.
How it connects: This is the data behind the enterprise SEO trend. Large organisations struggle with topical authority because their sites cover too many topics at once. The rising interest in enterprise SEO tools and metrics reflects this: companies are looking for ways to measure and improve topical focus at scale.
What to do: Build topical maps before creating content. Cover topics in depth with supporting pages. Use internal linking to create clear topical clusters. Measure topical coverage against competitors.
Tier 3: Emerging and Divergent
Factors where studies disagree, or where the signal is shifting rapidly. These represent the frontier.
Brand Signals and Branded Search
Divergent (but strongest AI correlation)The data: Ahrefs 75K brand study: brand web mentions 0.664 correlation with AI visibility (3x stronger than backlinks at 0.218). YouTube mentions: 0.737 correlation. Google patent US 9,031,929: brand search ratio as a site quality signal.
This is the most divergent factor in the consensus. Traditional SEO studies underweight brand signals. But Ahrefs' AI visibility data shows brand mentions are the single strongest predictor of AI search citation. Brands mentioned frequently across the web (especially on YouTube) are 6.5x more likely to be cited in AI-generated responses.
How it connects: The divergence between traditional SEO and AI search optimisation. For Google rankings, brand signals are a moderate factor. For AI search visibility (ChatGPT, Perplexity, AI Overviews), brand signals may be the most important factor. This is the core tension practitioners need to navigate in 2026.
What to do: Track branded search volume in GSC. Invest in digital PR that generates brand mentions (not just links). Build YouTube presence. Monitor brand citation frequency in AI search responses.
Schema Markup (Quality Over Quantity)
Moderate consensusThe data: Our client data analysis: significant positive correlation for specific JSON-LD types with 3+ properties. Surfer SEO: too many schema types on a single page correlates negatively with rankings. JSON-LD factors show stronger correlations than RDFa or Microdata.
The nuance matters here. Having schema markup is good. Having specific, detailed JSON-LD with the right @type is better. But over-implementing every possible schema type actually hurts. Surfer's 1M SERP study found negative correlation with schema overuse. Less is more when it is accurate.
How it connects: Schema markup is one of the few signals that works across both traditional search and AI search. Structured data helps Google understand content for rich results and helps LLMs parse content for AI-generated responses. This connects to the generative engine optimisation trend.
What to do: Use the most specific @type for your content (Article, Product, FAQPage, HowTo). Populate 3+ properties beyond the minimum. Validate with Rich Results Test. Remove redundant or inaccurate schema types.
On-Page Factor Breadth
Moderate consensusThe data: Our client data analysis: number of shared on-page factors used r=-0.23. Most successful sites scored high across ALL major factors. No single silver bullet.
Pages that are well-rounded across multiple signal categories (structure, keywords, entities, schema, links, meta) outperform pages that over-index on any single factor. This is the 'structural completeness' signal: Google rewards pages that tick all the boxes, not pages that perfect one box.
How it connects: This validates the structural SEO baseline approach. Sites missing foundational elements lose ground even if they excel in other areas. It also explains why enterprise SEO is trending: large sites need systematic auditing to ensure structural completeness at scale.
What to do: Score each page across 6 categories: structure, keywords, entities, schema, links, meta. Prioritise bringing the weakest category up rather than further optimising the strongest.
Consensus last updated April 2026. Get a full ranking factor audit →
AI Search Pulse
Latest updates from the AI Search Tracker.
Google June 2026 Spam Update Finishes Rolling Out
Change: Google's June 2026 spam update completed on 26 June. Scaled and templated content was hit hardest. Reinforces helpful, first-hand, E-E-A-T-backed content over volume.
SEO impact:
Google Confirms It Ignores llms.txt
Change: Google updated its generative-AI guidance to state that llms.txt files neither help nor hurt rankings and that Search ignores them, alongside other AI-only Markdown files.
SEO impact:
97% of llms.txt Files Receive No Requests
Change: Across 137,000 domains, 28% published an llms.txt file and 97% of those received zero requests in May 2026. 96% of the requests that did occur were from bots, mostly audit and scanner tools.
SEO impact:
Mueller: llms.txt Cannot Help LLMs Differentiate Sites
Change: On Search Off the Record, John Mueller argued self-reported files like llms.txt cannot help an LLM choose one site over another for discovery. He saw a narrow role only once an agent is already on a site.
SEO impact:
Google Publishes AI Optimization Guide for Search
Change: Google published an official AI optimization guide in May 2026. Key positions: schema markup is not required for AI search visibility; llms.txt is not used by Google; writing specifically for AI is unnecessary. Google's stated position: optimising for generative AI search is still just good SEO. The guide effectively validates the existing SEO-first approach while offering no new AI-specific signals.
SEO impact:
Claude Design Launches in Research Preview
Change: Anthropic launched Claude Design on April 17, powered by Claude Opus 4.7. It enables visual creation through conversation -- designs, prototypes, slides, and marketing collateral. Onboarding builds a design system from your codebase and design files, automatically applying brand colours, typography, and components to all projects. Designs can be exported to Canva, PDF, PPTX, or standalone HTML, and handed off directly to Claude Code for implementation.
SEO impact: The Claude Code handoff loop is the most significant feature for SEO practitioners: design an asset in Claude Design, export a handoff bundle, and Claude Code implements it directly. Canva export means OG images, social assets, and hero graphics can be generated and pushed to Canva without leaving the Claude workflow. Available at claude.ai/design for Pro/Max/Team/Enterprise subscribers.
ChatGPT Crawler Now Does 3.6x More Crawl Requests Than Googlebot
Change: A study by AllAI SPA analysed web crawl logs and found ChatGPT-User makes 3.6x more crawl requests than Googlebot across sampled domains. OpenAI's aggressive indexing is driven by both ChatGPT Search (real-time retrieval) and ongoing model training data collection. Many sites are seeing GPTBot in their server logs at volumes that exceed Google's own crawler.
SEO impact: Sites that block GPTBot via robots.txt are likely invisible or under-cited in ChatGPT Search. With ChatGPT running 2 billion daily queries, this is a substantial audience gap. Audit your robots.txt to confirm GPTBot access is allowed for all key pages. Also check that your pages are rendering without JavaScript for AI crawlers that don't execute JS.
99.9% of Informational Queries Now Trigger AI Overviews
Change: Position.digital analysis of 100,000+ queries found AI Overviews now appear on 99.9% of informational keywords, queries where users are seeking knowledge, context, or comparison. The threshold dropped from ~50% in early 2026 to near-universal coverage within weeks of the March 2026 core update completing. Commercial queries (transactional, navigational) still show lower AI Overview rates.
SEO impact: For informational content, the bread and butter of most SEO strategies, traditional organic clicks are now the exception, not the rule. Content that earns AI citation gets a 35% CTR boost (Seer Interactive). Content that doesn't gets punished by CTR dilution. The strategic imperative is clear: optimise for citation, not just position.
March 2026 Core Update Completes Rollout
Change: Google's March 2026 core update, which began on March 27, completed rollout on April 8. This update coincided with AI Overviews now appearing on approximately 50% of US search queries, up from 15-20% earlier in the year. Content cited inside AI Overviews earns roughly 35% more clicks than standard organic positions, but uncited pages see CTR drops of up to 61% on affected queries.
SEO impact: The dual impact is clear: being cited in AI Overviews is now a significant traffic multiplier, while being excluded is an active penalty. Sites need to optimise for both traditional rankings and AI citation simultaneously. This core update appears to further reward content depth, freshness, and E-E-A-T signals.
ChatGPT Ad Platform Hits $100M Annualised Revenue in Two Months
Change: OpenAI's ChatGPT advertising platform reached $100 million in annualised revenue within two months of launch, significantly faster than expected. Ads appear contextually within ChatGPT Search responses, creating a new monetisation layer for AI-assisted search.
SEO impact: ChatGPT Search is now a legitimate advertising channel, not just an organic citation opportunity. For SEO practitioners, this means monitoring ChatGPT as both an organic and paid channel. Brands already tracking utm_source=chatgpt.com traffic should expect the referral mix to shift as paid placements grow alongside organic citations.
Perplexity Pulls All Ads, Pivots to AI Agents
Change: After testing sponsored follow-up questions through 2024-2025, Perplexity removed all advertising from its platform citing user trust concerns. The company pivoted to autonomous AI agents, with products like the Comet AI browser. Revenue surged 50% to $305M ARR driven by subscriptions rather than ads.
SEO impact: Perplexity's ad-free, subscription-first model means organic citation is the only way to appear in Perplexity results. This makes Perplexity the purest test of whether your content earns AI citations on merit. With ~500M monthly queries, it is a significant organic-only AI search channel.
Search Live Expands Globally with Voice and Camera Input
Change: Google expanded Search Live to 200+ countries where AI Mode is available. Users can now use voice and camera input for hands-free troubleshooting and visual search queries. Canvas feature for creative writing and coding also launched in AI Mode across the US.
SEO impact: Multimodal search (voice + camera) means content needs to be optimised for conversational queries and visual recognition, not just typed keywords. Product images, video content, and structured data become more important as visual search grows.
Gmail Launches AI Overviews Powered by Gemini 3
Change: Google brought AI Overviews to Gmail, letting users ask questions about their inbox and get AI-summarised answers. The feature is powered by Gemini 3 and available to Google AI Pro and Ultra subscribers. This marks AI Overviews expanding beyond web search into personal productivity tools.
SEO impact: AI Overviews in Gmail signals Google's strategy to embed AI summarisation everywhere, not just web search. For email marketers, this means email content may be summarised before users read it. Subject lines, preview text, and the first paragraph become even more critical for engagement.
This week is about AI citations and the llms.txt reckoning. Our Bing AI Search report shows the site earning 17,211 grounding citations across 313 queries, with enterprise SEO platform comparisons hitting 85% citation share and Bing-vs-Google making up nearly half of all citations. Meanwhile the industry turned on llms.txt: Google confirmed it ignores the file, Ahrefs found 97% of published llms.txt files got zero requests, and Mueller called the discovery use case a dead end. Add the finished June 2026 spam update and the message is consistent: clicks are flattening, AI citations are the currency, and there is no shortcut file that buys them.