October’s State of Search & AI covers low content marketing results, Google’s AI reporting flaws, and what 131 experts say about core ranking factors.
October’s State of Search & AI covers low content marketing results, Google’s AI reporting flaws, and what 131 experts say about core ranking factors.
October’s signals show that core content and search fundamentals still determine results. Content marketing performance is hitting a multi-year low due to the abandonment of core disciplines rather than AI adoption. Meanwhile, a survey of 131 SEO experts confirms backlinks and relevance remain top ranking factors. While tools and platforms evolve rapidly, the underlying strategy remains unchanged.
September drew a clear line between two different AI visibility problems. Citation — whether a model pulls from your pages — is shaped by technical factors like crawlability, content structure, and getting substantive copy as close to the top of the page as possible. Recommendation — whether a model names your brand when asked what to choose — is driven by how thoroughly your brand is woven into the web content the model was trained on. Those are two distinct problems, and most AI search strategies are focused on the first while underinvesting in the second.
October reinforces the discipline side of that equation: the content practices most likely to earn citations and recommendations are the same ones most likely to produce measurable results across the board.
This month covers a significant content marketing performance study, important caveats about AI search reporting accuracy, new audience data on the Google-versus-AI question, a meaningful update to Google Business Profiles, and early signs that Google is considering compensating content for its role in shaping AI answers.
Just 14% of marketers reported strong results from their content this year, the lowest figure in over a decade — even as AI adoption in content production reached 92%. The more telling finding is that the teams that still reported strong results continued to conduct keyword research, collaborate with external subject-matter experts, and formally edit content before publication. Those are exactly the practices that fell out of fashion fastest as production speed became the priority.
What this means for marketers: The performance decline tracks with the erosion of content discipline, not with AI use itself. AI tools can accelerate production without degrading quality, but only when the underlying practices (research, expertise, editing) stay in place.
Google’s John Mueller confirmed that the position data in Search Console’s AI Overviews and AI Mode reports reflects where the AI block sits on the page as a whole — not where a specific link appears within that block. The report is also drawn from a filtered subset of existing search performance data, not a separate data layer. This implies that small movements in these numbers aren’t meaningful, and the percentages shouldn’t be read as precise measurements.
What this means for marketers: Treat AI visibility data from Search Console — and from third-party citation tools, which face similar limitations — as a directional signal. It’s useful for spotting trends over time, but not for drawing conclusions from individual data points or week-over-week swings.
New audience data found that about 95% of ChatGPT users also appear in Google’s audience, and that overlap has stayed stable even as AI platform visits grew 70% year-over-year. The behavior pattern highlights how AI tools joined Google in the research stack without replacing it.
What has shifted is where the click lands. Google can hold the same user and the same query and still lose the click to a zero-click AI answer on either platform.
What this means for marketers: Falling organic click volume isn’t evidence of an audience moving away from Google. The demand is still there; the click behavior is what’s changing. That distinction matters for how the performance conversation gets framed internally, and it reinforces the case for tracking branded demand and direct traffic alongside organic clicks to get an accurate picture of discovery health.
A new “Collected Info” tab in Google Business Profiles surfaces what Google’s automated assistant gathered through calls, texts, or WhatsApp outreach to businesses — and lets owners delete anything inaccurate. Until now, Google’s automated outreach could quietly update a listing’s details without a human ever reviewing or approving the change. This closes a gap that has been a real operational risk for multi-location brands.
What this means for marketers: This warrants a one-time audit across managed listings to check what’s been collected and whether any of it is inaccurate. Going forward, including a Collected Info check in the regular GBP audit cadence is worth doing.
An invite-only pilot called “AI Contribution” inside Search Console will pay a limited group of publishers when their content meaningfully shapes an answer in Gemini, AI Overviews, or AI Mode. Participation is currently restricted, but it’s the first explicit signal that Google is considering “shaping an AI answer” as a distinct, compensable outcome, separate from the referral click model that has defined search monetization for 25 years.
What this means for marketers: Nothing to act on yet, but it’s a meaningful signal about where Google sees the relationship between content and AI answers heading. If the pilot expands, it would create a new incentive structure around producing content that informs AI responses rather than content optimized purely for clicks.
A survey of 131 SEO professionals, updated specifically to account for the AI-search era, placed relevance at the top of the list of Google ranking factors. Backlinks were a close second, named by more than half of respondents as one of the three most important signals. The same fundamentals that topped the list before AI Mode existed still top it now. Nothing in the current AI search environment has displaced the core signals Google has relied on for years.
What this means for marketers: Link-building strategy doesn’t need to be reconsidered in light of AI search. The signals that earn organic rankings also contribute to the kind of web authority that influences AI recommendations. Sustained investment in relevance, quality content, and backlink acquisition remains the right call.
October is evidence against the belief that AI search requires a fundamentally different playbook. The content practices most linked to strong results — keyword research, expert input, careful editing — are the same ones that have always separated effective content from filler. The ranking signals SEO professionals trust most — relevance and backlinks — haven’t been displaced by AI Mode. And the audience data shows users haven’t abandoned Google; they’ve added AI tools alongside it.
Heading into Q4, that means:
The platforms are changing. The practices that make content and search strategy work are not. That’s the clearest signal October has to offer.
October’s State of Search & AI covers low content marketing results, Google’s AI reporting flaws, and what 131 experts say about core ranking factors.
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