Published: July 27, 2026
Last updated: July 27, 2026
Organic search traffic is disappearing. SparkToro and Similarweb’s most recent clickstream study found 68.01% of U.S. Google searches ended without a click in the first four months of 2026—the fastest two-year acceleration on record. This trend is driven largely by Google AI Overviews, featured snippets, and other SERP features answering users’ questions directly, eliminating the need to visit websites for more information.
There’s also causal data behind that number. When OpenAI widened ChatGPT Search access in 2024–2025, Bocconi University researchers found traditional search queries dropped 9.4% within weeks, and nearly doubled to 17% within 20 weeks. Informational, research-style queries—the kind a B2B buyer runs during early discovery—took the biggest hit. And ChatGPT is just one part of the shift; AI platforms like Gemini, Claude, and Perplexity are pulling the same queries away from a traditional results page.
That has huge implications for the B2B tech marketers running search engine optimization (SEO), generative engine optimization (GEO) and answer engine optimization (AEO) programs. If the organic traffic, absolute click-throughs, and click-through rate (CTR) that used to prove your content was working is going away, what key performance indicators should you measure instead?
Fewer, warmer visits
The thing to remember is, zero click doesn’t mean zero traffic. Total traffic to your site will almost certainly drop, but it will largely be top-of-funnel visitors who were never going to convert anyway. Interested buyers will still end up on your site. They’ll just get there later in their buying journey, through different channels, and in lower volumes.
Case in point: Across three B2B tech buyer surveys we ran this year, respondents told us vendor websites are the top (or near-top) place buyers go to check what AI tells them about that vendor.
- 93% of martech buyers check vendors’ website to verify AI output—their top method
- 80% of fintech buyers do the same—also their top method
- 60% of enterprise AI buyers check vendor websites too—just behind peer conversations as their top method
What this tells us is that buyers are landing on vendor sites with real commercial intent and with an AI-informed opinion that they are looking to challenge or confirm.
So what should you actually measure?
Generative search is and will continue siphoning away unqualified, top-of-funnel traffic. But that traffic will only be replaced by a smaller volume of qualified visitors—if your brand is showing up in AI answers and getting recommended when it matters.
Some of the KPIs that tell you whether that’s happening are upstream levers you can influence directly; others are downstream outcomes that tell you whether your efforts are actually working. Start tracking both.
Upstream AEO/GEO metrics
- Keyword rankings
This one might seem like a relic of the old model, but there it correlates with your AI visibility. That’s because, when someone prompts an AI assistant, the model often runs a live web search, breaking that prompt into several related sub-queries (called a “query fan-out”) and pulling organic results to inform its answer. Query fan-outs fire disproportionately for the prompts that make up vendor research: Recency prompts trigger it 81% of the time, ranking prompts 67%, comparison prompts 51%. And once it fires, rank matters. Claude’s cited sources overlap with Google’s top 10 results 64% of the time, for example. - Backlinks and referring domains. Backlinks do double duty here. They’re a classic factor in improving keyword rankings, but they’re also a separate signal in their own right. A strong backlink profile usually means your brand is being written about and referenced across the web, not just linked to, and that footprint is part of what feeds AI visibility.
- Third-party mentions across the web. Not every mention comes with a link. Press coverage, G2 and Capterra reviews, forum threads, and community Slack conversations that get indexed also influence AI answers. Track volume and sentiment of unlinked brand mentions the way you’d track backlinks.
- AI visibility (brand mentions, citation share, and AI share of voice [SOV] on a set of curated prompts)
This is the output side of the metrics above, and it’s what AEO tools show you by default. It tells you whether you’re in the AI conversation at all. What it doesn’t tell you is whether that visibility is doing anything downstream or resulting in revenue impact. For that, you need the rest of the list.
Downstream AEO/GEO metrics
- Direct traffic
Watch for growth in web visitors typing your website address straight into a browser instead of arriving via a search click or an AI answer. Google Search Console will show you this split. It’s one of the more reliable signals that AI exposure is building awareness and branded demand on its own, independent of any click. - Branded search volume
Similarly, look for branded search lift—that is, a rise in traditional search queries that include your company, product, or brand name. Like direct traffic, it’s a sign that demand is growing. - Bounce rate
As unqualified top-of-funnel traffic falls away, the visitors left in the mix are people who came with a specific reason to be there. Aggregate bounce rate should improve as a result, simply because the casual, one-and-done browsing traffic that used to inflate it is gone. - Engagement on “verification” pages
Track visits and engagement on the pages buyers need when they’re checking AI’s recommendations and conducting middle- and bottom-funnel vendor research, like compliance and integration pages, case studies, and pricing. Even as total website traffic falls, traffic to these pages may grow. - Key event rate
Compare sitewide and page-specific conversion rates on key events—like demo requests and contact form fills—against your historical baseline, because fewer, more qualified visitors should convert at a higher rate. A climbing key event rate alongside declining raw traffic is good evidence that the visitors you do have are warmer than the ones you lost. - Sales-reported source
Add “AI tool” as an option to a how-did-you-hear-about-us survey, or have reps ask during discovery calls. It’s the clearest attribution signal you can track. - Deal velocity and lead temperature
Look for shorter sales cycles and warmer first conversations. If AI already did the early comparison work, the leads reaching your sales team should arrive pre-qualified and further along in their buying journey.
Of course, most of this is correlational rather than a clean attribution model. You want to see your AI visibility numbers move first, then check whether things like branded search, verification-page traffic, or deal velocity move with it.
If you have the tooling and the internal appetite for it, multi-touch attribution or assisted-conversion reporting can take this a step further, connecting an early AI-influenced touchpoint to a deal that closes months later. But that’s a heavier lift than most B2B teams need to start with, and it’s still modeling a correlation, just with more infrastructure behind it. Don’t let the absence of that setup stop you from tracking the simpler signals above.
About the author
Caitlin Hartney is Director of Strategy at Block Club, where she brings editorial rigor to a discipline that too often runs on instinct. With a background in journalism, and training from NYU and the University at Buffalo, she treats brand strategy the way a good editor treats a story: find the thing that’s true, connect it to your audience, and say it in a way no one can ignore.
She has led positioning and messaging for companies navigating complex, trust-driven categories and built verbal identity and content strategy for leading B2B tech and SaaS brands like Plaid, Alloy, and Argyle. Across her work, she helps brands establish a point of view only they can own, then builds the language and editorial system to bring it to market. Lately that’s meant going deep on AI search optimization (AIO/AEO/GEO) to influence AI models’ perception of her clients, so they show up when buyers ask for vendor recommendations.
Caitlin believes that B2B tech brands are facing a differentiation deficit as AI accelerates product and brand parity. The ones that will come out on top will have something worth saying and the means to say it distinctly. She writes regularly on B2B content strategy, fintech and SaaS branding, and where AI search is headed.