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Category: AI Marketing

Zero-Click Search in 2026: How to Win the Clicks Left

Reading time: 11 min Table of Content Queries that still send clicks What zero-click search means Zero-click statistics for 2026 Why it keeps increasing Spotting it in Search Console Which queries to fight for Optimizing for zero-click Getting cited by AI What to measure Where paid search fits Zero-click search is the reason your Search Console graph shows a flat impressions line above a clicks line that keeps sinking. A zero-click search is a search where the user gets what they came for on the results page and never visits a site. Search “time in Tokyo” and Google prints the clock at the top of the page, so there’s nothing left to click. SparkToro’s June 2026 study of Similarweb clickstream data covered US desktop and mobile browser searches from January to April 2026. It found that 68.01% of Google searches ended without a click. Below you’ll find: what the current data actually says how to confirm your own exposure in Search Console in about ten minutes which queries are still worth fighting for, and which to concede Which Queries Still Send Clicks Query type Likely SERP outcome Is the click still winnable? What to optimize for Branded (your company name) Knowledge panel, sitelinks, your homepage on top Yes, and it’s the click you’re most likely to keep Accurate entity information, sitelinks that route to money pages, and a branded search trend tracked as a demand metric Navigational (a specific page or login) Direct link, usually resolved on the first result Yes Clear titles, correct canonicals, no near-duplicate pages competing Definitional and “what is” AI Overview or featured snippet answers it in full Rarely Visibility and citation rather than traffic, plus a brand mention inside the answer How-to AI Overview with steps, video carousel, People Also Ask Partly, when the task needs a tool, file, or real walkthrough The part a summary can’t deliver, such as a template, calculator, or annotated screenshots “Best [category] software” AI Overview naming a few vendors, ads, then listicles Yes, because buyers verify before choosing Being named in the summary, plus a page that compares options in real detail Pricing and comparison Mixed, with summaries that are often incomplete or dated Yes Specific, current numbers published on the page, and honest side-by-side comparisons Bottom-funnel commercial (“[service] agency near me,” “hire [service]”) Local pack, ads, then organic Yes, and this is where the click is worth the most Service pages, proof, local signals, and paid coverage when organic is pushed down Vendor selection (“best recruitment agency for fintech”) AI answer naming a short list of firms Yes, for whoever is on the list Third-party mentions, specific niche claims, and pages stating exactly who you serve What Zero-Click Search Means and What It Looks Like on the SERP Today A search ends in zero clicks when the results page satisfies the query by itself. Conversions, currency, sports scores, and store hours have worked this way for years. What changed is that the same treatment now applies to research, product, and comparison questions. Those used to send traffic to publishers and vendors. For a marketing team, the practical definition is narrower. A zero-click search is one where you can rank, get counted for an impression, and receive nothing measurable from it. Where Zero-Click Searches Happen AI Overviews and AI Mode answer at the top of the page. Featured snippets, knowledge panels, and People Also Ask lift text straight out of ranking pages. Local packs resolve phone numbers and directions without a site visit. AI assistants such as ChatGPT, Claude, and Perplexity are themselves the destination. A link is optional rather than the point of the interaction. How Much of Search Is Zero-Click in 2026 The current benchmark comes from SparkToro’s June 2026 analysis of Similarweb clickstream data, covering US browser searches from January to April 2026. In that window: 68.01% of Google searches ended without a click. Searches that produced at least one click fell by 9.51 percentage points, a 22.9% decline. Searches that led to another Google search rose by 7.2 points. A large part of the lost click was absorbed by Google itself rather than by any competitor of yours. Only 0.34% of searches moved into AI Mode during that period. The 2024 comparison figure most people quote, 60.45%, came from a different data panel (Datos). Read the jump as directional rather than as a precise change. The study also covers browser searches only and excludes the Google app. Pew Research Center studied the behavior itself rather than the totals. It used browsing data from 900 US adults, covering 68,879 searches in March 2025, and found: Clicks on results: users clicked a traditional search result in 8% of visits where an AI summary appeared, compared with 15% where none appeared. Clicks inside the summary: users clicked a link inside the AI summary in just 1% of visits. Ended sessions: users ended their browsing session on 26% of pages with a summary, against 16% of pages without one. The caveat is scale: a single month, a single panel, and 900 adults. What Google Says About Click Volume On August 6, 2025, Google’s head of Search, Liz Reid, published a post making two claims: Total organic click volume from Google Search to websites has been relatively stable year over year. Google is sending slightly more “quality clicks,” meaning visits where the user doesn’t immediately click back to the results. Google also disputed the methods behind third-party click studies. It did not publish its own figures, so the claim can’t be checked independently. Both pictures can be true at once. Stable totals across the whole web are compatible with many individual sites losing a significant share of their clicks. The losses concentrate where AI answers are most complete: Informational and definitional pages take the hit first. Commercial and vendor-selection pages hold up longer. Your own Search Console data is the only thing that tells you which side of that split your site sits on. Why Zero-Click Searches Keep Increasing

How to Get Clients for a Recruitment Agency (September 2026)

Reading time: 14 min Table of Content Methods compared Why outbound is getting harder Why inbound compounds Outbound without burnout Referrals and expansion Getting clients from SEO Getting named by AI assistants Google Ads for recruiters Partnerships Splitting outbound and inbound The American Staffing Association counts around 27,000 staffing and recruiting companies in the US. Many of them are chasing the same hiring managers you are. That is the real problem behind the question of how to get clients for a recruitment agency. There’s no shortage of companies hiring. The problem is a queue of firms saying the same thing to the same buyer in the same week. The methods that produce signed mandates in 2026 fall into three groups: Signal-based outbound for immediate pipeline Referrals and expansion inside accounts you already serve Search visibility across Google and AI assistants, the part of the mix that keeps producing after the work is done This article compares every client acquisition method recruitment agencies actually use. It shows why outbound response rates have fallen and what the data says about it, and explains how buyers now shortlist vendors before they speak to one. It then walks through how to get clients from SEO, from AI search, and from Google Ads. It ends with a plan for splitting effort between outbound and inbound, plus answers to the questions agency owners ask most. Client Acquisition Methods for Recruitment Agencies Compared Method Time to first client Cost per client over time Scales with Compounds or resets? Cold email Weeks Rises as reply rates fall and list quality degrades Send volume, domains, inbox infrastructure Resets the month you stop LinkedIn outreach Weeks Rises as connection limits and message fatigue bite Seat count and manual sender time Resets, with a small residual from profile visibility Cold calling Days to weeks Flat to rising, tied directly to headcount Hours on the phone Resets daily Hiring-signal prospecting Weeks Lower than untargeted outbound, but still recurring Data coverage and researcher time Resets, though your playbook improves Referrals and client expansion Days Lowest of any method Delivery quality and placements made Compounds slowly, capped by your client base SEO Months Falls as pages mature and rankings hold Ranking pages and topical depth Compounds GEO (AI search visibility) Months Falls as citations and third-party mentions accumulate Mentions, reviews, clearly stated specialization Compounds PPC (Google Ads) Days Flat, tied to auction prices and competition Budget Resets when budget stops, but the data carries over Partnerships Months Low once established Number of partners and their client volume Compounds while the relationship lasts Why Outbound Keeps Getting Harder for Recruitment Agencies Outbound still works. It just buys less than it used to for the same money and effort. Buyers are pushing back on it directly. In a Gartner survey of 632 B2B buyers, 73% said they actively avoid suppliers who send irrelevant outreach, and 61% said they would prefer to buy without dealing with a sales rep at all. Gartner’s follow-up survey a year later found that preference had climbed to 67%, with 45% of buyers using AI during a recent purchase. The technical side got stricter too: Google: since February 2024, Gmail has required senders of 5,000 or more messages a day to authenticate their email, avoid unsolicited mail, and make unsubscribing easy. Starting November 2025, Gmail ramped up enforcement, and non-compliant messages now face temporary and permanent rejections. Microsoft: since May 2025, Outlook.com requires SPF, DKIM, and DMARC for domains sending over 5,000 emails a day, and rejects messages that fail. Agencies sending at volume from cheap domains without authentication aren’t just getting worse results. Their emails aren’t being delivered at all. Then there is the part no survey fully captures. Hiring managers and HR leaders now receive so much AI-assisted recruiter outreach that they delete it on sight. When every message opens with a variation of the same comment about their funding round or open roles, personalization stops meaning anything. The economics matter more than any single number. Outbound produces exactly as much as you put into it this month and nothing more. Stop sending on the first of the month and the pipeline goes quiet by the end of it. Nothing builds up except damage to your domain’s reputation and a contact list that has already heard from you. Why Inbound Compounds for Recruitment Agencies The decisive shift is that buyers now build their shortlist before they speak to anyone. 6sense surveyed more than 4,000 B2B buyers for its 2025 Buyer Experience Report. It found that: 94% of buying groups rank a preferred vendor before contacting any seller. The pre-contact favorite goes on to win roughly 80% of deals. Buyers first engage sellers about 60% of the way through their journey. By the time an HR director takes your call, most of the decision has already happened somewhere you were either present or absent. Where that research happens has moved. G2’s Answer Economy research is based on a March 2026 survey of 1,076 B2B software buyers. It found that: 51% now start their research with an AI chatbot more often than with Google, up from 29% in April 2025. AI chatbots are the single biggest source influencing shortlists. 69% of buyers ended up choosing a different vendor than they originally had in mind, after chatbot guidance. This is data on software buyers, so treat it as directional rather than exact for hiring managers buying agency services. The direction is clear, though. Compounding is the whole argument for inbound: A page that ranks for “fintech recruitment agency” keeps producing inquiries in month nine without another hour of work. A case study cited by an AI assistant keeps being cited. Every new page adds to the base the previous pages built, which is why cost per client won falls over time instead of climbing. Outbound gives you a month of output for a month of work. Inbound gives you an asset. Is your agency on the shortlist before the first call? We’ll

What is Query Fan-Out? How to Get It Right

Reading time: 10 min Table of Content Query variant types How query fan-out works What Google has confirmed Does ChatGPT use it? Why it matters for SEO and GEO Don’t build a page per query Finding fan-out queries Optimizing for query fan-out Measuring AI visibility Query fan-out (also written “query fan out”) is the technique AI search systems use to break a single prompt into multiple related searches, run them at the same time, and build one answer from the results. Google confirmed the name and the mechanism in its May 2025 AI Mode announcement, which describes AI Mode splitting a question into subtopics and issuing many queries simultaneously. Most advice written since then treats every generated sub-query as a new keyword to build a page for. That is where it goes wrong. This post covers: what query fan-out actually is the query variant types described in Google’s patent application what Google has confirmed versus what is inference whether ChatGPT and Perplexity do something similar how to structure content so it gets retrieved and cited even though the sub-queries change on every run Every figure below links to its source, with the sample size and date attached. What Query Variants Does Google’s Fan-Out Patent Describe? Google’s patent application “Search with stateful chat” (US20240289407A1) describes a system that generates variants of a user’s query and runs them against a search backend. It is a patent application, not a confirmed description of how the live product behaves. Treat it as a blueprint for the category, not proof of what AI Mode did this morning. That said, the variant types it describes match what practitioners see in fan-out logs. Here is each type applied to one example prompt: “best CRM for a 20-person B2B SaaS sales team.” Variant type What it does Example sub-query Equivalent Same meaning, different wording “top CRM software for small B2B SaaS sales teams” Broader Zooms out to the parent topic “best CRM software 2026” Narrower Adds a constraint that shrinks the result set “CRM with built-in email sequences for 20 seats” Related Covers an adjacent topic the answer needs “CRM implementation time for small sales teams” Comparative Puts named options against each other “HubSpot vs Pipedrive vs Attio for B2B SaaS” Personalized Applies known context such as location, history, or tools “CRM that integrates with Slack and Gmail” Implicit Answers something the user needed but never typed “CRM pricing per user for 20 users” Parallel Explores a sibling topic at the same level “best sales engagement platform for B2B SaaS” The implicit and comparative types decide most B2B outcomes. A buyer asking for the “best CRM” never types “annual contract minimum” or “does it support multi-currency invoicing.” Yet those are exactly the sub-queries that determine which vendors survive the shortlist the model builds. How Does Query Fan-Out Work? Three things happen in order: Decomposition. The model reads the prompt and generates sub-queries covering the subtopics, constraints, and comparisons it judges necessary for a good answer. Parallel retrieval. Those sub-queries run against a search index and other data sources at the same time, not one after another. Synthesis. The model reads the returned passages, resolves conflicts between them, writes a single answer, and links to the sources it leaned on. The scale depends on the feature. Google’s I/O 2025 announcement describes Deep Search as the same fan-out technique taken further: it can issue hundreds of searches to build a fully cited report. A standard AI Overview sits at the other end of the range. The practical consequence is that you are no longer competing for one ranking position. You are competing on how well you cover a cloud of related searches, several of which you will never see in any keyword tool. What Has Google Actually Confirmed About Query Fan-Out? More than most people assume, and it is all in official documentation. Google’s Search Central guide, AI features and your website, says three things: Both AI Overviews and AI Mode may use a query fan-out technique, issuing multiple related searches across subtopics and data sources. This surfaces a broader, more varied set of supporting links than a classic web search. AI Mode and AI Overviews may use different models, so the links they show for the same question can differ. On eligibility, the documentation is unusually plain. To appear in these features, your pages need to be indexed and eligible to show in Search with a snippet, and there are no additional technical requirements. There is no fan-out schema, no special markup, and no separate opt-in. Google’s product team added detail in July 2025. As reported by Search Engine Journal, Google VP of Product Robby Stein said: AI Mode uses Google Search as a backend tool that runs multiple queries. Fan-out can cover topics the user never mentioned. The technique is active in AI Mode, Deep Search, and some AI Overview experiences. Its sources include web results and real-time systems like the Shopping Graph. Mike King of iPullRank told Digiday in June 2025 that fan-out targets the “subintents” behind a query rather than the query itself. Anything beyond that, including the exact number of sub-queries a given prompt triggers, is measurement and inference, not confirmation. Does ChatGPT Use Query Fan-Out? ChatGPT does something functionally similar when it searches the web, even though “query fan-out” is Google’s term. The clearest public measurement is MJ Cachón’s study of brand prompts in ChatGPT. It analyzed 1,797 sub-queries and found that a single run averages fewer than three sub-queries. Running the same prompt four times raises the number of distinct sub-queries to about 10.3. That gap is the finding that matters: one run tells you very little about which sub-queries a prompt can generate. Perplexity and Claude also break prompts down and search when connected to the web. Be careful, though, about describing how they do it with the confidence Google’s documentation allows for AI Mode. Neither has published a comparable description of its process, and stating one as fact is how

ChatGPT Sponsored Agents Ads Explained

Reading time: 8 min Table of Content What is a ChatGPT Sponsored Agent? How is this different from ChatGPT ads? What does the Ads Manager plugin change about campaign setup? Which businesses are the best fit for Sponsored Agents? How big is ChatGPT Ads right now? Can you get access to ChatGPT Sponsored Agents ads right now? OpenAI announced ChatGPT Sponsored Agents ads on September 16, 2026, and the format is different enough from everything else in your media plan that it deserves a real look. ChatGPT Sponsored Agents ads let someone click an ad inside ChatGPT and land in a labeled conversation with an AI agent the business sponsors, not with ChatGPT itself. Right now it is a limited alpha with a small group of US advertisers, so nobody outside that group is buying it this quarter. Below: what the format actually does, how it compares to the ChatGPT ad placements that opened to US advertisers in February 2026 and to Google Search ads, what else shipped alongside it, and what you can control before access widens. What is a ChatGPT Sponsored Agent? A Sponsored Agent is a branded conversation that starts after a click. Someone sees an ad in ChatGPT, clicks it, and instead of being sent straight to a landing page they open a labeled exchange with an agent the advertiser sponsors. They can ask follow-up questions, get answers scoped to that business, and then follow a link through to the advertiser’s site. Two details matter for how you plan around it. First, the conversation is clearly distinct from ChatGPT’s own answers, so the user knows they are talking to a sponsored experience. Second, it sits separate from the original conversation the person was having, which means it behaves more like a destination you bought than an interruption inside an organic answer. OpenAI’s help center article on Sponsored Agents confirms the current scope. In practice, the click is no longer the end of the funnel. The click is the start of a qualification conversation you are paying for, and the quality of that conversation depends on what the agent knows about your products, pricing, and eligibility rules. Want to know where your brand shows up in the buyer’s research? We will check whether AI chatbots, review sites, and comparison pages surface you at the moment buyers build their shortlist, and where you are invisible. Get a Free Visibility Audit How is this different from ChatGPT ads? The placements that opened to US advertisers in February 2026, with early partners including Best Buy and Williams-Sonoma, work the way most paid placements work. An ad appears in relevant moments inside ChatGPT, the user clicks, and the user goes to your site. The interaction ends at the handoff. Sponsored Agents keep the user inside ChatGPT for another step. That changes what “good creative” means. Your headline still has to earn the click, but the sponsored conversation has to hold up under open-ended questions you cannot fully script. Product data quality, not just ad copy quality, becomes a performance lever. Sponsored Agents vs. existing ChatGPT ads vs. Google Search ads Factor Sponsored Agents Standard ChatGPT Ads Google Search Ads Where it appears Inside ChatGPT, as a labeled conversation opened after an ad click Inside ChatGPT, alongside relevant conversations On the search results page What triggers it Conversational relevance, then the user choosing to start the chat Conversational relevance Keyword and query matching What happens after the click A back-and-forth with your agent, then a link to your site The user lands on your site The user lands on your site What you control The ad and the knowledge behind the agent; the conversation itself is dynamic Copy and imagery you approve, plus optional AI text adaptation Keywords, bids, assets, landing pages Where performance is won or lost Accuracy and depth of your product information Relevance and creative Keyword targeting, ad rank, landing page What does the Ads Manager plugin change about campaign setup? OpenAI also shipped an Ads Manager plugin that lives inside ChatGPT. You can create, update, and analyze campaigns through natural language in the same interface, and generate a campaign from a website URL or a written brief. For a small in-house team this removes a real amount of setup friction. The tradeoff is that the campaign scaffolding gets built from whatever your site says about you. If your product pages are thin or your positioning is inconsistent across the site, the generated campaign inherits that. Clean up the source before you let anything build from it. How do AI creative suggestions and AI text customization work? Two separate things were announced, and they behave differently. 1. AI creative suggestions produce copy and imagery based on your landing page and campaign objective. You review and edit before anything gets added, so this is an assist on production speed rather than an automated system running unattended. 2. AI text customization is opt-in and works at serve time. It adapts headlines and descriptions to the context of the conversation the user is having, and auto-translates into the user’s preferred language. That second part is the underrated piece for anyone already selling across ChatGPT Ads markets, because it collapses a localization workflow you would otherwise resource manually. Which businesses are the best fit for Sponsored Agents? The format rewards products where buyers have questions before they buy. Strong fits include: High-consideration ecommerce. Furniture, electronics, and anything with sizing, compatibility, or care questions. B2B SaaS. Buyers want to know about integrations, pricing tiers, security, and whether the tool fits their use case before booking a demo. Services with eligibility rules. Recruitment, financial, and professional services where the answer is “it depends” until a few questions are asked. It’s a weaker fit for impulse purchases and low-cost commodity products, where a conversation adds friction rather than confidence. Want to get onto the Day-One shortlist? See how we put brands in front of buyers earlier, in AI search, reviews, and the comparison pages that