By
Austin Coker
Reading time: 14 min
AI platforms like ChatGPT and Claude name the agencies whose pages match the exact role, niche, and geography of the prompt.
They also favor agencies whose claims about speed, specialization, and fees can be confirmed somewhere other than their own website.
GEO for recruitment agencies is the work of making your firm the one that gets named inside those answers.
This guide covers how it plays out for a staffing, recruitment, or executive search firm selling to hiring managers:
Why this matters now. G2’s March 2026 Answer Economy research surveyed 1,076 B2B software buyers. It found that 51% now start their research in AI tools more often than in Google, and that AI tools are the top influence on which vendors make a shortlist.
That’s software-buyer data, so read it as directional for professional services rather than a measurement of your market.
Gartner’s March 2026 survey of 646 B2B buyers points the same way: 67% prefer to buy without talking to a sales rep, and 45% used AI during a recent purchase. Buyers who want to avoid a sales conversation until the last moment are exactly the ones who let an assistant narrow their options for them.
Before you change a single page, it helps to know what happens in the few seconds between a hiring manager pressing enter and three agency names appearing.
The assistant doesn’t run your prospect’s sentence as a single search. It breaks the prompt into smaller topics, searches each one, and reads what comes back. Google documents this for AI Overviews and AI Mode as “query fan-out”: the system runs many related searches across subtopics and sources before writing its answer.
For a recruitment prompt, those smaller searches are predictable. A question about hiring a creative strategist for a DTC brand splits into searches about:
Your firm doesn’t need to win the original sentence. It needs to be the best answer to several of the smaller searches the sentence turns into. That’s why a single “Services” page almost never does the job.
Each of those searches returns a set of pages. The assistant pulls from the ones that answer the narrow question directly and early.
A page that states who it places, for which kind of company, at what fee structure, and in what timeframe is easy to quote. A page that opens with a paragraph about your commitment to partnership gives the model nothing to quote, so it moves on to a page that does.
The practical consequence is that the assistant isn’t judging your agency. It’s judging whether your page contains a quotable, checkable answer to a specific question. Those are different tests, and agencies with excellent reputations fail the second one all the time.
On client work, we repeatedly see a role-level page on a small site beat a generalist homepage on a large one. Say the prompt is about a TikTok Shop manager. One agency has a page about placing TikTok Shop managers, and a national firm has a page listing eleven practice areas. The narrow page gets named.
This is a pattern we observe rather than a measured rule, and it shifts with the model and the prompt. But it holds often enough to build a strategy on.
It’s also the most useful thing about AI search for a boutique or mid-sized firm. Authority still decides whether your site is in the pool of pages the assistant considers at all. How closely your page matches the prompt decides who gets named, and that’s something a fifteen-person agency can win on.
When an assistant returns a shortlist, it doesn’t just list names. It writes a short label for each one, such as “best for mid-senior roles,” “fastest turnaround,” or “strongest specialist option.” Those labels are built from claims it found on your pages and could confirm elsewhere.
That means the label is partly in your control. Suppose your page says you deliver pre-vetted candidates in about five days for one specific role, and a guest article or client story backs that up. Then “fastest” becomes available as a label for your firm. If your site says nothing concrete, the assistant writes something generic or names someone else.
These are typical prompt patterns rather than findings from a study, but they cover most of what hiring managers type. Each one should lead to a page or FAQ answer you own.
Build your prompt list this way, by role and industry, and you’ll find it’s finite. Most specialist agencies can cover all of their commercial demand with twenty to forty prompts.
The most common reason an agency is invisible in AI search is that its website claims too much ground. A homepage saying you recruit across technology, finance, marketing, operations, and executive leadership gives an assistant no reason to name you for any of them. The model is looking for the closest match to a narrow prompt, and breadth reads as a weak match.
You don’t have to narrow your business to narrow your pages. A generalist firm with real depth in three functions can publish role-level pages for those three and keep the broader capability statement where it belongs.
Most agency sites have a homepage, a sector page or two, an About page, a job board, and a contact form. Nothing on them answers “recruitment agency for a TikTok Shop manager” or “who places senior media buyers for DTC brands.” When the assistant runs its searches, no page on your site competes for the ones that matter, so you’re not in the running.
Hiring managers’ prompts are questions, and most of them are about money, speed, and process. When an agency site answers none of those in plain language, the assistant takes its answers from industry publications, competitor pages, or directories. The agency named in the final answer is the one that supplied the substance.
An assistant is cautious about repeating a strong claim it can find in only one place, especially when that place is the seller’s own website. Agencies with real specialization and no presence elsewhere tend to show up as an “also consider” name rather than the recommendation. Outside confirmation is what turns a claim on your page into a label in the answer.
We’ll run the prompts your buyers use across ChatGPT, Claude, Perplexity, and Google AI Mode, and show you which agencies get named and why.
This is the core production work of GEO for recruitment agencies. It’s closer to sales engineering than to blogging.
Build a dedicated page for each role and industry combination you genuinely want to be known for:
Resist combining four roles into one long page. A combined page weakens the match for every prompt it tries to cover.
Prioritize by commercial value rather than search volume. A role you place at a high fee with a strong win rate deserves a page even when keyword tools show almost no searches. People are already asking AI assistants about it, and keyword data hasn’t caught up with that phrasing yet. We plan and build these pages as part of our GEO for recruiting firms service.
Every role page should follow the same structure, so an assistant can find the same information in the same place across your site:
The role context section is what makes the page worth citing even when the assistant is answering a question that isn’t about hiring an agency at all.
Take the prompt list from the section above and use the questions word for word as your FAQ headings. Answer each in two to four sentences with real numbers. “How much does it cost to hire a creative strategist through an agency” should be followed by your actual fee percentage and what it includes. Vague answers don’t get quoted, and an FAQ written to avoid committing to anything is worse than no FAQ.
Agencies hate publishing fees. That’s understandable, but it’s also the biggest reason a competitor gets named first on prompts about cost.
You don’t need a full rate card. A stated range, a stated fee model, and a stated guarantee are enough to be quotable, and they pre-qualify the buyer before the first call. The same goes for timelines. “Pre-vetted candidates in about five days for this role” is specific enough to become the label the assistant writes next to your name.
Contributed articles and interviews on HR, talent, and recruitment publications do two jobs at once:
Write about the hiring problem you solve rather than about your agency, and use the same specialization language as your role pages.
The more valuable placements are often outside the recruitment press entirely. An ecommerce recruiter earning mentions on ecommerce and marketing publications confirms exactly the claim it needs confirmed: that it understands that industry and hires for it. When an assistant runs searches for a prompt about DTC hiring, those industry sources get considered alongside recruitment sources.
Directories and review profiles aren’t glamorous, but they’re often cited because they’re structured, current, and independent.
Consistency across these sources is what lets a model treat your positioning as fact rather than a marketing line.
The starting point. Constant Hire is a recruitment agency serving DTC and ecommerce brands. When the engagement started, it wasn’t appearing in ChatGPT at all while competitors were being named. For the prompts its buyers used, ChatGPT typically returned a short list of three or four agencies.
What changed. We did three things:
Where ChatGPT ranks Constant Hire now. It names the agency first for:
Look at those labels: five days, DTC-specific, mid-senior. Each reflects the kind of specific, checkable claim the role pages were built to make and the outside placements were built to support. That’s how a claim on your page becomes the assistant’s own description of your firm.
The results.
See how we build role-specific pages and third-party mentions that get recruitment, staffing, and executive search firms recommended in AI search.
Google added an AI Assistant default channel to GA4 on May 13, 2026. Traffic from recognized AI assistants is given the medium “ai-assistant.” OpenAI also confirms that publishers can track ChatGPT referral traffic in analytics tools including Google Analytics.
Treat whatever number you see as a minimum rather than a total. Some of these visits show up as direct traffic because the referrer information gets dropped.
Referral counts aren’t the number that matters to a recruitment business. Fees are.
That’s the only version of this measurement your leadership team will act on.
Pick twenty to forty prompts that reflect your commercial demand, and freeze the wording. Run each one several times, because answers vary between runs. Each month, log:
Over time, that log tells you whether a new page moved you onto the shortlist. The cited pages also show which third-party sources are actually feeding the answer.
None of this works if AI crawlers can’t reach your site.
It’s a ten-minute check of your robots.txt file and meta tags, and it’s worth doing before anything else on this list. We go deeper on the ChatGPT side on our ChatGPT rankings for recruiting firms page.
Candidate-side work covers job posts, job feeds, the job data your ATS sends out, and career pages. Its purpose is to attract applicants.
Client-side GEO targets a different buyer, with different prompts and different pages, and its purpose is winning fee-paying clients. Both are worth doing, but mixing them on the same pages weakens both. Everything in this guide is client-side.
We’ll take the twenty to forty prompts your buyers use, record which agencies AI assistants name and why, and show you which pages produce those answers. You keep the prompt set and the findings either way.
Austin Coker is the CEO and founder of 95 Projects. He has worked in SEO since 2020, when he built and sold an ecommerce brand that grew mainly through search. He founded 95 Projects in 2022 to help SaaS, ecommerce, and B2B service companies show up wherever their buyers search, from Google to ChatGPT and AI Overviews.
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Timelines vary by niche and competition. A well-built role page can start appearing in AI answers faster than it would climb Google’s rankings. Holding the top spot on competitive prompts takes longer, because that usually depends on third-party mentions building up. In the Constant Hire engagement, meaningful ChatGPT-sourced revenue was tracked within four months.
It matters for getting into the pool of pages the assistant considers, because authority affects which pages it retrieves in the first place. It matters much less for which agency gets named, since that decision tends to favor the page that most closely matches the prompt. A specialist page on a modest site often beats a broad page on a strong one.
Yes, and it’s the main opportunity AI search offers boutique firms. National agencies usually publish broad capability pages that match nothing exactly. A small firm can own a role-plus-industry query outright with one well-built page and a handful of outside mentions.
You need pages that answer buyer questions, and those are usually service and role pages rather than blog posts. A blog earns its place when it covers salary data, hiring market conditions, or role-specific guidance that assistants can cite, because that content gets picked up in the searches around a hiring prompt. Weekly general recruitment commentary does very little.
Check the AI Assistant channel in GA4 for referral traffic, then compare it with what buyers tell you, since some assistant traffic shows up as direct. Add an AI option to your intake form, ask on the discovery call, and tag the source in your CRM through to the fee. What buyers tell you is usually the more accurate of the two.
SEO is about ranking a page so a buyer clicks it. GEO is about being the agency an AI assistant names and describes inside its own answer, often without a click. The underlying work overlaps heavily, since both reward clear, specific, well-supported pages. The differences are that GEO targets full questions rather than short keywords, rewards quotable specifics like fees and timelines, and is measured by which agencies get named rather than by ranking positions.
