GEO for Government
When a resident asks an AI assistant about your program, make sure it answers with your words.
US searches now show an AI Overview
residents use AI to find a government service
average ChatGPT question, vs. about 4 on Google
AI Overviews now appear on roughly half of US searches. ChatGPT, Gemini, Copilot, and Perplexity answer questions about benefits, permits, deadlines, and fees by reading the web and handing back a paragraph, often with no link at all. GNW makes sure that paragraph is built from your pages, says what your pages say, and sends residents to the right place.
The shift
Residents are asking. Someone is answering.
More than one in ten residents now use an AI tool to find the government service they need, and among Gen Z it’s more than one in five. The questions are longer and more specific than search ever was. The average Google query runs about four words; the average ChatGPT question runs about 23.
An assistant doesn’t rank pages. It assembles an answer from whatever it can read and trust. If your hours live in an image, your eligibility rules in a scanned PDF, and your fee schedule in three places that disagree, the answer it assembles will be confidently wrong. Or it will come from an aggregator, an advocacy site, or a different state entirely.
Traditional search traffic is expected to fall by half within two years. Ranking first on a page fewer people see doesn’t help the resident with a deadline tomorrow.
What residents used to type
What they type now
~23 words · one assembled answer
Why GNW
A wrong answer has a price, even when nobody sees it.
Revenue you're counting on
An airport wants travelers in its own garages, not a private lot down the road. A transit authority wants riders buying the right fare. A county wants permits and payments coming through its portal, not a third-party site that charges a convenience fee and sends you the paperwork late. When the AI answer names someone else, the money goes with it.
Programs nobody uses
Utilization depends on people knowing a program exists and understanding whether they qualify. When an assistant describes the wrong income limit, the old application window, or a form that was retired two years ago, eligible residents don’t apply. The program looks like it lacks demand when what it lacks is an accurate answer.
Trust, when it matters most
What GNW does
We fix what the assistants read, then keep watching what they say.
We audit the way a resident would.
We take the questions your front desk, 311 line, and call center answer most, then ask them in ChatGPT, Gemini, Copilot, Perplexity, and Google’s AI Overviews, from a clean browser, in the plain language a resident uses. For each one we record who got cited, whether the steps, deadlines, and fees were correct, and whether the resident was sent to your service or somewhere else.
We build that into a tracked set of around a hundred prompts, categorized by program and intent, so the data coming back is something you can act on rather than a pile of screenshots. Alongside it we pull your analytics, Search Console, and Bing Webmaster data and crawl the site for the technical problems that stop machines reading it: content rendered in JavaScript, facts locked in images, pages with no clear structure.
You get a scored list of your highest-traffic services, ranked by how badly the AI is currently representing them, and the fixes that will reach the most residents first.
We fix the content, not the AI.
Most wrong answers trace back to the same handful of causes, and we work through them page by page:
One source per fact
Answer first
One source per fact
Answer first
GovernmentService, FAQPage, OpeningHoursSpecification, and ContactPoint so machines can read what each fact is without guessing. Trust signals machines can measure
Consistency off your site
We monitor what the assistants are telling residents.
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We prepare your content for your own AI.
The chatbot your agency is building or buying reads the same pages ChatGPT does. Contradictory pages produce contradictory answers in both. Content we’ve restructured for public assistants is retrieval-ready for yours.
We report in your numbers.
Citation share on your top service pages against completions, enrollments, and call volume for those same services. Not pageviews. The report your digital team can bring to a budget hearing.
You start ahead.
For any question that touches a regulation, a benefit, a fee, or a public record, the major assistants already prefer to cite a government source over a commercial one. Private companies spend real money trying to get into answers you’re entitled to by default. The job on your side is narrower: make sure the page exists, says one thing, and can be read by a machine. That’s most of the work, and it’s the work we do.
Why GNW
A wrong answer has a price, even when nobody sees it.
It starts with an audit.
Then we rebuild.
Then we stay on it.
Most agencies see citation changes within weeks of the rebuild going live, because the assistants re-read .gov pages often and already treat them as authoritative. The work is making that authority legible.
Find out what AI assistants say about your programs today.
Who this is for
Built for public agencies where a wrong answer costs residents time or money.
- State agencies running benefits, licensing, tax, or health programs where a wrong answer costs a resident money or time
- Cities and counties pushing transactions online and trying to bring call volume down
- Airports, transit authorities, ports, and utilities whose revenue depends on residents choosing the public option over a private one
- Federal offices and bureaus with public-facing guidance spread across program pages and PDFs
- Digital service teams already under WCAG 2.1 AA and plain-language deadlines who need the same effort to count twice
Procurement-ready
See what residents are being told today
The audit shows you, in a week, what the major AI assistants say about your programs, who they’re citing, and where they’re wrong. From there, we fix it and keep it fixed.