// case study

Second-largest AI footprint across HHS — with the smallest organic web presence.

A federal health agency engineered to outperform its sister agencies on AI citations despite the smallest traditional web footprint. The result of a deliberate Trust But Verify strategy executed through a GEO Flywheel calibrated for how LLMs actually learn.

FEDERAL HEALTH AGENCY2025–2026AEO + GEOMULTI-YEAR ENGAGEMENTSOURCE: AHREFS · BRAND24
// the results

The numbers behind a category-leading AI footprint.

// AI CITATIONS / MONTH
0
across major AI surfaces — AI Overviews, ChatGPT, Perplexity, Gemini, Copilot
// VS PEER AGENCY A
+0%
despite peer having ~16× more organic traffic
// VS PEER AGENCY B
0×
more than double peer agency on AI citations
// SHARE OF DEPT.
~0%
~43% on ChatGPT specifically — the largest LLM surface
// THE CHALLENGE

Smallest footprint. Same mission.

The agency had the smallest traditional digital footprint of its four sister agencies — a function of legacy web architecture and a constrained promotional budget. On classical SEO, the dashboards showed a fourth-place finish. On the surface that actually shapes the next decade of clinical decision-making — the LLMs and AI answer engines that providers, patients, payors, and policymakers now reach for first — the agency's research was barely visible. The mission required a different definition of "discoverable."

// THE APPROACH

Re-engineer for the surface where the answer is actually decided.

We mapped the agency's audiences across the Trust But Verify continuum — Pursuers, Providers, Patients & Families, Payors, Policy Makers — and rebuilt the production model around the GEO Flywheel. Short, FAQ-shaped pages. Repeating video. Public-social production at the shapes models prefer. Stakeholder re-share loops. Cross-domain citation seeding.

"The dashboards said fourth place. The model said second. We optimized for the model — because that's where the buyer actually was."

Implementation looked like: content rebuilt and republished in the format answer engines actually retrieve; a video program engineered to give models multiple bites of the apple; a social rhythm built around the public channels LLMs read most; an amplification loop that turned every stakeholder share into a referring backlink the model could see.

// WHAT WE SHIPPED

Strategy plus every asset underneath it.

Macro-level ideation followed by the line-by-line shipping that most consultancies hand off to a third vendor. End-to-end delivery, in-house, on the same timeline.

  • Trust But Verify continuum & comms architecture
  • GEO Flywheel operating model & cadence
  • FAQ-shaped page rebuild for AEO retrieval
  • Multi-format video program (long, short, vertical)
  • Social media end-to-end across owned channels
  • Newsletter + listserv re-architecture
  • Stakeholder re-share & coalition mapping
  • ASPA / Releases process navigation
  • Brand & graphic systems for outbound assets
  • Editorial & QA for every public-facing page
  • AHRQ.gov-class web architecture support
  • Performance & AI-citation tracking dashboard
// THE IMPACT

Stewardship into outcome.

The numbers are the headline. The mission underneath is the point. Federal research dollars only translate into safer care if the research surfaces in the tools providers and patients actually use. The agency's footprint on the AI frontier is now disproportionate to its budget — which is exactly what stewardship is supposed to look like.

// FOR PROVIDERS

In the bedside copilot.

Agency research surfaces directly in the AI tools clinicians use at the point of care.

// FOR PATIENTS

In the answer they trust.

Validated, evidence-based content reaches the answers patients see when they ask an LLM first.

// FOR TAXPAYERS

Reports that don't sit on shelves.

Research investments translate into impact at the surface where decisions are being made.

// next engagement

Build this kind of AI footprint for your healthcare brand.