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The Vertical Citation Audit 2026: 7 Verticals Ranked by AI Citation Share — Luxury Hotels, Universities, Fashion, Hospitals, Restaurants, Law Firms, Financial Advisors

EPR Editorial TeamEPR Editorial Team4 min read
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the vertical citation audit — 5w ai visibility index research cover
the vertical citation audit — 5w ai visibility index research cover
  1. Law Firms — most concentrated: a small number of BigLaw names dominate almost every tested query.
  2. Financial Advisors — high concentration around a handful of national wirehouses and robo-advisors.
  3. Universities — high concentration around a stable set of top-ranked institutions.
  4. Hospitals — moderate-high concentration around a few nationally recognized health systems.
  5. Luxury Hotels — moderate concentration; strong brand recall but engines cite specific properties over parent brands.
  6. Fashion — moderate concentration; heritage luxury houses share the answer with a handful of digital-native names.
  7. Restaurants — least concentrated: highly local and long-tail, few names repeat across markets.

What the Audit Tested

The audit ran category-relevant buyer-research prompts, "best [category] in [context]," "top-rated [category] for [use case]," "how do I choose a [category]," across seven verticals: luxury hotels, universities, fashion, hospitals, restaurants, law firms, and financial advisors. Each vertical was tested against a fixed entity set relevant to that category, run through all five frontier engines (ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews). Figures are labeled "Estimated ~X% modeled" and read as a cross-vertical comparison, not as a live citation log for any single brand.

Why Concentration Varies This Much Across Verticals

The spread between the most and least concentrated verticals traces to how buyers actually search. Law firms and financial advisors are categories where buyers ask comparison and credential questions, "top M&A firms," "best wealth manager for [situation]," and a small set of nationally recognized names answers almost every version of that question, so citation concentrates hard at the top. Restaurants sit at the opposite end: the buyer query is almost always locally scoped ("best restaurant in [city]"), so the answer set resets by market and no small group of names can dominate nationally.

Hotels and fashion land in the middle for a related reason, brand recognition is national or global, but the actual cited entity is often more specific than the brand (a named property, a named collection or spokesperson), which spreads citation across more surfaces than a pure brand query would.

Vertical-by-Vertical Notes

Law Firms. The tightest concentration in the study. A handful of BigLaw names answer most comparison and credential queries, consistent with the pattern EPR has documented separately in the dedicated Law Firms Citation Share Audit.

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Financial Advisors. National wirehouses and a small number of robo-advisor brands dominate general "how do I choose" queries; independent regional advisors rarely surface unless the query names a specific city or niche.

Universities. A stable top tier answers most "best university for X" queries regardless of engine; mid-tier and regional institutions surface mainly on narrowly scoped program-specific queries.

Hospitals. A small number of nationally recognized health systems dominate general queries; regional and community hospitals surface mainly on location-scoped queries.

Luxury Hotels. Strong brand-level recall, but engines frequently cite a specific named property over the parent brand when the query is destination-scoped.

Fashion. Heritage luxury houses share the answer with a smaller number of digital-native names that over-index relative to their retail footprint, echoing the pattern in EPR's broader Fashion Citation Share Index.

Restaurants. The least concentrated vertical tested, answers reset almost entirely by city, and no small set of names repeats across markets the way it does in every other vertical here.

What This Means for Practitioners

The practical takeaway is that "get cited" strategy needs to be vertical-specific. In law, finance, university, and hospital categories, the opportunity is displacing or joining a small, stable top tier, a hard, slow fight for share against entrenched names. In hotels and fashion, the opportunity is winning the property- or collection-level citation even without owning the brand-level one. In restaurants, national brand-building barely matters; the fight is local, market by market.

Methodology

Seven verticals, a fixed category-relevant entity set per vertical, category-relevant buyer-research prompts, five engines (ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews), directional source-weight modeling. All figures labeled "Estimated ~X% modeled." Full methodology: The GEO Citation Audit: Six-Step Methodology.

The AI Visibility Audit Cluster

Master index: The AI Visibility Audit Cluster 2026, Research series measuring how corporate communications and industry pages surface in AI engine retrieval.

Direct siblings: IR Page Citation Audit 2026 · Wire Service Citation Audit 2026 · 100 Consumer Brands Citation Share Study · Podcast Citation Index 2026 · Paywall Visibility Index 2026 · AI Language Citation Audit (Arabic, Spanish, French, German)

Methodology anchor: How Citation Share Works: The Measurement Framework

Related: AI Communications · GEO (Generative Engine Optimization) · The Answer-Engine Era · Citation Share Index 2026

Frequently Asked Questions

Which vertical has the most concentrated AI Citation Share?

Law firms, followed by financial advisors and universities. A small number of nationally recognized names answer most comparison and credential queries in these categories.

Which vertical has the least concentrated AI Citation Share?

Restaurants. Buyer queries are almost always scoped to a specific city, so the cited answer set resets by market and no small group of names dominates nationally.

Why do luxury hotels and fashion brands see moderate rather than high concentration?

Because engines frequently cite a specific named property, collection, or spokesperson rather than the parent brand, which spreads citation across more distinct entities than a pure brand-level query would.

How many engines and verticals did this audit cover?

Seven verticals, luxury hotels, universities, fashion, hospitals, restaurants, law firms, and financial advisors, tested against all five frontier engines: ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews.

EPR Editorial Team
Written by
EPR Editorial Team

The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.

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