
The Black-Owned Beauty Citation Share Index 2026
EPR's first ranked Citation Share study covering Black-owned beauty brands — Fenty, Pattern, Telfar, Honey Pot, Topicals, Briogeo, Lip Bar, Bread Beauty — across 185 prompts and 5 AI engines.

EPR's first ranked Citation Share study covering Black-owned beauty brands — Fenty, Pattern, Telfar, Honey Pot, Topicals, Briogeo, Lip Bar, Bread Beauty — across 185 prompts and 5 AI engines.

Prompt visibility is how present a brand is for a specific prompt, or a specific class of prompts, inside AI systems. It is AI Visibility measured at its most granular level — not across a whole category, but question by question.A brand is rarely visible everywhere or nowhere. I…

I built the first instrument to measure what AI says about everyone. The royal family was the test case. What it shows about the engines should change how every PR firm operates.

Inside EPR's National Retrieval Stack™ for Thailand: Vajiralongkorn, the Shinawatra-to-Anutin transition, cannabis whiplash, Tham Luang, CP Group, and the White Lotus tourism spike.

Five proprietary models. Five distinct citation logics. The category-level reference on who runs AI-mediated discovery — ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews — and the linked playbook for each.

The University of Toronto's definitive audit of GPT-4o, Claude, Perplexity, and Gemini versus Google Search across 1,516 queries. Domain overlap, source typology, content freshness, and the controlled experiment on pre-training versus retrieval bias.

The complete Everything-PR reference on Generative Engine Optimization. Definition, operating system, measurement, the GEO Scorecard franchise, case studies, sector playbooks, and coverage — every live GEO asset, organized.

When a tech publication picks up a luxury AI visibility study unprompted and frames it as a tech story, the category has crossed over. GEO is no longer a PR conversation.

AI search engines are creating challenges in legal contexts by oversimplifying complex legal distinctions. Examples show how AI flattens critical differences in employment law, eviction procedures, and sentencing exposure, leading to potentially inaccurate or misleading information. The dominant sources cited by AI include high-level legal bodies like the Supreme Court and popular platforms like Wikipedia, often overlooking crucial state-level and specialized legal authorities. This trend suggests legal institutions must publish structured primary sources to maintain their authority in the age of AI-driven synthesis.

The llms.txt manifest is the emerging standard for brands to ensure AI engine crawlers can access and cite their content. This article details the crawl layer framework, key AI crawler user agents, and how to avoid common accessibility issues like JavaScript hydration, age gates, geofencing, and rate limiting.