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An AI Visibility Study by Track My Visibility

Trackdown Report: Rare Beauty

Last Updated :

09 Mar 2026

Analyzing how a celebrity-founded inclusive beauty brand performs across AI-generated answers in the blush, foundation, and clean makeup category

🔥 Key Finding

Rare Beauty ranks #1 among all tracked competitors in AI visibility, outperforming established brands in the category. However, 70.83% of tracked prompts still return no brand mention. Most gaps are in use-case scenarios, beginner-focused content, and unbranded category discovery prompts.

37%

Overall Visibility

The Coverage Problem

1.9

Average Position

The Prominence Strength

#1

Competitive Rank

Category leader in AI visibility

+90

Net Sentiment

Overwhelmingly Positive

AI Engine Performance Breakdown

Each Al engine reveals a different facet of the same authority gap

Perplexity - 36.67%
Gemini - 53.33%
ChatGPT - 20%
AI Overview - 6.67%

Rewards category definition. Rare Beauty is excluded when it fails to answer the why behind the category.

Rewards verifiable claims. Rare Beauty appears when statements can be cross-referenced.

Rewards conceptual relevance. Rare Beauty fits into broad conversations but doesn't anchor them.

Rewards explanatory necessity. Rare Beauty is rarely essential to comprehensive answers.

Top 6 Prompts Where the Brand Was Not Visible

Prompt:

"Best dewy foundation for dry skin"

NARS

NARS

Ilia

Ilia

Charlotte Tilbury

Charlotte Tilbury

Maybelline

Maybelline

L'Oreal

L'Oreal

Rare Beauty

Rare Beauty

Prompt:

"How to layer highlighter over sunscreen"

NYX Cosmetics

NYX Cosmetics

Supergoop!

Supergoop!

Ilia

Ilia

Neutrogena

Neutrogena

Naked Sundays

Neutrogena

Rare Beauty

Rare Beauty

Prompt:

"What products to use for natural wedding makeup"

Charlotte Tilbury

Charlotte Tilbury

NARS

NARS

Ilia

Ilia

Glossier

Glossier

Tarte

Tarte

Rare Beauty

Rare Beauty

Prompt:

"Minimal makeup kit for beginners"

Maybelline

Maybelline

e.l.f. Cosmetics

L'Oreal

L'Oreal

Patrick Ta

Patrick Ta

Rare Beauty

Rare Beauty

Prompt:

"Budget-friendly cruelty-free makeup under $20"

e.l.f.

NYX Cosmetics

NYX Cosmetics

Wet n Wild

Wet n Wild

Milani Cosmetics

Milani Cosmetics

Pacifica

Pacifica

Rare Beauty

Rare Beauty

Prompt:

"Sheer vs light coverage for natural look"

NARS

NARS

Ilia

Ilia

Estée Lauder

Patrick Ta

Patrick Ta

Laura Mercier

Laura Mercier

Rare Beauty

Rare Beauty

Top 5 Prompts Where the Brand Was Visible

Vegan cruelty-free clean makeup picks

K-beauty style tints alternatives worldwide

What makeup to use for a 5-minute face

Best highlighters for glass skin look

Everyday makeup essentials checklist

Top Competitors Frequently Mentioned

RankBrandPositionVisibilityKey Advantage
#1
Rare Beauty
1.937%Sentiment + comparison dominance
#2
Glossier
2.218%Beginner-focused content
#3
Fenty Beauty
2.215%Foundation + shade expertise
#4
NARS
2.013%Comparison infrastructure
#5
Maybelline
2.413%Budget positioning

Content Infrastructure Gap Analysis

Where content investment is needed to match or exceed competitive benchmarks in the six dimensions that AI systems prioritize for brand mentions

Rare beauty radar

Why These Gaps Exist

These gaps are not related to product quality or brand reputation, but rather to how content is structured, validated, and made discoverable to AI systems

No Explainer Content Infrastructure

Rare Beauty relies on product pages and social validation. Missing: use-case hubs answering "waterproof blush for travel", "makeup for sensitive skin", or "beginner makeup routines".

Weak External Validation Signals

Awards exist (Allure, Vogue features), but aren't structured for AI discovery. Limited FAQ schema, review markup not prominently displayed in machine-readable format.

Missing Comparison-Ready Content

AI defaults to YouTube creators and editorial sites for "Rare Beauty vs Fenty" queries because the brand doesn't own its comparison narrative beyond product pages.

Thin Schema Implementation

Product pages use basic schema but lack FAQ schema, HowTo markup, and scenario-based structured content that AI engines prioritize for educational queries.

Strategic Recommendations

Each recommendation addresses a specific structural weakness in how AI systems currently evaluate and surface the brand

Build Category-Led Content

  • Create "Best Blush for [Skin Type]" educational hub
  • Develop beginner makeup tutorials with HowTo schema
  • Build use-case landing pages: beach makeup, gym-proof looks, minimal routines
  • Launch "Clean Beauty Explained" positioning content

Amplify External Validation Signals

  • Create awards page with schema highlighting press mentions
  • Add FAQ schema on product pages covering skin compatibility
  • Display sensitive skin/dermatologist validation where applicable
  • Structure reviews with aggregated rating schema

Own the Comparison Narrative

  • Create owned content: "Rare Beauty vs Glossier: Honest Comparison"
  • Develop comparison tables for celebrity brands
  • Build ingredient and price comparison guides
  • Launch "Clean Beauty Alternatives" content series

Enhance Schema and Structured Data

  • Implement FAQ schema answering common product questions
  • Add HowTo schema for application guides
  • Create Product schema with vegan/cruelty-free attributes
  • Structure gift guides with ItemList schema

What This Study Teaches About AI Visibility

AI rewards clarity over persuasion

Brand storytelling builds loyalty, but clear, machine-readable explanations about product selection and use cases drive AI visibility.

Category ownership matters more than brand recall

Brands that build use-case hubs dominate unbranded discovery, even if less culturally prominent than celebrity brands.

Comparative content unlocks disproportionate visibility

Owning comparison content prevents third-party reviewers from controlling the narrative in AI answers.

Depth of explanation beats surface-level detail

AI favors entities that answer why and how, not just what. Depth of explanation builds durable visibility.

Consistency across channels reinforces AI trust

AI visibility compounds when structured, validated content is consistent across website, YouTube, editorial, and retailer pages.

Methodology

Study Parameters:

Total Prompts

120 unique prompts tracked within TMV

AI Engines

ChatGPT, Perplexity, Gemini, AI Overview

Time Window

Mar 02, 2026 to Mar 09, 2026

Category

Beauty, Inclusive Makeup, Liquid Blush, Foundation

Intent Mix

Commercial-heavy with supporting informational, comparison, and trust queries

Prompt Design:
  1. Each prompt mapped to one primary intent category (commercial, informational, comparison, trust/validation)
  2. Strong majority of non-branded prompts to test category authority vs brand recall
  3. Mix of short, direct questions and longer, descriptive queries mirroring natural AI usage
  4. Aligned with core themes: coastal design, marine-grade materials, resort style, saltwater durability
Limitations:
  1. AI responses evolve over time; results represent a snapshot of current behavior
  2. Prompt selection influences visibility patterns; different prompt sets may yield different results
  3. Brand-controlled content changes can rapidly affect AI visibility
  4. Results specific to beauty category; patterns may differ in other segments