GEOHub
Brand AI Model Visibility Analysis
The first GEO visibility measurement platform

Brand keyword optimizationfor AI models

When users ask AI questions, does your brand show up on the first screen? Measure and improve your presence across mainstream AI models.

Run a brand AI visibility report

Enter your brand name, product name, or other keywords and generate your AI visibility report in 1 minute.

Case wall

Global brand model visibility reports

Mock case

OpenAI

AI infrastructure

GEO66

Mainstream models know the brand well, but comparison prompts still split recommendation share.

Global brand sampleHigh answer visibility
Mock case

DeepSeek

AI model platform

GEO65

The brand earns strong attention in China-facing models, but commercial trust can still improve.

Global brand sampleChina-model strength
Mock case

Notion

Productivity SaaS

GEO57

Recognition is strong, yet recommendation prompts still leave room for sharper category positioning.

Global brand sampleStrong awareness
Mock case

Stripe

Payment infrastructure

GEO65

Commercial prompts trust Stripe, but price-sensitive comparisons still create replacement pressure.

Global brand sampleCommercial trust lead
Mock case

Apple

Consumer electronics

GEO66

Models identify Apple instantly, but category comparisons can weaken direct purchase recommendation share.

Global brand samplePremium brand pull
Mock case

Tesla

Electric vehicles

GEO64

Models surface Tesla frequently, but caution and controversy reduce trust consistency in some answers.

Global brand samplePolarized visibility
Mock case

Nike

Sportswear

GEO68

Nike dominates mindshare in sportswear prompts, though sustainability and pricing caveats still appear.

Global brand sampleHigh category recall
Mock case

Adidas

Sportswear

GEO62

Adidas stays visible in shortlist prompts, but it is less likely to be the default first recommendation.

Global brand sampleStrong shortlist rate
Mock case

Zara

Fast fashion

GEO59

Zara is easy for models to recognize, but quality and sustainability warnings still affect trust wording.

Global brand sampleFast-fashion awareness
Mock case

Uniqlo

Apparel retail

GEO63

Uniqlo performs well in value-led and essentials prompts, especially when users ask for practicality.

Global brand sampleReliable basics brand
Mock case

OpenAI

AI infrastructure

GEO66

Mainstream models know the brand well, but comparison prompts still split recommendation share.

Global brand sampleHigh answer visibility
Mock case

DeepSeek

AI model platform

GEO65

The brand earns strong attention in China-facing models, but commercial trust can still improve.

Global brand sampleChina-model strength
Mock case

Notion

Productivity SaaS

GEO57

Recognition is strong, yet recommendation prompts still leave room for sharper category positioning.

Global brand sampleStrong awareness
Mock case

Stripe

Payment infrastructure

GEO65

Commercial prompts trust Stripe, but price-sensitive comparisons still create replacement pressure.

Global brand sampleCommercial trust lead
Mock case

Apple

Consumer electronics

GEO66

Models identify Apple instantly, but category comparisons can weaken direct purchase recommendation share.

Global brand samplePremium brand pull
Mock case

Tesla

Electric vehicles

GEO64

Models surface Tesla frequently, but caution and controversy reduce trust consistency in some answers.

Global brand samplePolarized visibility
Mock case

Nike

Sportswear

GEO68

Nike dominates mindshare in sportswear prompts, though sustainability and pricing caveats still appear.

Global brand sampleHigh category recall
Mock case

Adidas

Sportswear

GEO62

Adidas stays visible in shortlist prompts, but it is less likely to be the default first recommendation.

Global brand sampleStrong shortlist rate
Mock case

Zara

Fast fashion

GEO59

Zara is easy for models to recognize, but quality and sustainability warnings still affect trust wording.

Global brand sampleFast-fashion awareness
Mock case

Uniqlo

Apparel retail

GEO63

Uniqlo performs well in value-led and essentials prompts, especially when users ask for practicality.

Global brand sampleReliable basics brand
Mock case

Lululemon

Premium activewear

GEO56

Models position Lululemon as premium, but affordability prompts increase replacement risk.

Global brand samplePremium positioning
Mock case

Chanel

Luxury fashion and beauty

GEO61

Luxury authority is strong, though some models still answer with style heritage rather than purchase guidance.

Global brand sampleLuxury authority
Mock case

Dior

Luxury fashion and beauty

GEO60

Dior shows strong style recall, but recommendation answers can shift depending on category context.

Global brand sampleHigh style recall
Mock case

L'Oreal

Beauty group

GEO63

Models recognize the beauty umbrella brand, but product-line specificity is not always consistent.

Global brand sampleBeauty group scale
Mock case

Estee Lauder

Prestige beauty

GEO61

Prestige beauty signals are clear, but recommendation share can narrow when users ask for trendier brands.

Global brand samplePrestige beauty trust
Mock case

SK-II

Skincare

GEO66

SK-II appears often in premium skincare prompts, but ingredient-focused answers can widen comparison pressure.

Global brand sampleSkincare category fit
Mock case

Fenty Beauty

Cosmetics

GEO68

Models associate Fenty Beauty with diversity and shade range, which helps trust in recommendation prompts.

Global brand sampleInclusive brand signal
Mock case

Coca-Cola

Consumer beverage

GEO66

Brand familiarity is extremely high, yet health-oriented prompts can quickly redirect to alternatives.

Global brand sampleMass-market dominance
Mock case

Starbucks

Coffee retail

GEO64

Starbucks is easy for models to recall, but price-value prompts reduce default recommendation strength.

Global brand sampleLifestyle brand recall
Mock case

Dyson

Home and beauty devices

GEO63

Dyson stands out in innovation prompts, but premium pricing keeps replacement risk visible.

Global brand sampleInnovation-led demand
Mock case

Lululemon

Premium activewear

GEO56

Models position Lululemon as premium, but affordability prompts increase replacement risk.

Global brand samplePremium positioning
Mock case

Chanel

Luxury fashion and beauty

GEO61

Luxury authority is strong, though some models still answer with style heritage rather than purchase guidance.

Global brand sampleLuxury authority
Mock case

Dior

Luxury fashion and beauty

GEO60

Dior shows strong style recall, but recommendation answers can shift depending on category context.

Global brand sampleHigh style recall
Mock case

L'Oreal

Beauty group

GEO63

Models recognize the beauty umbrella brand, but product-line specificity is not always consistent.

Global brand sampleBeauty group scale
Mock case

Estee Lauder

Prestige beauty

GEO61

Prestige beauty signals are clear, but recommendation share can narrow when users ask for trendier brands.

Global brand samplePrestige beauty trust
Mock case

SK-II

Skincare

GEO66

SK-II appears often in premium skincare prompts, but ingredient-focused answers can widen comparison pressure.

Global brand sampleSkincare category fit
Mock case

Fenty Beauty

Cosmetics

GEO68

Models associate Fenty Beauty with diversity and shade range, which helps trust in recommendation prompts.

Global brand sampleInclusive brand signal
Mock case

Coca-Cola

Consumer beverage

GEO66

Brand familiarity is extremely high, yet health-oriented prompts can quickly redirect to alternatives.

Global brand sampleMass-market dominance
Mock case

Starbucks

Coffee retail

GEO64

Starbucks is easy for models to recall, but price-value prompts reduce default recommendation strength.

Global brand sampleLifestyle brand recall
Mock case

Dyson

Home and beauty devices

GEO63

Dyson stands out in innovation prompts, but premium pricing keeps replacement risk visible.

Global brand sampleInnovation-led demand

How it works

Generate brand model visibility analysis reports in one click

01

Start with one query

Type a brand name, product name, or strategic keyword into the large intake field.

02

See the report instantly

Open the generated report immediately and review GEO index, recognition, recommendation, sentiment, and replacement pressure.

03

Read the full diagnosis directly

Access the complete report for section-level conclusions, metric explanations, and an action roadmap.

SEO entry

Search entry pages around core GEO metrics

Start with brand visibility, recommendation rate, Top 3 presence, replacement risk, and commercial triggers.

AI Brand Visibility

Measure how often AI models recognize, recommend, shortlist, or replace your brand. Run a free GEOHub summary.

AI Recommendation Visibility

See whether AI models actually recommend your brand, not just mention it. Measure recommendation visibility with GEOHub.

Top 3 AI Presence

Measure how often your brand appears in the Top 3 positions of AI answers and shortlist-style recommendations.

AI Replacement Risk

Understand when AI answers replace your brand with competitors and where demand may be redirected upstream.

AI Commercial Trigger

See whether your brand appears when AI answers high-intent buying and purchase-adjacent questions.

ChatGPT Brand Visibility

See whether your brand appears, gets recommended, or gets replaced in ChatGPT-style discovery and buying prompts.

Curated cases

Curated cases for benchmark and example intent

These pages are built for search entry and case interpretation, not token-based report indexing.

Notion AI Visibility Case

A curated GEOHub case on how strong awareness can still leave a brand exposed in recommendation and shortlist prompts.

Developer Observability AI Case

A curated GEOHub category case showing how AI answers can split recommendation share in observability and monitoring prompts.

What the report explains

Go deeper and get the most honest feedback on your brand.

Clear module verdicts

Each section ends with a direct conclusion instead of generic commentary.

Metric definitions

Every metric explains its calculation logic, reading method, and strategic importance.

Action roadmap

The last section converts weak signals into a 30 / 60 / 90 day optimization plan.