/ Client Implementation Case Study
How AI Search Is Recommending Body Care Brands Case Study
How AI Search Is Recommending Body Care Brands
By Mark HuntleyFounder and CEO/ Key Outcomes
Results at a glance.
Neutral presence only for CeraVe and Cetaphil
CeraVe and Cetaphil appeared in the observed response as factual cleanser examples rather than valid recommendations.
No confirmed recommendation leaders
The supplied evidence does not show positive recommendation credit, top-three recommendation capture, rank-one credit, or captured recommendation value for either surfaced brand.
Billie did not appear
Billie was not framed, ranked, or recommended in the observed Google AI Mode answer.
One observed response with modeled monthly qu…
The dataset contains one observed Google AI Mode response for an evaluation-style cleanser-versus-face-wash prompt with modeled monthly query volume of 473.
/ Market Context
What Changed in the Market
Body care is no longer discovered only through retail shelves, influencer content, paid social, branded search, and marketplace listings.
AI systems increasingly answer direct consumer questions such as what should I use, what should I compare, which product type fits a skin concern, and which brands represent a category. In that environment, brands compete not only for awareness, but for retrieval fit inside AI-generated explanations.
The observed query was evaluative rather than purely informational.
That matters because AI systems often use these moments to introduce default brand examples that may shape later searches for best, reviews, for sensitive skin, and where to buy.
/ The Challenge
What the Brand Needed
This snapshot highlights the gap between visibility, recommendation power, and retrieval fit in AI-mediated discovery moments, especially for brands that want to appear beyond their strongest historical category.
PRIORITY / 01
Build Stronger Product-Function Associations
Body care brands need to be clearly connected to use cases such as body wash, shaving, body lotion, moisturizer, sensitive skin, dry skin, sunscreen / body SPF, exfoliation, deodorant, and cleanser alternatives.
PRIORITY / 02
Separate Awareness from Retrieval Fit
A brand can be known by consumers and still be missing from AI-mediated decision paths. Billie's absence in this snapshot is a reminder that brand awareness does not automatically translate into AI retrieval.
PRIORITY / 03
Strengthen the Evidence Layer Around Adjacent Categories
If a brand wants to appear beyond its strongest historical category, it needs public source material that supports that expansion. For Billie, that may mean clearer evidence around body care, shaving-adjacent skincare, sensitive-skin use cases, and comparison-stage consumer questions.
PRIORITY / 04
Expand Prompt Coverage Before Making Category Claims
A publish-ready benchmark would need broader cluster coverage across high-intent prompts such as best body wash, sensitive-skin body care, shaving products, moisturizers, sunscreen / body SPF, body lotion, reviews, alternatives, and brand-versus-brand comparisons.
/ Our Approach
What we did.
Mapped AI Recommendation Visibility Across Prompts and Platforms
Track prompts, platforms, company presence, valid recommendations, top-three performance, rank-one performance, framing, and citation sources.
Identified the Sources Shaping AI Answers
Find the editorial sources, review sites, forums, government sources, directories, owned properties, and search-visible sources that influence brand framing.
Built the Citation Architecture Plan for Public Evidence
Strengthen the public evidence layer so AI systems have more accurate, consistent, and persuasive source material to synthesize.
/ The Outcome
The Outcome
The benchmark produced an early market signal rather than a category-wide winner claim.
- Neutral presence for CeraVe and Cetaphil Both brands were retrieved as representative cleanser examples, not endorsed as the best options.
- No valid recommendations confirmed The supplied observation does not support recommendation credit, top-three capture, or rank-one credit.
- Billie remained absent in the observed answer Billie did not appear in the Google AI Mode response.
- Low-confidence public teaser only Because the sample size is one observation, this should be treated as a low-confidence public teaser, not a full market census.
Neutral presence for CeraVe and Cetaphil Both brands were retrieved as representative cleanser examples, not endorsed as the best options.
No valid recommendations confirmed The supplied observation does not support recommendation credit, top-three capture, or rank-one credit.
Billie remained absent in the observed answer Billie did not appear in the Google AI Mode response.
Low-confidence public teaser only Because the sample size is one observation, this should be treated as a low-confidence public teaser, not a full market census.
/ Take the next step
Want to Understand Your AI Citation Footprint?
We start every engagement with a full audit of how AI systems reference your brand today.
Measurable, Repeatable Programme
Build a durable foundation of credible citations that compounds over time and continues to influence AI answers as new queries emerge
Citation Architecture Review
Identify which high-authority community sources are and aren't working in your favour across AI platforms.
AI Visibility Audit
Understand exactly how LLMs are referencing your brand today and which sources are shaping those answers.
/ Learn More
Understanding AI Visibility
About The Author
Mark Huntley
Founder and CEO
Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.