Thanks to decades of clinical research and public education initiatives, people all around the world know just how important sun protection is to skin health. But when it comes to sunscreen, which brands deserve your trust and which ones don’t? For an increasing number of consumers, answering that question begins with an LLM prompt. The resulting shortlist of brands can then become their guide on the buyer journey to a more confident purchase.
According to our GenAI Lens analysis of LLM recommendations for the best facial SPF:
- Dermatologist-backed brands dominate the category.
- Beauty editors, review platforms, and medical sources dominate the leading sources.
- Brand-owned content didn’t move the needle.
Here’s what brands in sun protection and beyond need to know about where and how they appear in LLM recommendations.
Methodology: This analysis is based on GenAI Lens data on LLM responses to the prompt Best SPF for your face generated from March 14 to April 14, 2026, across seven LLM modes: Claude, Deepseek, ChatGPT, Llama, Google AI Mode, Google AI Overviews, and Perplexity. Request a demo to see how an AI visibility analysis can surface actionable insights tailored to your industry and brand.
Contents:
AI Visibility Tiers: Which Sunscreen Brands Did LLMs Surface Most?
Which AI Models Surface Which Sunscreen Brands?
Key Terms: Skin Type and Makeup
Which Sources Actually Influenced AI?
Key Takeaways: What Our Sunscreen Analysis Means for All Brands
FAQ: LLM Recommendations and Sunscreen Brand Visibility
AI Visibility Tiers: Which Sunscreen Brands Did LLMs Surface Most?
Evaluating across all metrics — including visibility, total mentions, and mention rate — the facial sunscreen category separates into three distinct tiers of visibility, led by names whose clinically proven effectiveness factor heavily in their branding.
Tier 1: The default answers (60% visibility)
EltaMD (60% visibility, 198 mentions) and La Roche-Posay (60%, 195 mentions) are effectively the default sunscreen answer in AI, appearing in six out of ten responses. Their lead is thanks to their strong presence in high-authority editorial and clinical sources (more on that below), which are heavily represented in AI citations.
Tier 2: High-potential challengers (33–48% visibility)
Supergoop (48%, 144 mentions), CeraVe (33%, 88 mentions), and Neutrogena (30%, 87 mentions) form a second tier of AI visibility that highlights a fundamental challenge: Widespread name recognition and availability don’t necessarily translate into frequent, prominent LLM recommendations. For this tier, mentions in third-party content tend to skew toward general skincare rather than best-in-class sunscreen recommendations.
Tier 3: Low visibility with niche ownership (9–23%)
COOLA (23%, 50 mentions), Colorescience (16%, 36 mentions), Black Girl Sunscreen (9%, 15 mentions), Shiseido (10%, 11 mentions), and Sephora (11%, 8 mentions) achieved limited visibility in response to our prompt. However, AI did recognize specific differentiators, such as COOLA’s and Colorescience’s mineral/reef-safe positioning.
Implications for brands: Across visibility tiers, brands benefit from third-party validation and differentiation through specific sub-categories and use cases. However, as we’ll expand on next, which brands break through ultimately depends on the LLM generating the response.
Which AI Models Surface Which Sunscreen Brands?
Consumers see dramatically different recommendations depending on which LLM platform they search on. As the heatmap above shows, sunscreen brands can have high visibility on one model and be invisible on others.
DeepSeek was the most brand-inclusive model.
DeepSeek consistently surfaces the broadest set of brands, with La Roche-Posay (97%), EltaMD (97%), Supergoop (95%), and Neutrogena (93%) all registering near-maximum scores. This suggests that DeepSeek drew on the widest range of sources of all the models.
COOLA scored big with Claude.
The only LLM platform that COOLA scored high visibility on was Claude, which also scored it higher than any other brand at 80%. This may point to Claude’s reliance on expert-led, third-party content like this “Best Face Sunscreens of 2026” blog (more on that below), which declared COOLA’s Classic Face Sunscreen SPF 50 its top pick overall.
Google AI Mode and Google AI Overviews recommendations were not the same.
La Roche-Posay (68%), EltaMD (71%), and Supergoop (71%) achieved high visibility scores in Google AI Mode, an opt-in LLM experience. However, on Google AI Overviews, which reaches a larger audience by virtue of being opt-out, no brand scored higher than 17%. This gap shows how the tighter, summary-style format of AI Overviews leaves room for fewer brands compared to more expansive, chat-based experiences like AI Mode.
Meta Llama and ChatGPT: Inconsistent mid-tier
ChatGPT and Meta Llama surfaced first-tier brands reliably but show significant dropoff for everyone else. And even so, no brand achieved higher than 42% visibility, suggesting that these models prioritize widely validated brands over exploration for more niche or specialized products.
Takeaway: With LLM models varying so drastically, brands should focus on building consistent authority across high-quality third-party sources rather than optimizing for any single platform.
Key Terms: Skin Type and Makeup
The keywords most frequently mentioned in AI-generated facial sunscreen recommendations reveal how LLMs frame what “best” means in this category. Terms related to sun protection are a given, but others like “makeup”, “skin type”, “sensitive skin”, and “acne” show how AI-generated answers frame “best” through potential, personalized use cases.
Tip: For LLM analyses tailored to your brand, GenAI Lens’ keyword widget shows you where to dig deeper. For this sunscreen example, next steps include analyzing prompts related to specific consumer use cases, such as layering with makeup or preventing breakouts. See how it works in real time — request a demo to explore the prompts, keywords, and sources shaping AI recommendations in your category.
Which Sources Actually Influenced AI?
Expert-led publications and blogs, as well as beauty retail websites, comprised the top 10 sources cited in LLM answers to our sunscreen prompt. Brand-owned websites were completely absent. As we’ve seen in previous analyses, these results highlight just how much LLMs pull from niche subject matter experts to shape their recommendations to users.
Elements like thorough methodologies, clear structuring, and a comparison table helped this Treeline Review blog stand out to LLM models on the hunt for unbiased, reliable information.
For example, the American Academy of Dermatology website was the third-most influential source with 37 citations of practical resources like this “Sunscreen FAQ” that don’t explicitly mention brands. Fashion website Who What Wear came in second place with 38 citations, thanks to content, like this rigorously researched and tested list of the best facial SPFs. This publication is also home to two of the most cited journalists for this prompt, Eleanor Vousden of Who What Wear UK (28 citations) and Claire Sullivan of Footwear News/WWD (23 citations). However, it was Treeline Review, an outdoor gear review website that generated the most AI citations, with all 45 coming from a single blog called “Best Face Sunscreens of 2026”.
Niche editorial and industry expert sources influence AI more than messaging on brand websites when it comes to evaluating the “best” options. No matter the sector, brand AI visibility strategies should begin with asking, 'Which of the top 100 sources citing in our category are we absent from?' and working backward from there.
Key Takeaways: What Our Sunscreen Analysis Means for All Brands
For brands operating in sunscreen and beyond, winning in AI search means probing how models interpret prompts and building authority where they look for information. Keep in mind:
- LLM recommendations are shaped by a mixture of sources. In the case of sunscreen, earned media and expert content drove visibility more than paid and owned channels.
- As LLMs seek to meet users’ unique needs, its framing of what is “best” trends toward personalization and specific use cases.
- AI models’ tailoring responses to more personalized queries gives lower-visibility brands the opportunity to still break through by owning distinct sub-categories.
In today’s AI landscape, brands that will win the race for visibility will need a bird’s eye-view. to understand where your brand is underrepresented and why, and use those insights to shape your strategy accordingly.
FAQ: LLM Recommendations and Sunscreen Brand Visibility
Which sunscreen brands do LLMs recommend most?
According to Meltwater’s GenAI Lens analysis of sunscreen brands, EltaMD and La Roche-Posay are the most frequently recommended, appearing in roughly 60% of LLM responses and acting as default answers across multiple AI platforms.
Why do LLMs favor certain sunscreen brands over others?
Based on Meltwater’s GenAI Lens analysis of sunscreen brands, LLMs prioritize brands that are consistently featured in high-authority third-party sources such as dermatology organizations, expert reviews, and editorial beauty publications.
Do brand websites influence LLM sunscreen recommendations?
No. Meltwater’s GenAI Lens analysis of sunscreen brands found that brand-owned websites had little to no impact on LLM recommendations, with AI models relying instead on independent, expert-led content.
How do different LLMs vary in sunscreen brand recommendations?
Different LLM platforms produce significantly different brand recommendations, with some models surfacing a wider range of brands and others focusing on a smaller, more consistent set, according to Meltwater’s GenAI Lens analysis of sunscreen brands.
What factors do LLMs consider when recommending facial sunscreen?
Meltwater’s GenAI Lens analysis of sunscreen brands shows that LLMs evaluate sunscreen based on use-case factors such as skin type as well as reliable information from independent, expert-led content.
Why do some sunscreen brands have low visibility in LLM results?
Based on Meltwater’s GenAI Lens analysis of sunscreen brands, brands with lower visibility tend to lack strong representation in high-authority third-party content or are only associated with niche use cases rather than broad “best” recommendations.
How can sunscreen brands improve their visibility in LLM recommendations?
Meltwater’s GenAI Lens analysis of sunscreen brands suggests that improving visibility requires increasing presence in expert-led publications, securing high-quality third-party reviews, and owning specific product niches or use cases.
