How social discovery shapes AI search visibility in beauty

AI search visibility in beauty is increasingly shaped before a prompt is ever entered.

Brands that appear in generative answers are often those already discussed, validated, and reinforced across social platforms. By the time a user turns to AI search, much of the groundwork has been laid.

Using the beauty category as a lens, this article examines how social discovery influences brand visibility – and why AI search ultimately reflects those signals.

Discovery didn’t move to AI – it fragmented

Brand discovery has fragmented across platforms. AI tools influence mid-funnel consideration, but much discovery happens before a user enters a prompt.

The signals that determine AI visibility are formed upstream. By the time a user reaches generative search, preferences and perceptions may already be set. If brands wait until AI search to influence demand, the window to shape consideration has narrowed.

That upstream influence is increasingly social. Roughly two-thirds of U.S. consumers now use social platforms as search engines, per eMarketer research. 

This shift extends beyond Gen Z and reflects how people validate information and discover brands. These same platforms consistently appear among the top citation sources in AI results. The dynamic is especially visible in the beauty category.

In a study our agency conducted with a beauty brand partner, we found that Reddit, YouTube, and Facebook ranked among the top cited domains in both AI Overviews and ChatGPT.

While Reddit is often viewed as an anti-brand environment, YouTube appears nearly as frequently in citation data, making it a logical and underutilized target for citation optimization.

Dig deeper: Social and UGC: The trust engines powering search everywhere

The volume reality: Social behavior still outpaces AI

It’s easy to focus on headline figures around AI usage, including the billions of prompts processed daily. But when measured against business outcomes such as traffic and transactions, the scale looks different.

Social platforms are already embedded in mainstream search behavior. For many users, search-like activity on platforms such as TikTok and YouTube is habitual. Nearly 40% of TikTok users search the platform multiple times per day, and 73% search at least once daily.

Referral data reinforces the contrast. ChatGPT referral traffic accounted for roughly 0.2% of total sessions in a 12-month analysis of 973 ecommerce sites, a University of Hamburg and Frankfurt School working paper found. In the same dataset, Google’s organic search traffic was approximately 200 times larger than organic LLM referrals.

AI search is growing and strategically important. But in terms of repeat behavior, measurable sessions, and downstream transactions, social platforms and traditional search continue to operate at a substantially larger scale.

The validation loop: Why AI needs social

The most critical contrarian point for 2026 is that optimizing for social is also optimizing for AI. Large language models are not primary sources of truth. They function as mirrors, reflecting the consensus formed through human conversations in the data they are trained on.

AI systems also demonstrate skepticism toward brand-owned properties. One study found that only 25% of sources cited in AI-generated answers were brand-managed websites.

At the same time, AI engines prioritize third-party validation. Up to 6.4% of citation links in AI responses originated from Reddit, an analysis by OtterlyAI found. This outpaces many traditional publishers.

There’s also a measurable relationship between sentiment and visibility. Research shows a moderate positive correlation between positive brand sentiment on social media and visibility in AI search results.

Dig deeper: The social-to-search halo effect: Why social content drives branded search

Video and expert authority shape AI visibility

Treating video as a “brand channel” or a social-first effort rather than a search surface is a strategic failure.

On platforms such as TikTok and YouTube, ranking signals are shaped by spoken language, on-screen text, and captions – signals AI crawlers increasingly use to “triangulate trust.”

In the beauty category, for example, ChatGPT accounts for about 4.3% of searches, while Google processes roughly 14 billion searches per day. However, for “how-to” and technique-based queries, consumers favor the detailed, personalized guidance of social-first video content.

At the same time, the beauty sector has fractured into two universes, according to Yotpo’s GEO for Beauty Brands analysis.

Science-backed brands such as Paula’s Choice and CeraVe dominate AI-generated results because they publish deep, structured educational content. Meanwhile, more traditional marketing-led brands are significantly less visible.

The phrase “dermatologist recommended” correlates with high visibility in AI results because large language models treat expert social proof as a primary ranking signal, according to the same report.

Breaking the high-production barrier: Creating content at scale

One of the biggest hurdles brands cite is budget. Many believe they need a Hollywood production crew to compete in video environments. That is a legacy mindset. 

In today’s environment, high-gloss production can be a deterrent. The current landscape rewards authenticity over polish. Consumers are looking for real people with real skin concerns, not highly filtered commercials.

Optimizing for video discovery doesn’t require filmmaking expertise. Brands can leverage internal talent without adding headcount.

• Partner with creator platforms: Platforms such as Billow or Social Native allow brands to work with creators for as little as $500 per video. When mapped to a high-intent query, that investment can drive measurable search visibility outcomes.
• Leverage social natives on staff: Often, the strongest asset is internal. Identify team members who are active on platforms such as TikTok and understand platform dynamics. Creating internal incentives or challenges to produce content can generate a steady stream of authentic assets while contributing to culture.
• Make strategy the differentiator: A large following is not a prerequisite for visibility. In one case, a TikTok profile built from scratch with one part-time creator at $2,500 per month generated hundreds of thousands of views within 90 days. The focus was not on viral trends, but on meaningful transactional terms that drive revenue.

If a new profile can reach more than 100,000 views per video within three months on a limited budget, the barrier isn’t equipment. It’s clarity on the business case and disciplined execution.

Dig deeper: How to optimize video for AI-powered search

The new beauty SEO playbook for 2026

The data is clear. Brands can’t win the generative engine if they’re losing the social conversation.

AI models function as mirrors, reflecting web consensus. If real users on Reddit, YouTube, and TikTok aren’t discussing a brand, AI systems have little to surface.

If marketers wait until a user reaches a ChatGPT prompt to shape perception, the opportunity has already narrowed.

Discovery happens upstream. Validation occurs in the loop between social proof and algorithmic citation.

Translating this into action requires rethinking team structure and priorities:

• Stop the silos: Your SEO and social teams shouldn’t speak different languages. Both must focus on search surfaces.
• Prioritize the “why” before the “what”: Don’t just fix a technical tag. Build the business case for how social sentiment and expert validation drive market share.
• Embrace scrappy execution: Whether through $500 creator partnerships or internal social-native talent, start building authentic assets now.

We’re witnessing a shift from algorithm-driven discovery to community-driven discovery.

It’s agile and multidisciplinary, and when executed well, it can meaningfully impact the bottom line.