GEO CASE STUDY
Cited on the Science: 43% Citations Growth for InCellDerm
How a science-backed skincare brand built the citation infrastructure that AI systems need to recommend it, growing citations by 43% and expanding cited page coverage by 39% across the ingredient and skin concern queries where purchase decisions begin.
Client
InCellDerm (tryincellderm.com)
Niche
Skincare DTC
Duration
6-Month Campaign
+43%
Citations growth
+43%
Citations growth
+39%
Cited pages growth
The Client
InCellDerm: Science-Driven Skincare Built on Cell Biology
InCellDerm is a science-backed skincare brand rooted in cellular biology research, offering formulations built around ingredient efficacy and skin barrier function rather than trend-led marketing. Sold DTC through tryincellderm.com, the brand operates in a skincare category where AI has become a primary research channel. Consumers increasingly consult large language models to evaluate ingredients, compare formulations, and identify products suited to their specific skin concerns before making a purchase. For a brand whose strength is its science, earning AI citations is a direct function of communicating that science in a format AI systems can extract and cite.
THE CHALLENGE
Strong Formulations, Weak Citation Signal
Underrepresented in AI Skincare Responses
When consumers asked AI systems about ingredient-led skincare, cell regeneration, or skin barrier solutions, InCellDerm was not appearing in the responses. Brands with deeper editorial citation networks were being named instead, regardless of whether their formulations were more or less relevant to the query. The product quality existed. The AI signal did not.
Citation Baseline Too Thin to Compete
With 259 citations at baseline, InCellDerm’s citation footprint was insufficient relative to the incumbents dominating AI skincare recommendations. Established skincare brands with years of editorial placement across beauty, dermatology, and wellness publications had built citation mass that AI systems treat as a credibility proxy. Closing that gap required a systematic programme, not incremental content updates.
Cited Page Coverage Too Narrow for the Category
Skincare AI queries span a wide range of intents: specific ingredients, skin concerns, skin types, routine frameworks, and formulation comparisons. With 153 cited pages at baseline, InCellDerm was absent from the majority of those intents even when it had a product directly suited to the query. Narrow cited page coverage means narrow AI presence, regardless of how strong the core product range is.
Science-Led Brands Need Citation-Ready Content
AI systems in the skincare category are asked to evaluate ingredients, compare formulations, and explain scientific concepts. Content that makes general brand claims rather than specific, extractable ingredient or efficacy statements is not cited in those responses. InCellDerm’s scientific credibility needed to be structured in a format that AI retrieval systems could actually act on.
Our Approach
GEO for Skincare: Translating Science Into Citations AI Systems Can Use
Our strategy for InCellDerm was built on one insight: in a science-led skincare category, citation authority is earned by making complex formulation claims legible to AI retrieval systems at the ingredient and concern level. We focused on converting InCellDerm’s existing scientific credibility into structured, citeable content mapped to the specific intents where skincare AI queries originate.
Ingredient and Concern Intent Mapping
We mapped the AI query landscape across the skincare intents most relevant to InCellDerm’s formulations, covering active ingredients, skin barrier function, cell turnover, and concern-specific clusters such as hyperpigmentation, dehydration, and sensitivity. Each cluster was assessed against the brand’s existing cited page coverage to identify where the citation gap was widest and the competitive resistance was lowest.
Science Structured for AI Extraction
We rebuilt InCellDerm’s content around the structural requirements of AI citation: specific ingredient claims, defined mechanisms, and concern-to-formulation logic that AI systems can extract and cite as a direct answer to a consumer query. Each page was written to answer one clearly defined question with one clearly supported answer, giving AI retrieval systems exactly the extractable unit they need to generate a citation event.
Cited Page Expansion Across Skin Concern Clusters
Growing cited pages from 153 to 213 required building into concern and ingredient clusters where InCellDerm had no existing coverage. We prioritised clusters with high AI query volume and low incumbent citation density, giving InCellDerm the fastest route to new citation events without competing head-on against brands with deeply entrenched editorial networks in those intents.
The Impact
43% Citations Growth: InCellDerm Now Has a Citeable Science Presence AI Systems Draw From
+43%
Citations growth (259 to 370)
+39%
Cited pages growth (153 to 213)
“InCellDerm’s science was always credible. Now it is citeable. The brand has built a structured presence across the ingredient and concern intents where skincare consumers consult AI first, giving it a compounding citation advantage that grows with every new query answered.”
Actionable Insights
What Science-Led Skincare Brands Can Learn From This Campaign
AI Skincare Citations Follow Extractable Claims
When a consumer asks an AI to explain what an ingredient does or recommend a product for a skin concern, the response cites content that makes a specific, defensible claim about a specific ingredient or mechanism. General brand positioning and lifestyle copy do not generate citation events. Science-led brands with strong formulations lose AI visibility when that science is buried in marketing language rather than structured for extraction.
Cited Page Breadth Determines AI Query Coverage
A skincare brand with ten cited pages earns AI mentions across ten intents. One with two hundred earns mentions across the full spectrum of consumer queries in the category. Because skincare AI queries are fragmented across dozens of ingredient, concern, and routine clusters, cited page breadth is the single biggest structural driver of AI mention volume for brands in this space.
Science Credibility Must Be Made Legible to AI
A brand with genuine formulation expertise holds a significant GEO advantage over brands making unsupported claims, but only if that expertise is communicated in a structure AI systems can parse. Clinical research, ingredient mechanisms, and efficacy data need to be written into content at the page level, not referenced in abstract brand copy, for AI systems to treat them as citable authority signals.
GEO Is Where Skincare Consideration Begins
Skincare consumers researching ingredients, comparing actives, or looking for solutions to a specific concern are increasingly doing that research through AI before they visit any brand or retailer website. The brands cited in those responses are introduced at the highest-intent point in the consideration journey. For science-led skincare, GEO is not a supplementary channel. It is where the purchase decision starts.