When AI is asked about shampoo — who does it recommend?
We sent 26 real buying questions to ChatGPT and Google AI Overviews – the questions shoppers actually ask. Then we counted which providers get named, and how often. The result is a ranking built from real AI answers, not opinion.
Nearly half of all AI recommendations go to just 6 of 97 providers.
Kérastase (5.8%) and L'Oréal (4.9%) dominate the answers – the remaining 97 named providers split what's left. If you're not here, you simply don't exist to AI users. That's exactly the gap BuzzView makes visible.
Who does AI recommend for shampoo?
Share of all brand mentions across 26 prompts (Share of Voice). The longer the bar, the more often AI names the provider – across every question tested.
Five things the data reveals about this category
Behind the ranking — what the numbers actually mean for brands in the shampoo market.
97 providers named — yet the top 6 brands capture 26.7% of all AI mentions.
Across 26 prompts, AI systems named 97 distinct shampoo brands — a number that immediately signals how fragmented the category looks from a model's perspective. The long tail is real: 85 of those 97 brands collectively account for 180 mentions, meaning the vast majority of named providers appear only once or twice across the entire prompt set. This is not a market where AI converges on a short, stable list the way it does in, say, project management software or cloud infrastructure.
And yet concentration still exists at the very top. Kérastase (19 mentions, 5.8% share of voice), L'Oréal (16, 4.9%), Sante (14, 4.3%), Sebamed (13, 4.0%), Balea (13, 4.0%), and Lavera (12, 3.7%) together account for 87 of the 326 total mentions — roughly 26.7%. That share may sound modest, but in a pool of 97 named brands it represents a meaningful clustering effect driven by brand recognition, editorial ubiquity, and the sheer volume of consumer review content these brands generate online.
The shampoo market's fragmentation reflects its structural reality: it spans drugstore private labels (Balea, Cien), pharmacy-positioned dermatological brands (Sebamed, Vichy), mass-market prestige (L'Oréal, Garnier), professional salon lines (Kérastase, Wella, Redken), and a fast-growing natural/organic segment (Sante, Lavera, Alverde, Weleda). AI models draw from all of these simultaneously, which is why no single brand commands even 6% share of voice. The competitive landscape is genuinely multi-polar.
For brands outside the top six, the 73.3% of mentions that flow to the remaining field represents both the challenge and the opportunity. Appearing in 97-brand pools means AI is willing to surface almost anyone — but only if the training signal is strong enough. Brands that systematically build review density, expert editorial coverage, and structured product data across hair-care-focused platforms are far more likely to break through the noise and join the recurring mention tier.
The shampoo category is one of the most fragmented AI-search landscapes measured — 97 brands named, no single leader above 6% share of voice. Being mentioned at all already signals meaningful AI footprint; being mentioned consistently is the real differentiator.
Kérastase and L'Oréal appear in 42.3% of prompts. Jean & Len and Cien appear in just 19.2%.
Visibility — measured as the share of prompts in which a brand receives at least one mention — tells a different story than raw mention counts. At the top, Kérastase and L'Oréal each appear in 42.3% of the 26 prompts tested, meaning nearly every other time a user asks an AI system a shampoo-related question, one of these two brands shows up in the response. This is the benchmark for category leadership in AI-generated recommendations: not ubiquity, but consistent presence across prompt types.
At the lower end of the tracked-brand spectrum, Jean & Len and Cien each appear in only 19.2% of prompts — fewer than one in five. The gap between 42.3% and 19.2% is substantial. It means a brand at the bottom tier of tracked providers is essentially invisible for the majority of buying-intent questions. Users who ask about dandruff shampoos, color-safe formulas, or daily-use options are unlikely to encounter Jean & Len or Cien in the AI response unless their prompt very specifically targets those brands.
What drives visibility in the shampoo category? The primary engine is consumer review volume and sentiment on large retail platforms — DM, Rossmann, Douglas, Amazon, and dedicated beauty portals like Beautypedia or Cosmopolitan's product roundups. AI models learn from the editorial patterns of these platforms. Brands that receive consistent, detailed review coverage with keyword-rich context (hair type, concern, ingredient) score higher in the implicit relevance signals that models use when generating recommendations.
Secondary drivers include dermatologist endorsement (highly visible for Sebamed, Vichy), salon professional credentialing (critical for Kérastase, Wella, Redken), and sustainability/ingredient transparency coverage (which has been a major factor in Sante and Lavera's strong visibility relative to their market size). Brands that invest only in traditional advertising without generating the kind of content that AI models index — third-party editorial, clinical studies, expert Q&As — will struggle to close the visibility gap regardless of their retail distribution.
A 23-percentage-point visibility gap separates the top tracked brands from the lowest in the same set — the difference between appearing in 4 out of 10 AI answers and fewer than 2 out of 10. Review density, editorial coverage, and expert endorsement are the levers that move this number.
Best-of prompts favor Kérastase. Concern-specific prompts unlock Sebamed, Sante, and Vichy.
The 26 prompts in this dataset cover four distinct intent types: general best-of questions ("best shampoo 2026"), comparison questions ("Kérastase vs L'Oréal"), concern-specific or use-case queries ("best shampoo for dandruff," "best shampoo for color-treated hair"), and alternative-seeking questions ("alternatives to Schwarzkopf"). Each intent type activates a different layer of the AI's knowledge graph, and the brands that dominate in one category often differ significantly from the winners in another.
General best-of prompts tend to surface the brands with the broadest editorial footprint: Kérastase, L'Oréal, and Schwarzkopf appear reliably here because they have accumulated thousands of "best shampoo" list placements across beauty media. Comparison prompts, by contrast, require that both named brands have strong documentation — which is why L'Oréal consistently performs well in head-to-head formats, as it serves as the reference point against which premium alternatives like Kérastase are evaluated.
Concern-specific prompts are where specialist brands gain their advantage. Sebamed — a brand with a dermatologically certified positioning and clinical pH documentation — outperforms its overall share of voice when prompts target scalp health, dandruff, or sensitive skin. Similarly, Sante and Lavera gain disproportionate visibility on prompts about sulfate-free, natural, or vegan formulas. Vichy benefits from the dermatology-referral context embedded in questions about hair loss or scalp conditions. These brands would appear weaker than they truly are if only measured on general best-of prompts.
For content strategy, this means that a single content pillar is insufficient. Brands need both broad editorial presence (to win best-of prompts) and deep, concern-specific content assets (to win use-case prompts). A brand like Redken or Wella that excels in professional and salon contexts should be producing content that explicitly maps its products to the concern-based questions consumers actually ask — damaged hair repair, color protection, volumizing for fine hair — because those are the prompts where the AI is most willing to surface specialist alternatives over the big mass-market names.
Prompt type is a visibility lever brands can actually influence. Building concern-specific content (scalp health, color care, natural ingredients) unlocks prompt categories where specialist brands like Sebamed, Sante, and Lavera already outperform their overall share of voice.
Balea earns positive framing in 85% of its mentions. Garnier and Schwarzkopf trail at 33–36%.
Sentiment distribution across the tracked brands reveals a striking divergence that raw mention counts and share of voice numbers alone cannot capture. Balea, the dm drugstore private label, achieves the highest positive sentiment rate in the dataset: 11 positive mentions out of 13 total (85%). Sebamed follows closely with 10 positive out of 13 (77%), and L'Oréal posts 10 positive out of 16 (63%). These three brands are not merely named by AI — they are recommended with genuine endorsement language.
At the other end of the spectrum, Schwarzkopf earns only 4 positive mentions out of 11 (36%), while Garnier registers just 3 positive out of 9 (33%). This matters because AI models in recommendation contexts do not merely list options — they qualify them. A mention accompanied by neutral or hedging language ("some users prefer," "commonly available") has a meaningfully different conversion impact than a mention accompanied by affirmative framing ("widely praised for," "dermatologist-recommended," "top-rated for color care").
What drives positive sentiment in the shampoo category? The primary driver is verified consumer outcome language — the kind of testimonial and review vocabulary that appears in star-rated review aggregators, beauty community forums like Reddit's r/HairCare, and magazine roundup articles that include explicit verdicts. Balea's strong positive rate reflects the outsized volume of enthusiastic consumer reviews on DM's own platform and German beauty blogs that have positioned it as exceptional value. Sebamed's rate reflects its clinical positioning and the trust language that dermatologists use when recommending it.
For Schwarzkopf and Garnier, the lower positive rate likely reflects the mixed nature of their product portfolios: both brands cover mass-market to mid-range price points across dozens of product lines, and AI models appear to pick up the heterogeneity of consumer experiences. A brand that sells both budget and premium lines without a clear positioning signal will have its sentiment diluted by average-experience reviews of entry-level products. Brands with a clearer, more consistent quality promise — like Sebamed's pH 5.5 guarantee or Kérastase's professional-grade positioning — tend to generate more consistently positive sentiment in the AI's framing.
Being mentioned is not enough — the sentiment of the mention shapes whether users act on it. Brands like Balea and Sebamed with clear, consistent quality signals earn positive framing in the majority of their AI appearances; brands with diffuse portfolios get mentioned but qualified into neutrality.
97 providers, no brand above 6% share of voice: shampoo is an early-stage AI-search market — and the positions are still fluid.
AI-search maturity in a product category can be assessed by looking at concentration at the top, fragmentation in the field, the consistency of recommendations across prompt types, and the predictability of sentiment. A mature AI-search market — think cloud CRM or project management software — typically shows two to four dominant providers capturing 40–60% of mentions collectively, with a long but stable tail. The shampoo category looks nothing like this. With 97 named brands and a top-6 capturing only 26.7% of mentions, this market is in an early, high-fragmentation phase of AI-search development.
This early-stage fragmentation is partly structural — shampoo genuinely is a more fragmented retail category than software, with hundreds of legitimate brands sold in pharmacies, supermarkets, and salons across Germany alone. But it is also a signal of how AI models are currently trained on this category: without a dominant editorial consensus (no single shampoo equivalent of the "Gartner Magic Quadrant"), models pull from a wide and heterogeneous body of review, blog, and forum content, resulting in high variance in recommendations from one prompt to the next.
The practical implication is that brand positions are still genuinely contestable. Unlike a mature AI-search market where the top two or three players have effectively locked in their position through years of accumulated editorial dominance, shampoo brands in the mid-tier visibility range (23–34% prompt coverage) — Schwarzkopf, Weleda, Redken, Wella, Vichy, Garnier, Alverde, Nivea, Balea — are separated by margins small enough that a focused content investment over the next 12–18 months could realistically shift ranking positions. The window to influence these positions before the market matures and hardens is open right now.
The natural and organic sub-segment is the most interesting pocket of opportunity. Sante (38.5% visibility, 4.3% share of voice) and Lavera (34.6% visibility, 3.7% share of voice) already outperform several larger, better-resourced mass-market brands. As consumer interest in ingredient transparency, sustainability certification, and natural formulation continues to grow, the content ecosystem supporting these brands is likely to expand — and AI models will reflect that shift. Brands positioned in the natural/organic space have a structural tailwind in AI-search that is not yet fully priced into their visibility scores.
Shampoo is an early-stage AI-search market with positions still in flux — which means the cost to move is low and the potential gain is high. Brands that invest in structured, concern-specific, sentiment-positive content now are building an AI visibility lead that will become progressively harder to close as the market matures.
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AI visibility of the tested providers
Visibility score = share of prompts where the provider appears in the AI answer at all. 100% means: present for every relevant question.
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