When AI is asked about toothpaste — 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 81 providers.
Elmex (9.2%) and Colgate (7.3%) dominate the answers – the remaining 81 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 toothpaste?
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 this space.
81 providers named. The top 6 capture 40% of all AI mentions.
Across 26 prompts, AI systems collectively named 81 distinct toothpaste brands — a number that initially suggests a wide-open, fragmented market where any brand might have a shot at visibility. The reality is far more concentrated. The top six providers — Elmex, Colgate, Sensodyne, Parodontax, Meridol, and Blend-a-med — account for 126 of 314 total mentions, which comes to exactly 40.1% of all AI-generated recommendations. The remaining 60% is scattered across 75 other brands, most of which appear only once or twice across the entire prompt set.
This pattern is a classic power law, and it plays out in toothpaste in a particularly sharp way because the category is dominated by a handful of pharmaceutical-grade, clinically validated brands that have built decades of dentist endorsements and independent research backing. Elmex, a brand developed with Swiss dental institutes, leads with 29 mentions. Sensodyne, backed by GSK's clinical documentation infrastructure, places third with 22 mentions. These are not random outcomes — they reflect the types of sources AI systems draw on when answering health-adjacent product questions.
What makes toothpaste different from, say, a software or fashion category is the presence of functional sub-segments that partially democratize the space. Sensitivity, whitening, children's formulas, fluoride-free options, and gum care each have their own leading brands. Sensodyne dominates the sensitivity sub-niche, Parodontax owns the gum-bleeding angle, and natural brands like Lavera and Weleda hold credible positions in the fluoride-free segment. This means that within sub-segments, concentration is even higher — but a different set of names emerges at the top depending on which segment the prompt targets.
For challenger brands, the 69 brands in the "andere" (other) category — accounting for 129 of 314 mentions collectively — reveal both the ceiling and the floor. Getting mentioned at all is achievable. Breaking into the top six requires clinical credibility, sustained media coverage across dental health outlets, and presence in review ecosystems that AI systems index heavily, such as pharmacist recommendation databases, Stiftung Warentest archives, and major dental association publications. The structural gap between the sixth and seventh position is wide and will only deepen as AI systems increasingly favor sources they already have high trust in.
The toothpaste AI landscape is deceptively open — 81 brands get named, but 40% of all recommendations go to just six. For any brand outside this top tier, the priority must be owning a specific health segment rather than competing head-on for the general "best toothpaste" answer.
Elmex appears in 61.5% of prompts. Dentalux and Urtekram appear in just 15.4%.
The visibility score — representing the share of the 26 prompts in which a brand was named at least once — reveals a four-tier structure within the tracked brands. Elmex sits at the top at 61.5%, meaning AI systems found it relevant across more than six out of ten prompts. Sensodyne follows at 53.8%, Colgate at 46.2%, and Parodontax at 38.5%. These four brands form a clear first tier that AI consistently reaches for regardless of whether the prompt is about general best-of, sensitivity, children, whitening, or gum care.
The second tier — Blend-a-med at 34.6%, Oral-B at 30.8%, Meridol at 30.8%, and Weleda at 30.8% — shows brands with solid but narrower relevance. They appear in roughly a third of prompts, typically for specific use cases where they have documented strengths. Blend-a-med and Oral-B draw on Procter & Gamble's investment in consumer content and dental professional outreach. Weleda benefits from its well-established natural/biodynamic positioning, which earns it consistent mentions on fluoride-free and natural care prompts.
What drives visibility in the toothpaste category is a specific combination of clinical endorsements and structured editorial coverage. Brands like Elmex and Sensodyne rank highest not because they spend more on consumer advertising, but because they are referenced in dentist recommendation guides, appear in Stiftung Warentest test results that are widely cited online, and have years of indexed content associating them with specific health outcomes. AI systems aggregate these citation trails. A brand that appears in 50 dentist-recommendation blog posts will appear in AI answers far more reliably than a brand with strong TV ad recall but sparse professional documentation.
Brands in the bottom tier — Dentalux, Urtekram, Alverde, and Curaprox at 15–19% visibility — are not invisible, but they operate at the edge of AI awareness. Their mentions are highly prompt-specific, appearing only when the exact niche they serve is addressed directly. Curaprox, for instance, has a premium positioning with strong dental professional support, yet its visibility lags. This likely reflects a content gap: clinical and review content for Curaprox exists mainly in German, and the AI systems queried in this study may be weighting English-language sources more heavily. For these brands, a targeted multilingual content strategy focused on specific health verticals represents the clearest path to higher prompt coverage.
The 46-point visibility gap between Elmex and Dentalux is driven primarily by the depth and breadth of clinical and editorial documentation available online — not marketing spend. Brands in the bottom tier should audit which health sub-segments they can plausibly own, then invest in building structured, citation-worthy content specifically for those use cases.
Different questions produce different winners — and most brands only show up for one type.
The 26 prompts in this study span four distinct query types, and each type has a different competitive landscape. Best-of prompts — "beste Zahnpasta 2026," "welche Zahnpasta ist die beste?" — reliably surface the broad category leaders. Elmex, Colgate, Sensodyne, and Blend-a-med dominate these answers, because their brand equity is sufficiently broad to be recognized as all-round recommendations. These prompts produce the highest mention density but also the most predictable answers, which means they are simultaneously the most valuable and the hardest to crack for newcomers.
Use-case and vertical prompts — "beste Zahnpasta für empfindliche Zähne," "Zahnpasta gegen Zahnfleischbluten," "beste Zahnpasta für Kinder" — tell a more nuanced story. Sensodyne predictably leads sensitivity prompts with authority, while Parodontax and Meridol capture the gum-health angle almost exclusively. Children's prompts surface Elmex Kinder and Blend-a-med Kids as primary recommendations, reducing the field dramatically. Natural brands like Lavera, Weleda, and Alverde only emerge reliably on fluoride-free prompts. The implication is clear: these brands have achieved segment AI-visibility, but they have not built the cross-segment recognition that would drive overall share of voice higher.
Comparison prompts — exemplified in the study by "Elmex vs Colgate – which is better?" — generate the richest analysis-style responses from AI systems and tend to produce more balanced, considered outputs with explicit pros and cons. These prompts are where brand narratives and positioning statements matter most, because AI systems must choose how to frame each brand's strengths. Brands with clear, differentiated positioning — Sensodyne for sensitivity, Parodontax for gum health — fare well in comparison prompts because their use-case clarity gives AI systems an obvious frame to work with.
Alternative-seeking prompts — "gute Zahnpasta ohne Fluorid" — open the door widest for smaller and niche brands. Eurodont, Dontodent, and Prokudent, which are discount pharmacy brands, achieve their most significant AI mentions in this context, as AI systems seek to provide a range of accessible options at different price points. The content strategy implication is significant: if a brand can own a specific "alternative to X" or "best Y for budget-conscious buyers" narrative, it can generate consistent AI visibility without needing to compete for the premium recommendation slot. This is the primary growth lever available to brands currently sitting in the 15–25% visibility tier.
No single brand dominates all prompt types. Brands that map their content strategy to specific prompt categories — sensitivity, gum care, children, fluoride-free, budget — consistently outperform their overall market share in AI recommendations for those segments. Prompt-type targeting is the most efficient path to increased AI visibility in this category.
Prokudent earns 100% positive mentions. Parodontax is the only brand with negative sentiment on record.
Of all the findings in this study, the sentiment data may be the most commercially significant. AI systems do not simply name brands — they frame them. A mention accompanied by qualifiers like "clinically proven," "recommended by dentists," or "ideal for sensitive teeth" carries a fundamentally different commercial value than a mention framed as "affordable but limited" or "not suitable for daily use." Analyzing the positive, neutral, and negative mention breakdown across the tracked brands reveals meaningful strategic differences in how each brand is positioned in AI-generated responses.
Prokudent stands out as the single brand in the dataset with a 100% positive sentiment rate — all 8 of its mentions carry positive framing. This is particularly striking for a discount pharmacy brand, and it likely reflects a positioning advantage: when AI systems mention Prokudent, they do so specifically in the context of value-for-money recommendations, where the positive framing is inherent to the context. Similarly, Eurodont achieves 7 positive mentions out of 9 total, suggesting that discount brands, when mentioned at all, tend to be praised for what they deliver within their category. The context of the recommendation creates a natural positive frame.
In contrast, Sensodyne — despite its 22 total mentions — achieves only 9 positive mentions against 13 neutral ones. This neutral-heavy profile is characteristic of well-established brands that AI systems treat as functional defaults rather than enthusiastic recommendations. "Sensodyne is a good option for sensitive teeth" is a different signal than "Sensodyne is highly recommended by dentists and rated best in category." The distinction matters for consumer decision-making: positive framing drives click intent, while neutral framing registers as information without emotional pull. Brands with high mention counts but neutral-dominant sentiment should audit the source content AI draws from and invest in driving more explicitly positive third-party validation.
Parodontax is the only brand in the leaderboard with a recorded negative mention — 1 out of 18 total. While a single negative mention is not statistically alarming, it is worth investigating. In the toothpaste category, negative AI mentions most commonly arise from specific product formulations that consumer forums or dental publications have criticized — strong flavors, higher abrasiveness scores, or formulations not recommended for certain conditions. In Parodontax's case, its sodium bicarbonate-based formulation is occasionally flagged in consumer dental discussions as too harsh for users with existing enamel erosion. Understanding which source texts are generating this framing is the first step toward neutralizing the negative signal through targeted counter-content.
Mention volume and sentiment are independent dimensions that must be tracked separately. A brand with 22 mentions and 59% neutral framing (Sensodyne) is in a different strategic position than a brand with 8 mentions and 100% positive framing (Prokudent). For brands targeting AI-driven purchase intent, converting neutral mentions into positive ones is often more impactful than simply increasing total mention count.
81 named brands, 0% negative for most players — this category is mature, structured, and already closing.
The toothpaste AI landscape is not in an early, chaotic phase where brand positions are still being formed. The data shows a market that is already well-structured in how AI systems understand and represent it. Established clinical brands hold the top positions with consistent logic — Elmex for general excellence and caries prevention, Sensodyne for sensitivity, Parodontax for gum health — and these positions are reinforced by decades of published clinical evidence, dental association recommendations, and consumer reporting archives. AI systems are not guessing; they are synthesizing a deeply indexed knowledge base that strongly favors the incumbents.
The high brand count of 81 distinct mentions might suggest the opposite — that the market is fragmented and therefore fluid. But this interpretation is misleading. The 81 brands include a long tail of regional, pharmacy-own-label, and niche natural brands that collectively share less than half the total mentions. The structure is actually bimodal: a small group of clinically dominant brands with entrenched AI positions, and a large group of occasional mentions that appear only under very specific prompt conditions. This bimodal structure is a hallmark of mature AI category representation, where the top tier has effectively pre-answered the most common questions and made it difficult for others to displace them.
For brands currently in the middle or bottom tier, the window for organic repositioning is narrowing. The content sources that AI systems rely on — dental testing databases, pharmacist recommendation guides, long-form health journalism, clinical study repositories — are slow-moving and require years of consistent investment to influence. A brand that begins building structured clinical content, dentist endorsement programs, and review ecosystems today will see AI visibility improvements in 12 to 24 months. A brand that delays will find that the top tier's advantages compound as AI systems index more data and assign higher trust weights to brands already present in their training sources.
The zero-negative-sentiment rate across 15 of the 16 tracked brands is also a maturity signal. In emerging AI categories — cryptocurrency wallets, AI tools, certain fintech services — negative mentions are common because the knowledge base is thin and critical reviews dominate. In toothpaste, AI systems have access to enough depth that they can construct nuanced, balanced recommendations without resorting to the kind of "use with caution" framing that characterizes less well-documented categories. This means that brand reputation damage through AI channels is unlikely to be a near-term risk for most players — but it also means that the upside of AI visibility is increasingly winner-take-most for the brands already at the top of the stack.
The toothpaste category is already in a mature phase of AI representation — top positions are held by clinically credentialed incumbents and the structural gap is widening, not closing. Brands wanting to build meaningful AI visibility should act now, focusing on segment-specific clinical content and professional endorsement ecosystems before the window for organic positioning narrows further.
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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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