How AI Search Is Recommending Sunscreen Brands: Monthly Trends

Executive Summary

La Roche-Posay holds the recommendation coverage lead in October 2026 at 92.9% of qualified observations, extending its advantage over second-place CeraVe to 16.7 points. The month's defining feature is the separation that opened between the top of the field and the middle: La Roche-Posay, CeraVe, EltaMD, and Neutrogena all sit at or above 72.2%, while Supergoop fell to 52.2% and the brands below it remain far back.

CeraVe is the strongest upward mover with a full set of figures. Coverage rose 5.8 points from 70.4% in July to 76.2% in October, and the move from September was sharper still at Up 9.7 points. Top-three placement climbed 20.2 points to 48.9%, and rank-one placement rose 9.5 points to 20.1% (125 of 622 observations). La Roche-Posay also rose, Up 3.3 points from July to 92.9%, with top-three placement up 15.8 points to 72.0%.

Supergoop recorded the sharpest decline, Down 13.3 points from 65.5% in July to 52.2% in October, and Down 10.6 points from September alone. EltaMD extended a three-month downward streak, falling 7.3 points from 80.8% in July to 73.5%, while holding the category's strongest rank-one rate at 31.4%.

Against the prior month, the category was not stable. The benchmark recorded two significant risers and four significant decliners, with the qualified observation count rising from 522 in September to 622 in October. Across the full July-to-October series, La Roche-Posay has now held the lead in all four tracked months, but with a widening margin this month.

Each monthly run begins with 800 prompt-surface observations (653 unique questions in October 2026, 650 in July 2026) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor; 638 were relevant and 162 were irrelevant in October, versus 568 relevant and 232 irrelevant in July. The public metrics use the 622 qualified observations in October and the 557 in July that survive both qualification stages.

Key Findings

AI Response Inconsistency Alerts

Questions This Section Answers

• What conflicting product information did AI platforms give for EltaMD UV Clear, and how large was the gap?
• Which platforms disagreed, and did the answers cite any supporting sources?

One critical/high-severity factual inconsistency was detected this month, spanning two AI platforms.

EltaMD

AI platforms provided conflicting information about the price of EltaMD UV Clear at high severity. When asked "Which is the best sunscreen for acne prone skin?", ChatGPT stated the product costs $25.50 while Gemini stated $76.00. The same product cannot carry both prices, and the responses differed on the most directly comparable commercial attribute a buyer would use to evaluate the option. ChatGPT's answer referenced the American Academy of Dermatology's sunscreen guidance page ("How do I know if I'm using the right sunscreen?"); no source page was surfaced alongside Gemini's response. This is a pricing-class conflict, and it sits outside the brand recommendation cluster that the rest of this report measures.

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set, which rose from 557 observations in July to 622 in October.

September 2026 is the intermediate month in this series, with 522 qualified observations. The qualified set contracted in September and then expanded in October as fewer prompts were judged irrelevant to the category.

Benchmark-Level Metrics

The October answer mix returned toward recommendation-heavy output after September's dip to 69.0% recommendation-shaped and 85.6% valid shortlist share.

AI Recommendation Trend

Questions This Section Answers

• Which sunscreen brands separated from the middle of the field, and which fell back?
• How much ground did CeraVe gain on La Roche-Posay in October 2026?

A Widening Leader Gap and a Converging Middle

La Roche-Posay extended its lead in October while the brands immediately behind it split apart. CeraVe and EltaMD now sit close together in second and third, Neutrogena has closed on both, and Supergoop dropped away from that group.

Six of the nine tracked brands moved beyond normal month-to-month variation, so the category-level change came from several individually significant shifts rather than one dominant event.

What Changed This Month

Questions This Section Answers

• Which sunscreen brand recorded the sharpest recommendation decline, and was it a presence or placement problem?
• Which brand gained the most on top-three placement, and how much did it rise?
• Why did EltaMD's recommendation count rise even as its coverage rate fell?

La Roche-Posay

La Roche-Posay rose 3.3 points from 89.6% valid recommendation coverage in July to 92.9% in October, a significant gain within the tracked series, and climbed a further 9.2 points from September's 83.7%. The brand now holds 578 of 622 qualified observations, the largest valid recommendation count in the category.

Placement strengthened rather than presence. Raw mention presence held effectively flat at 95.8% versus 95.7% in July, while top-three rate rose 15.8 points to 72.0% and rank-one rate edged up 4.1 points to 18.8%.

The distinction to notice: La Roche-Posay is not appearing in materially more answers than it did in July. It is converting the answers it already appears in into shortlist placements at a much higher rate, which is why the leader gap widened even as CeraVe and Neutrogena improved.

Highest-priority diagnostic: Which prompt families moved La Roche-Posay into top-three placement this month, and which surfaces carry that placement most consistently?

Supergoop

Supergoop recorded the sharpest decline in the category, Down 13.3 points from 65.5% valid recommendation coverage in July to 52.2% in October, a significant decline, and Down 10.6 points from September's 62.8%. Valid recommendation count fell from 365 observations to 325.

The retreat was driven by presence. Raw mention presence fell 14.9 points from 68.9% to 54.0%, while top-three rate slipped 4.5 points to 26.4% and rank-one rate held essentially flat, up 0.4 points to 7.4%.

The distinction to notice: Supergoop appears in substantially fewer AI answers than it did in July, but where it does appear it still places. The loss is a coverage-of-answers problem, not a placement problem, which is the opposite of the pattern shown by La Roche-Posay.

Highest-priority diagnostic: Which prompt families stopped surfacing Supergoop entirely, and which brands appear in the answers where it is now absent?

CeraVe

CeraVe rose 5.8 points from 70.4% valid recommendation coverage in July to 76.2% in October, a significant gain, and Up 9.7 points from September's 66.5%, the largest single-month move recorded for the brand in this series. Valid recommendation count reached 474 observations.

The movement was concentrated in placement. Raw mention presence rose only 1.3 points to 79.6%, while top-three rate climbed 20.2 points to 48.9% and rank-one rate rose 9.5 points to 20.1% (125 observations).

The distinction to notice: CeraVe's presence was already strong in July. What changed is where it lands once mentioned, with top-three placement roughly two-thirds higher than at baseline. That is a different mechanism from a presence-led gain.

Highest-priority diagnostic: Which prompts moved CeraVe into top-three placement, and did those answers previously recommend La Roche-Posay or EltaMD?

EltaMD

EltaMD declined 7.3 points from 80.8% valid recommendation coverage in July to 73.5% in October, a significant decline, and Down 4.8 points from September's 78.3%. This is the brand's third consecutive monthly decline, tied for the longest downward streak in the category. Valid recommendation count fell from 450 observations to 457 (the count rose slightly even as the rate fell, because the qualified denominator expanded from 557 to 622).

The decline was entirely a presence effect. Raw mention presence fell 12.0 points from 86.4% to 74.4%. Top-three rate rose 2.9 points to 53.2% and rank-one rate held essentially flat at 31.4%, which remains the highest rank-one rate of any tracked brand.

The distinction to notice: EltaMD is mentioned in meaningfully fewer answers than in July, but in the answers where it appears it is recommended and placed at least as strongly as before. The brand lost reach, not standing.

Highest-priority diagnostic: Which prompt families dropped EltaMD from their answers, and was the drop concentrated on any single surface family?

Neutrogena

Neutrogena rose 3.3 points from 68.9% valid recommendation coverage in July to 72.2% in October, though this move falls short of a significant gain on its own. The move from September was significant at Up 6.1 points, continuing a two-month upward streak. Valid recommendation count reached 449 observations.

As with CeraVe, the gain was placement-led. Raw mention presence slipped 1.3 points to 75.7%, while top-three rate rose 15.6 points to 31.8% and rank-one rate edged up 2.2 points to 5.1%.

The distinction to notice: Neutrogena has now closed to within 1.3 points of EltaMD in overall coverage while trailing it by 26.3 points on rank-one placement. The two brands are near neighbours on shortlist inclusion and far apart on first position.

Highest-priority diagnostic: Which prompts moved Neutrogena into top-three placement, and which brands occupy rank one in those same answers?

Sun Bum

Sun Bum declined 4.6 points from 14.9% valid recommendation coverage in July to 10.3% in October, a significant decline, though the move from September was not significant at Down 1.6 points. Valid recommendation count fell from 83 observations to 64.

Raw mention presence fell 5.9 points to 12.4%, and top-three rate slipped 1.0 point to 2.2%. Rank-one rate held at roughly 0.8% across both months.

The distinction to notice: Sun Bum moves between roughly 9% and 15% coverage across the series without a durable trend, and its valid recommendation counts are small enough that a handful of observations shifts the rate. The baseline-to-current decline is real within the tracked set, but it reflects a brand operating on a thin base.

Highest-priority diagnostic: Which question types still surface Sun Bum, and do those answers place it or only mention it?

Vichy

Vichy declined 2.0 points from 3.6% valid recommendation coverage in July to 1.6% in October, a significant decline, and Down 0.3 points from September's 1.9%, a third consecutive monthly decline. Valid recommendation count fell from 20 observations to 10.

Raw mention presence fell 2.8 points to 2.1%. Top-three rate and rank-one rate each rose 0.1 point, to 0.5% and 0.3% respectively.

The distinction to notice: Vichy's percentage movement is proportionally large and its absolute counts are very small. Ten valid recommendations out of 622 observations is the entire basis of the current figure, and small counts make rates sensitive to single observations.

Highest-priority diagnostic: Which prompts still surface Vichy at all, and do those answers cluster on any particular surface family?

Kopari Beauty

Kopari Beauty recorded 0.0% valid recommendation coverage in October, Down 0.4 points from 0.4% in July, with zero valid recommendations across 622 qualified observations versus 2 in July. Raw mention presence fell 0.9 points to 0.0%, a significant decline on a large relative basis but a shift of a handful of observations.

The distinction to notice: Kopari Beauty has now been recorded at or near zero across the full series. Its presence in the qualified benchmark set is too thin to support a coverage narrative in either direction.

Highest-priority diagnostic: Which, if any, prompt surfaces mention Kopari Beauty, and are those mentions clustered in a specific product or use-case question type?

Cetaphil

Cetaphil moved Down 0.3 points from 32.0% valid recommendation coverage in July to 31.7% in October, a non-significant move, but the intervening months tell a different story. The brand fell to 27.8% in August and 20.1% in September before recovering Up 11.6 points in October, the largest single-month move recorded for the brand in this series. Valid recommendation count reached 197 observations.

The October gain was placement-led: raw mention presence slipped 2.7 points to 33.9%, while top-three rate rose 4.9 points to 14.8%.

The distinction to notice: on a baseline-to-current basis Cetaphil looks flat. The month-to-month path was not flat, and the current figure sits well above where September left it while remaining far below the top cluster.

Highest-priority diagnostic: Which prompts drove Cetaphil's September-to-October recovery, and which of those prompts had previously left the brand out?

Buyer-Intent Interpretation

Questions This Section Answers

• What types of sunscreen questions does the benchmark actually capture, and which ones does it miss?
• Can this benchmark answer price sensitivity or head-to-head sunscreen comparisons?

All 622 qualified observations in October fell into the Brand Recommendation cluster, as did all 557 in July. No qualified observations were recorded for pricing and value or multi-brand comparison questions in either month. The public benchmark therefore captures which brands AI recommends and in what order, but it cannot answer price sensitivity, value positioning, or head-to-head comparison questions for this category. The pricing inconsistency recorded between ChatGPT and Gemini this month is an exception surfaced through dedicated conflict detection, not part of the qualified recommendation set. Those commercial questions require dedicated prompt sets beyond the current discovery scope.

Brand Opportunity Summary

Questions This Section Answers

• Which sunscreen brands carry the strongest current signals, and which are declining?
• What specific diagnostic should each brand investigate next?

The benchmark identifies where attention is warranted across the category; a company-level analysis is needed to explain why these patterns emerged.

Evidence Behind the Benchmark

Questions This Section Answers

• What data builds the brand-level percentages, and what is the qualified denominator?
• Why should small-count brands like Kopari Beauty and Vichy be read alongside their absolute observation counts?

The aggregate metrics are built from prompt-level observations covering the query, the AI surface, the recommendation outcome, the rank position, sentiment, and citations where exposed. Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns behind these percentages; the benchmark describes the output distribution, not its cause. Source presence is not automatically treated as proof of causation.

Report-Specific Interpretation Notes

• Brand-level percentages are calculated within the qualified observations per month: 557 for July and 622 for October, not the 800 raw prompt-surface collections.
• Brands such as Kopari Beauty and Vichy operate on very few observations, so their percentage changes should be read alongside the absolute counts named in the sections above.
• All six canonical AI surface families carried at least one qualified observation in both months, so no surface was dropped or added between baseline and current.
• Month-over-month movement identifies changes worth investigating; it does not by itself establish the cause of those changes.

About This Benchmark

This report is part of the LLM Authority Index AI Visibility Market Discovery research program:

• AI Visibility Industry Market Methodology
• AI Visibility Industry Market Metrics
• AI Visibility Industry Market Standards

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

Beneath the aggregate percentage sit the questions that matter: which high-intent prompts does a brand win, which competitor takes the recommendation when a brand loses, what attributes do AI systems associate with each option, and which external sources shape those answers. Supergoop's 14.9-point drop in presence and EltaMD's 12.0-point drop raise the same unresolved question from opposite directions: which prompts and which surfaces moved, and who absorbed the answers. The benchmark shows the scoreboard; it does not reveal the plays that produced it.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. That analysis turns the current standings in this report into a concrete action plan.

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