CiteWorks Studio

How AI Search Is Recommending Body Care Brands: Monthly Trends

Benchmark-Based Industry Analysis | Powered by LLM Authority Index

Mark HuntleyBy Mark HuntleyFounder and CEO
8 minutes read

Key Takeaways

  • CeraVe led September 2026 body care recommendations at 87.5% coverage, maintaining a 7.8-point lead over Neutrogena.
  • Kiehl's fell to 39.0% coverage, down 5.8 points from August and 12.7 points from July, marking a second consecutive significant decline.
  • Neutrogena held second at 79.7%, with lower overall coverage but stronger top-three placement in the answers where it appeared.
  • September's qualified benchmark shrank to 518 observations after more prompts were filtered as irrelevant, affecting brand-level percentages across the category.

Executive Summary

CeraVe remains the category leader in AI-driven body care recommendations at 87.5% valid recommendation coverage in September 2026, though the margin is narrowing. Neutrogena holds second at 79.7%, down 1.4 points from August, leaving the leader with a 7.8-point advantage. The leader's position is stable, but the gap to the field has compressed slightly.

The most material story this month is the continued decline of Kiehl's. The brand fell another 5.8 points from August to September, reaching 39.0% valid recommendation coverage, and its cumulative drop of 12.7 points from July is now significant. This marks the second consecutive month of significant decline for Kiehl's, moving beyond normal month-to-month variation. Neutrogena also registered a significant 4.9-point decline from July to September, down to 79.7%, though its month-over-month movement was within expected bounds.

No brand posted a significant rise in coverage this month. The category's most notable upward signals came in placement quality rather than reach. Billie appeared in one qualified recommendation in September after two months with none, and Origins gained rank-one appearances from zero to 0.4%. The steady competitive cluster moved within a narrow band, while the two significant decliners shaped the month's direction.

Each monthly benchmark run begins with 800 prompt-surface observations across the defined AI/search surface universe (660 unique questions in July, 700 in August, 697 in September). Of those, 800 mentioned a tracked brand or competitor; 665 were relevant and 135 were irrelevant in July, versus 690 relevant and 110 irrelevant in August, and 585 relevant and 215 irrelevant in September. The public metrics are drawn from the 623 qualified observations in July, 634 in August, and 518 in September that survived both qualification stages. The smaller September denominator follows a larger irrelevant-prompt filter.

AI recommendation trend

valid recommendation coverage, Jul 2026 to Sep 2026

0%25%50%75%100%Jul 2026Aug 2026Sep 2026
  • CeraVe87.5%
  • Neutrogena79.7%
  • Cetaphil70.5%
  • Kiehl’s39.0%
  • Sun Bum4.2%
  • Origins2.9%
  • Billie0.2%
  • Kopari Beauty0.2%

Key Findings

Signal

September 2026 finding

Category leader

CeraVe at 87.5% valid recommendation coverage

Second place

Neutrogena at 79.7%, down 1.4 points from August

Largest riser

No brand posted a significant rise in coverage

Largest decliner

Kiehl's down 5.8 points from August, a 12.7-point drop from July

Top-three prominence

Neutrogena up 6.1 points from July to 48.5%

Smallest presence

Billie at 0.2% coverage with 1 valid recommendation in September

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.

Research stage

Jul 2026

Sep 2026

What it represents

Source prompt-surface observations collected

800

800

Total prompts run across the surface universe

Unique questions

660

697

Distinct questions after de-duplication

Brand / competitor mentions

800

800

Prompts mentioning a tracked brand or competitor

Relevant prompts

665

585

Prompts relevant to the benchmark

Irrelevant prompts

135

215

Prompts filtered out as irrelevant

Qualified benchmark observations

623

518

Public denominator after qualification

Qualified surface breadth

6

6

AI surface families with at least one qualified observation

The August intermediate month saw 690 relevant prompts, 110 irrelevant, and 634 qualified observations. These benchmark-level figures set the context for the brand-level standings that follow.

Benchmark-Level Metrics

Metric

Jul 2026

Sep 2026

Change

Qualified observations

623

518

Down 105

Companies tracked

8

8

Flat

Recommendation-shaped answer share

67.9%

67.6%

Down 0.3 points

Valid recommendation shortlist share

90.2%

87.3%

Down 2.9 points

Category leader by coverage

CeraVe (90.8%)

CeraVe (87.5%)

Leader stable

The qualified observation count fell in September, and the valid recommendation shortlist share also dipped. Brand-level percentages reflect a smaller, more tightly filtered denominator than in prior months.

AI Recommendation Trend

Significant Declines for Two Brands Reshape the Mid-Tier

Brand

Jul 2026

Sep 2026

Movement

Sep 2026 rank

Billie

0.0%

0.2%

Up 0.2 points

8th

CeraVe

90.8%

87.5%

Down 3.3 points

1st

Cetaphil

73.2%

70.5%

Down 2.7 points

3rd

Kiehl's

51.7%

39.0%

Down 12.7 points

4th

Kopari Beauty

0.5%

0.2%

Down 0.3 points

7th

Neutrogena

84.6%

79.7%

Down 4.9 points

2nd

Origins

4.2%

2.9%

Down 1.3 points

6th

Sun Bum

4.8%

4.2%

Down 0.6 points

5th

CeraVe's leadership held steady across the period, but Kiehl's and Neutrogena both recorded cumulative declines that moved beyond normal month-to-month variation, compressing the competitive cluster behind the leader into a narrower band between second-place Neutrogena (79.7%) and third-place Cetaphil (70.5%). The remaining brands shifted within expected bounds across the July-to-September window; the August intermediate month put Kiehl's at 44.8% and Neutrogena at 81.1%, showing a continuous downward path for both.

What Changed This Month

Kiehl's

Kiehl's recorded its second consecutive significant decline, reaching 39.0% valid recommendation coverage in September. This is down 5.8 points from August's 44.8% and 12.7 points from July's 51.7%, a cumulative drop that moved well beyond normal month-to-month variation. The brand remains in fourth place, but its position relative to the leaders has deteriorated.

Raw mention presence fell in parallel, from 56.7% in July to 44.2% in September, a 12.5-point decline. The coverage loss tracks a broader reduction in how often Kiehl's appears in AI-generated answers at all.

The brand did not convert its remaining appearances into rank-one recommendations. Its top-three rate fell from 28.9% to 20.8%, while rank-one appearances held roughly flat at 2.3%. Kiehl's had 202 valid recommendations in September, down from 284 in August and 322 in July.

Highest-priority diagnostic: Which prompts that previously surfaced Kiehl's in top positions now omit it, and which competitor is capturing those recommendation slots?

Neutrogena

Neutrogena holds second place, but its cumulative coverage decline is significant. Valid recommendation coverage fell from 84.6% in July to 79.7% in September, a 4.9-point drop that moved beyond normal month-to-month variation across the period. The August-to-September movement of 1.4 points was within normal variation, meaning the bulk of the shift occurred earlier in the series.

Placement quality tells a different story. Neutrogena's top-three rate rose from 42.4% in July to 48.5% in September, a 6.1-point gain. Rank-one appearances held flat at 8.7%.

Neutrogena is recommended in fewer answers overall, but in the answers where it appears, it is positioned at the top of the list more often. The brand had 413 valid recommendations in September, down from 514 in August.

Highest-priority diagnostic: Which surfaces or prompt categories drove the earlier coverage loss, and is the improvement in placement concentrated in specific high-intent answer types?

CeraVe

CeraVe remains the coverage leader at 87.5% in September, but its cumulative decline from 90.8% in July is worth noting. The 3.3-point drop remained within normal month-to-month variation, and the 2.4-point move from August was also within normal variation.

The leader's placement strength held. Top-three rate rose from 65.8% in July to 67.4% in September, and rank-one appearances improved from 44.5% to 46.0%. Raw mention presence actually rose slightly from 97.4% to 97.9%.

CeraVe is appearing in slightly fewer recommendation lists, but its grip on top positions within those lists has strengthened. The brand had 453 valid recommendations in September, down from 570 in August as the qualified denominator contracted.

Highest-priority diagnostic: Is the coverage decline a function of the smaller September denominator, or are specific prompt categories beginning to favor a different brand?

Billie and Small-Count Movers

Billie appeared in one qualified recommendation in September, reaching 0.2% coverage after two consecutive months at zero. The single recommendation was also a rank-one appearance. This is a small-count movement, and the August figure of zero presentations means the baseline comparison starts from nothing.

Origins gained ground on placement even as coverage declined. Its rank-one rate moved from 0.0% in July to 0.4% in September, and top-three rate rose from 1.0% to 1.5%. The brand had 15 valid recommendations in September, down from 26 in July. Sun Bum held roughly steady at 4.2% coverage with 22 valid recommendations.

Kopari Beauty remains at minimal presence with 0.2% coverage and 1 valid recommendation in September. For these small-count brands, a change of a few points can represent only a handful of answers, so the percentages should be read with that context.

Highest-priority diagnostic: For Billie, which prompt generated the first qualified recommendation, and can that pattern be replicated across similar prompts?

Buyer-Intent Interpretation

Buyer-intent cluster

What it captures

Strategic question

Brand Recommendation

AI answers that recommend a specific brand or product

Which brands earn the top recommendation slot when a buyer asks for a product?

Pricing & Value

AI answers that address cost, value, or price comparison

Which brands are positioned as the value or price leader in AI answers?

Multi-Brand Comparison

AI answers that compare two or more brands head-to-head

Which brands win direct comparison prompts, and which are omitted?

In September 2026, all 518 qualified observations fell into the Brand Recommendation cluster. The benchmark surfaced no qualified observations for pricing, value, or head-to-head comparison questions in July, August, or September. The public benchmark cannot yet answer which brand AI positions as the value option, the premium option, or the winner of a direct brand comparison.

Brand Opportunity Summary

Brand

Sep 2026 coverage

Current signal

Highest-priority diagnostic

Billie

0.2%

First qualified recommendation after two zero months

Which prompt generated the single recommendation, and can it be replicated?

CeraVe

87.5%

Leader with stable top-three prominence

Which prompt categories are beginning to favor a competitor?

Cetaphil

70.5%

Third place, stable with slight decline

Where is Cetaphil losing rank-one appearances to the leader?

Kiehl's

39.0%

Significant two-month decline, still fourth

Which prompts dropped Kiehl's, and which competitor captured those recommendations?

Kopari Beauty

0.2%

Minimal presence, 1 valid recommendation

What prompts generate the few recommendations Kopari does receive?

Neutrogena

79.7%

Second place, coverage down but placement quality up

Which surfaces drove the earlier coverage loss, and which competitor benefits?

Origins

2.9%

Low single-digit coverage with improving placement

Which prompt types produce Origins recommendations, and why is presence so narrow?

Sun Bum

4.2%

Low single-digit coverage, stable

Which seasonal or product-specific prompts drive Sun Bum's mentions?

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

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

Report-Specific Interpretation Notes

  • Small-count movement: Brands like Billie, Kopari Beauty, Origins, and Sun Bum have small absolute counts. Their percentage movements should be read with that context; a change of a few points can represent only a handful of answers.
  • Qualified denominator: Percentages are calculated within the qualified benchmark set (518 observations in September), not the raw collection of 800 prompts. The September denominator contracted as more prompts were filtered as irrelevant, which affects brand-level percentages.
  • Directional analysis: Month-over-month movement identifies changes worth investigating, but it does not by itself establish the cause of those changes. A brand appearing more or less often in AI answers can reflect shifts in the underlying evidence sources, model behavior, or prompt mix.

Next Step

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

The aggregate percentages above raise questions that the benchmark alone cannot answer. Which high-intent prompts does a brand win, and which does it lose? When a brand is not recommended first, which competitor takes the top slot? What attributes do AI systems associate with each option, and which external sources are shaping those answers?

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. Where the benchmark shows a signal, the audit shows the cause and the path to change.

Request an AI visibility audit

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Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
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About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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