Beauty and Personal Care AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Beauty and Personal Care benchmark compares 6 companies across 220 AI answers that met its inclusion rules. Bella Lash leads with 65 recommendations (29.55% of answers). At least one tracked company was recommended in 97 answers; some answers recommended several companies.

The rankings distinguish being mentioned from receiving an affirmative recommendation, then examine placement and the wording used about each company. Earlier monthly results show how counts and rates changed, with each month using its own answer total. These results describe the answers reviewed, not product quality or customer satisfaction. Differences between monthly samples limit comparisons and do not establish why a result changed.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Beauty and Personal Care

Industry leaderboard

Questions This Section Answers

• How do Beauty and Personal Care rank by recorded AI recommendations in November 2026?

The leaderboard orders companies by how many answers recorded an affirmative recommendation, so it measures endorsement volume rather than visibility alone. A company can appear often yet be recommended less often, and the two readings answer different questions.

Ties would require equal recommendation counts; near-equal counts should not be read as shared standing. Placement figures are nested inside recommendations, so first-place and shortlist results are subsets rather than separate wins.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Beauty and Personal Care answer sample recommend any tracked company?

97 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 201, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Every qualified answer mentioned at least one tracked company, but fewer than half recorded a recommendation for any of them. That gap separates appearance from endorsement: being named in an answer is not the same as being put forward.

Because one answer can recommend several companies, company-level recommendation totals exceed the number of answers carrying a recommendation. Answers without a tracked recommendation may still have named companies outside this comparison, so coverage here is bounded by the tracked set.

Reach and affirmative recommendation

Bella Lash ranks 1 by recommendation count. Mentions: 137 (62.27%); recommendations: 65 (29.55%). Top 3 placements: 53 (24.09%); first-place placements: 40 (18.18%).

Wording about the company: 74 positive, 63 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 47.4%. The net framing score was 0.54 (defined in Methodology).

72 mentions had no recorded recommendation. Of recorded recommendations, 81.54% were Top 3 and 61.54% were first-place.

Bella Lash leads on recommendation count, but its mentions outnumber its recommendations considerably, so reach and endorsement diverge. The recommendation-to-mention ratio describes how often a mention in the recorded answers also carried an affirmative endorsement; it is not a conversion measure.

A ranking by recommendation count does not by itself establish a unique winner where counts are close. Placement counts sit inside recommendations, so they refine order rather than add to it.

Recommendation order and placement

Placement describes where a recommended company appeared in an answer's ordering. Shortlist placements include first-place placements, and both are subsets of recommendations, so they should be read as layers of the same endorsement rather than as separate achievements.

Ratios of recommendations to mentions vary widely across companies, and a high ratio on a small mention base is less stable than one on a larger base. These figures describe recorded answer wording, not customer behavior.

Classified framing in context

Framing classifies the wording surrounding a mention as positive, neutral or negative. It is not a measure of customer sentiment, product quality or reputation, and neutral wording is common across the tracked companies.

Positive framing does not explain why a recommendation was or was not recorded. The net framing score summarizes the balance of positive and negative wording within the selected answers only, and no negative mentions were recorded for any tracked company this month.

Company results in detail

Bella Lash

Questions This Section Answers

• What do the November 2026 AI answer results show about Bella Lash mentions, recommendations and placement?

Bella Lash ranks 1 by recommendation count. Mentions: 137 (62.27%); recommendations: 65 (29.55%). Top 3 placements: 53 (24.09%); first-place placements: 40 (18.18%).

Wording about the company: 74 positive, 63 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 47.4%. The net framing score was 0.54 (defined in Methodology).

72 mentions had no recorded recommendation. Of recorded recommendations, 81.54% were Top 3 and 61.54% were first-place.

From October 2026 to November 2026, Bella Lash's mention count fell from 139 to 137, while its recommendation count fell from 131 to 65. The recommendation rate was 47.99% and 29.55% respectively.

Bella Lash holds the top recommendation count, with mentions well ahead of recommendations, so much of its visibility did not carry an endorsement. Its recorded wording was positive or neutral, never negative, and most of its recommendations landed in shortlist or first-place positions.

Compared with the earlier snapshot, both its mention and recommendation counts were lower, and its recommendation rate also fell. The samples differ between months, so the comparison shows what was recorded without establishing why.

Sugarlash PRO

Questions This Section Answers

• What do the November 2026 AI answer results show about Sugarlash PRO mentions, recommendations and placement?

Sugarlash PRO ranks 2 by recommendation count. Mentions: 90 (40.91%); recommendations: 48 (21.82%). Top 3 placements: 38 (17.27%); first-place placements: 18 (8.18%).

Wording about the company: 53 positive, 37 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 53.3%. The net framing score was 0.59 (defined in Methodology).

42 mentions had no recorded recommendation. Of recorded recommendations, 79.17% were Top 3 and 37.50% were first-place.

From October 2026 to November 2026, Sugarlash PRO's mention count rose from 78 to 90, while its recommendation count fell from 71 to 48. The recommendation rate was 26.01% and 21.82% respectively.

Sugarlash PRO ranks second on recommendations and shows a comparatively high share of mentions that also carried an endorsement. Its recorded wording was positive or neutral throughout, and a substantial portion of its recommendations appeared in shortlist positions.

Its mention count rose from the earlier snapshot while its recommendation count and recommendation rate were lower. Because the monthly samples differ, these movements are reported as recorded changes rather than as evidence of cause.

Lashbox LA

Questions This Section Answers

• What do the November 2026 AI answer results show about Lashbox LA mentions, recommendations and placement?

Lashbox LA ranks 3 by recommendation count. Mentions: 113 (51.36%); recommendations: 45 (20.45%). Top 3 placements: 35 (15.91%); first-place placements: 19 (8.64%).

Wording about the company: 52 positive, 61 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 39.8%. The net framing score was 0.46 (defined in Methodology).

68 mentions had no recorded recommendation. Of recorded recommendations, 77.78% were Top 3 and 42.22% were first-place.

From October 2026 to November 2026, Lashbox LA's mention count fell from 150 to 113, while its recommendation count fell from 132 to 45. The recommendation rate was 48.35% and 20.45% respectively.

Lashbox LA ranks third on recommendations despite a mention count above Sugarlash PRO's, reflecting a lower share of mentions that carried an endorsement. Its wording was positive or neutral, with neutral mentions outnumbering positive ones.

Both its mention and recommendation counts were lower than in the earlier snapshot, and its recommendation rate declined as well. The comparison is between separate samples, so it does not establish why the recorded results moved.

Paris Lash Academy

Questions This Section Answers

• What do the November 2026 AI answer results show about Paris Lash Academy mentions, recommendations and placement?

Paris Lash Academy ranks 4 by recommendation count. Mentions: 42 (19.09%); recommendations: 24 (10.91%). Top 3 placements: 14 (6.36%); first-place placements: 2 (0.91%).

Wording about the company: 26 positive, 16 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 57.1%. The net framing score was 0.62 (defined in Methodology).

18 mentions had no recorded recommendation. Of recorded recommendations, 58.33% were Top 3 and 8.33% were first-place.

From October 2026 to November 2026, Paris Lash Academy's mention count fell from 61 to 42, while its recommendation count fell from 49 to 24. The recommendation rate was 17.95% and 10.91% respectively.

Paris Lash Academy ranks fourth on recommendations but records one of the higher shares of mentions that also carried an endorsement, a ratio resting on a smaller mention base than the leaders. Its wording was positive or neutral, and first-place placements were rare relative to its shortlist placements.

Its mention and recommendation counts and its recommendation rate were all lower than in the earlier snapshot. The samples differ between months, so no cause is inferred.

Borboleta Pro

Questions This Section Answers

• What do the November 2026 AI answer results show about Borboleta Pro mentions, recommendations and placement?

Borboleta Pro ranks 5 by recommendation count. Mentions: 27 (12.27%); recommendations: 14 (6.36%). Top 3 placements: 9 (4.09%); first-place placements: 5 (2.27%).

Wording about the company: 14 positive, 13 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 51.9%. The net framing score was 0.52 (defined in Methodology).

13 mentions had no recorded recommendation. Of recorded recommendations, 64.29% were Top 3 and 35.71% were first-place.

From October 2026 to November 2026, Borboleta Pro's mention count fell from 36 to 27, while its recommendation count fell from 30 to 14. The recommendation rate was 10.99% and 6.36% respectively.

Borboleta Pro ranks fifth, with a moderate share of its mentions carrying an endorsement and wording that was positive or neutral. Its recommendations were more often shortlisted than placed first.

Its mention count, recommendation count and recommendation rate were all lower than in the earlier snapshot. That comparison rests on separate monthly samples, so it describes recorded change without explaining it.

London Lash pro

Questions This Section Answers

• What do the November 2026 AI answer results show about London Lash pro mentions, recommendations and placement?

London Lash pro ranks 6 by recommendation count. Mentions: 25 (11.36%); recommendations: 5 (2.27%). Top 3 placements: 4 (1.82%); first-place placements: 2 (0.91%).

Wording about the company: 5 positive, 20 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 20.0%. The net framing score was 0.20 (defined in Methodology).

20 mentions had no recorded recommendation. Of recorded recommendations, 80.00% were Top 3 and 40.00% were first-place.

From October 2026 to November 2026, London Lash pro's mention count fell from 34 to 25, while its recommendation count fell from 23 to 5. The recommendation rate was 8.42% and 2.27% respectively.

London Lash pro ranks sixth, and its mentions only occasionally carried an endorsement, the lowest such share among the tracked companies. Its wording was mostly neutral, with few positive mentions and none negative.

Its mention and recommendation counts and its recommendation rate were lower than in the earlier snapshot. With a small recommendation base, its placement proportions should be read cautiously, and the monthly samples differ.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Beauty and Personal Care snapshots from July 2026 to November 2026 differ in recommendation coverage and measurement scope?

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

The earlier snapshot and the current month are separate samples of AI answers, with different answer totals, so counts and rates are not directly interchangeable across them. Rank positions can shift when counts move, and a changed rate does not by itself demonstrate improvement, loss of standing or the effect of any intervention.

The comparison shows how the recorded results differed between the two months; it does not establish why they differed.

What the November Rankings Show

The November results answer several distinct questions. Reach asks how often a company appeared at all; recommendation asks whether an answer affirmatively endorsed it; placement asks where an endorsed company sat in the ordering; and framing describes the wording around a mention. Each measure can move independently of the others.

A company with wide reach but a modest endorsement share is visible without being consistently put forward, while a company with a high endorsement share on a small base carries more uncertainty. Placement layers refine recommendations rather than adding to them, and framing is not sentiment or quality. Read together, these measures describe the selected answers, not the market, customers or the companies themselves.

Methodology

Questions This Section Answers

• How were the November 2026 Beauty and Personal Care AI visibility measures counted, and what do they not establish?

This benchmark has partial coverage: 2 of 3 planned question categories contributed usable observations; 1 contributed none. This describes question-category coverage, not demonstrated platform outages. Findings apply to the available answer set.

The month in the title is the reporting period. The exact dates when the original AI answers were collected have not been verified.

Each company is counted at most once in each answer that meets the benchmark rules. A recommendation requires both an affirmative endorsement and positive wording. Mention, recommendation, Top 3 and first-place rates use the full benchmark answer total. Top 3 and first-place results are included within recommendations, not added to them.

The recommendation-to-mention ratio divides recommendations by mentions. It describes AI answer wording, not customer conversion. Net framing is positive minus negative mentions, divided by all mentions, on a scale from -1 to +1. It does not measure customer satisfaction or company quality.

Market: US; 6 tracked companies. AI services represented: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity.

Research screening totals (answer observations can include repeated questions):

The source does not provide a reader-facing definition of “reserved”; that screening label is reported without inferring a reason for exclusion. Only the included benchmark answers form the rate denominator.

One answer can mention or recommend several companies. Adding company totals would therefore count some answers more than once. The results describe the AI answers reviewed, not independently verified facts about the companies or their products.

Monthly sample coverage:

July 2026 measured a different set of companies, so it is excluded from this comparison. August 2026 measured a different set of companies, so it is excluded from this comparison. September 2026 measured a different set of companies, so it is excluded from this comparison.

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

Coverage is partial: only some planned question categories contributed usable answers, and the exact collection dates for the original AI answers are unverified. The reporting month is a label for the period, not a guarantee of when answers were gathered.

Each company is counted at most once per answer, and a recommendation requires both affirmative endorsement and positive wording. Rates use the full benchmark answer total, and one answer can name several companies, so company totals should not be summed. Net framing is a wording balance, not customer satisfaction or company quality. Monthly samples differ, so comparisons show recorded change without establishing cause.