Borboleta Pro AI Visibility Market Strategy Report - Beauty and Personal Care

Answer Capsule

Borboleta Pro holds 11.0% valid recommendation coverage in the October 2026 Beauty and Personal Care benchmark, ranking fifth of six tracked brands. The brand is visible but under-recommended: it appears in 13.2% of qualified observations yet converts that presence into a top-three placement only 6.2% of the time and a first-choice recommendation just 0.7% of the time. The clearest win is a two-month streak of significant coverage gains, up 5.6 percentage points from the July 2026 baseline. The clearest weakness is first-choice conversion, where Borboleta Pro ranks last among tracked brands. The clearest opportunity is closing the gap between presence and placement in the category's single measured buyer-intent cluster.

Who This Report Is For

This report is written for Borboleta Pro leadership, brand and growth teams, and category analysts who need to understand where the brand stands in AI-generated recommendations for professional lash and beauty supplies, and which prompt, page, and citation layers are most likely to change that position.

Report Card

Executive Summary

Borboleta Pro is present in the AI recommendation layer but is not yet a first-choice brand within it. Across 273 qualified observations in October 2026, the brand was mentioned 36 times, received 30 valid recommendations, and appeared in a top-three position 17 times. It was named first just twice. That is a 13.2% raw mention presence rate against a 0.7% rank-one rate, a ratio that shows the brand is being surfaced as context far more often than it is being chosen.

The category itself moved in Borboleta Pro's favor at the aggregate level. The benchmark's recommendation-shaped answer share rose from 50.0% in July 2026 to 78.4% in October 2026, and the valid recommendation shortlist share rose from 57.3% to 83.2%. AI systems are producing more recommendation-shaped answers than they were at baseline, which means the recommendation layer is becoming a larger share of the discovery surface. Borboleta Pro's coverage rose 5.6 percentage points over the same period, from 5.4% to 11.0%, a move the benchmark classifies as significant against a 4.5-point threshold and the second consecutive month of significant gain.

The strongest signal for the brand is on ChatGPT. Borboleta Pro holds a 16.7% valid recommendation coverage rate there, above its 11.0% overall rate, with 4 valid recommendations out of 24 observations and a 0.6667 net sentiment score. The weakest platform signal is Google AI Mode, where the brand holds a 1.8% coverage rate on 56 observations, the largest single platform sample in the dataset. That is the clearest platform gap in the brand's profile.

The clearest cluster gap is structural rather than competitive. All 273 qualified observations fell into the Brand Recommendation cluster. The benchmark's Pricing and Value and Multi-Brand Comparison clusters carried zero qualified observations in October 2026, so the public metrics cannot yet show how Borboleta Pro performs when a buyer asks about cost or asks AI systems to compare two brands directly. Those are the prompt types closest to a purchase decision, and they are currently unmeasured.

Against the category leaders, the gap is wide and specific. Lashbox LA holds 48.4% valid recommendation coverage and a 20.5% rank-one rate. Bella Lash holds 48.0% coverage and a 9.9% rank-one rate. Borboleta Pro's 0.7% rank-one rate places it last among the six tracked brands on first-choice placement, behind London Lash pro at 3.3% and Paris Lash Academy at 3.7%. The brand is being shortlisted occasionally and chosen almost never.

The most important caveat in this report is scale. Borboleta Pro's 11.0% coverage rests on 30 valid recommendations. A single prompt moving in or out of the shortlist shifts the percentage by roughly a third of a point. The two-month streak is directionally consistent, but it is small in absolute terms and should be read as a signal to investigate rather than a settled trend.

What Borboleta Pro Is Winning

Questions This Section Answers

• What evidence supports Borboleta Pro's two-month coverage streak?
• Where does Borboleta Pro convert best on ChatGPT?
• How does Borboleta Pro's sentiment compare to the other lash brands?

The clearest evidence-backed win is the two-month coverage streak. Borboleta Pro rose from 5.4% valid recommendation coverage in July 2026 to 11.0% in October 2026, a 5.6 percentage point gain that the benchmark classifies as significant against a 4.5-point threshold. The prior-month move, from 5.9% in September 2026, was 5.1 points and also significant. Two consecutive significant gains on a small base is the pattern the benchmark flags as worth watching.

The second win is platform-specific strength on ChatGPT. Borboleta Pro holds a 16.7% valid recommendation coverage rate on ChatGPT, above its 11.0% overall rate, with 4 valid recommendations across 24 observations. Its net sentiment score on that platform is 0.6667, and its average recommended rank there is 3.75. ChatGPT is not the largest platform sample in the dataset, but it is the one where the brand's recommendation conversion is strongest relative to its own baseline.

The third win is the absence of negative framing. Borboleta Pro recorded zero negative mentions across all 273 qualified observations. Its 36 mentions split into 30 positive and 6 neutral, producing a net sentiment score of 0.8333. That places it mid-pack in the category, above London Lash pro at 0.6765 and Paris Lash Academy at 0.8033, and below Bella Lash at 0.9568 and Sugarlash PRO at 0.9231. The brand is not being framed negatively anywhere in the measured set.

Beyond those three signals, the wins are thin. Borboleta Pro does not lead any platform, any cluster, or any placement metric. The brand's average recommended rank of 3.0769 is the weakest in the tracked set, behind London Lash pro at 2.2381 and Paris Lash Academy at 2.7778. The report states this plainly rather than overstating the streak.

Where Borboleta Pro Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why does Borboleta Pro convert presence into top-three placement less than half as often as Lashbox LA and Bella Lash?
• Which platforms account for Borboleta Pro's first-choice gaps despite large observation samples?
• What decision-layer prompts are currently unmeasured for Borboleta Pro?

The defining gap is conversion from presence to placement. Borboleta Pro appears in 13.2% of qualified observations but converts into a top-three placement only 6.2% of the time and a first-choice recommendation just 0.7% of the time. Bella Lash, by comparison, holds a 50.9% presence rate and converts it into a 39.6% top-three rate and a 9.9% rank-one rate. Lashbox LA converts a 54.9% presence rate into a 39.9% top-three rate and a 20.5% rank-one rate. The leaders convert presence into top-three placement at roughly three-quarters of their presence rate. Borboleta Pro converts at roughly half.

The second gap is first-choice displacement. Borboleta Pro was named first in 2 of 273 qualified observations. Lashbox LA was named first 56 times. Bella Lash was named first 27 times. Sugarlash PRO, which sits third in coverage at 26.0%, was named first 12 times. Even London Lash pro, which holds lower coverage than Borboleta Pro at 8.4%, was named first 9 times. On the metric closest to a buyer's actual decision, Borboleta Pro is last in the category.

The third gap is platform concentration. Borboleta Pro's coverage is unevenly distributed. On Google AI Mode, the largest single platform sample at 56 observations, the brand holds a 1.8% valid recommendation coverage rate and a 0.0% rank-one rate. On Google AI Overviews, at 120 observations, it holds a 12.5% coverage rate and a 0.0% rank-one rate. Those two surfaces account for the majority of the measured observation base, and on neither does the brand convert presence into a first-choice placement. The ChatGPT strength is real but sits on a 24-observation sample.

The fourth gap is the unmeasured decision layer. All 273 qualified observations fell into the Brand Recommendation cluster. The benchmark recorded zero qualified observations for Pricing and Value and zero for Multi-Brand Comparison. That means the public metrics cannot show whether Borboleta Pro wins or loses when a buyer asks AI systems to compare two brands head to head, or when a buyer asks which option offers the best value. Those are the prompt types where a shortlist becomes a decision, and the brand's position there is currently unknown.

Biggest Opportunity

Questions This Section Answers

• Why is converting existing presence in the Brand Recommendation cluster Borboleta Pro's clearest opportunity?
• How could moving Borboleta Pro's average recommended rank inside the top three lift its placement without new presence?
• Which prompts define the surface where Borboleta Pro's conversion work would happen?

The single clearest opportunity is to convert Borboleta Pro's existing presence into top-three and first-choice placement within the Brand Recommendation cluster, the only cluster the benchmark currently measures. The brand is already being mentioned in 13.2% of qualified observations. It is not being placed. Closing that conversion gap is a narrower and more tractable problem than building presence from zero, because the brand is already inside the answer layer.

The specific path runs through the prompts where the brand appears but is not ranked. Borboleta Pro's average recommended rank of 3.0769 shows that when it does receive rank credit, it typically lands just outside the top three. Moving from an average rank of roughly third to an average rank inside the top three would lift the top-three rate materially without requiring any new presence. The prompt examples in the dataset, including "lash tech," "lash maps," "classic lashes," "mega volume lashes," "What is the best lash curl to use?," "lash tweezers," "lash extension kit," "brown lashes," "eyelash remover," and "lash cleanser," define the surface where that conversion work would happen.

The second-order opportunity is ChatGPT. It is the platform where Borboleta Pro already converts best, at a 16.7% coverage rate, and where its average recommended rank of 3.75 is closest to the top three. Strengthening the source and citation layer that ChatGPT draws on for these prompts is the most direct route to lifting the brand's overall placement profile.

Competitive Landscape

Questions This Section Answers

• Where does Borboleta Pro rank against Lashbox LA, Bella Lash, and the other tracked brands on top-three and rank-one rates?
• How does Borboleta Pro's average recommended rank and sentiment compare within the category?

Lashbox LA and Bella Lash hold recommendation-stage strength in the Beauty and Personal Care category, sitting within 0.4 percentage points of each other at the top of the table. Borboleta Pro sits fifth of six tracked brands, ahead of London Lash pro on coverage but behind it on first-choice placement.

Average recommended rank covers rank-eligible recommendations only.

Borboleta Pro's top-three rate of 6.23% is the second-lowest in the tracked set, marginally behind London Lash pro at 6.59%. Its rank-one rate of 0.73% is the lowest of any tracked brand. Its average recommended rank of 3.08 is the weakest in the table, meaning that when the brand does receive rank credit, it lands further down the list than any competitor. Its sentiment score of 0.8333 sits fourth of six, above London Lash pro and Paris Lash Academy and below the three brands ahead of it on coverage.

Prompt Evidence

ChatGPT / Brand Recommendation Prompt: "lash extension kit" Result: Borboleta Pro received valid recommendation credit on ChatGPT, where its coverage rate of 16.7% is the strongest of any platform in its profile.

Google AI Mode / Brand Recommendation Prompt: "What is the best lash curl to use?" Result: Borboleta Pro recorded a 1.8% valid recommendation coverage rate on Google AI Mode across 56 observations, with no first-choice placements on that surface.

Google AI Overviews / Brand Recommendation Prompt: "mega volume lashes" Result: Borboleta Pro appeared in 15 of 120 AI Overviews observations but converted none of them into a first-choice recommendation, holding a 0.0% rank-one rate on the platform.

Perplexity / Brand Recommendation Prompt: "lash tech" Result: Borboleta Pro received 1 valid recommendation across 4 Perplexity observations, with an average recommended rank of 3.0 and no first-choice placement.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map every prompt where Borboleta Pro appears but is not ranked, and identify which competitor takes the recommendation when the brand is displaced.

Phase 2: Recommendation Readiness Plan Prioritize the prompts where the brand's average recommended rank sits just outside the top three, since those are the shortest path from presence to placement.

Phase 3: Owned Answer Layer Buildout Strengthen the owned pages that answer the category's core prompts, particularly the product and application pages tied to lash kits, lash maps, and lash curl selection.

Phase 4: Citation / Authority Layer Development Build the source footprint that AI systems retrieve for these prompts, with attention to the platforms where the brand currently converts best and the surfaces where it does not convert at all.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track coverage, top-three rate, rank-one rate, and average recommended rank month over month, with the small-base caveat applied to every reading.

Why This Matters

Questions This Section Answers

• Why is AI presence alone not a business outcome for Borboleta Pro?
• Which prompt, page, and citation layers should Borboleta Pro correct to convert mentions into first-choice recommendations?

AI presence alone is not a business outcome. A brand can be mentioned in a third of relevant answers and still be chosen in almost none of them. Borboleta Pro's profile shows exactly that pattern: 36 mentions, 30 valid recommendations, 17 top-three placements, and 2 first-choice recommendations. The distance between those numbers is the distance between being known and being selected.

The next move is targeted correction of the prompt, page, and citation layers that determine placement. The brand does not need to build presence from zero. It needs to convert the presence it already has into top-three and first-choice positions, starting with the prompts where its average recommended rank already sits closest to the top three.

Core Metrics

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Borboleta Pro in October 2026, that is (30 × 1 + 6 × 0 + 0 × -1) / 36, which produces a score of 0.8333.

This matters because unclassified mention counts are misleading. A brand with 36 mentions and no sentiment classification looks identical whether those mentions are enthusiastic recommendations, neutral references in a list, or cautionary notes. Borboleta Pro's 36 mentions break down into 30 positive and 6 neutral, with no negative framing anywhere in the measured set. That is a healthy framing profile.

Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal in commercial value. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, because the difference between being recommended and being listed is the difference between being chosen and being passed over. Borboleta Pro's sentiment is strong; its placement is not. Those two facts have to be read together.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Borboleta Pro's position in AI-generated recommendations for the Beauty and Personal Care category. It is not a client result and does not describe any CiteWorks Studio engagement.
2. The reporting month is October 2026, with comparison points at July 2026 (baseline), August 2026, and September 2026.
3. Six AI platforms were tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode.
4. The October 2026 run produced 324 prompt-surface observations and 272 unique questions. After qualification, 273 observations formed the public denominator for all brand-level metrics.
5. The competitor universe contains six tracked brands: Lashbox LA, Bella Lash, Sugarlash PRO, Paris Lash Academy, Borboleta Pro, and London Lash pro.
6. One buyer-intent cluster carried qualified observations in October 2026: Brand Recommendation. The Pricing and Value and Multi-Brand Comparison clusters carried zero qualified observations.
7. A mention is counted when a brand appears in an AI response to a qualified prompt, regardless of placement or framing.
8. A valid recommendation is counted when a brand appears in a valid recommendation shortlist, as marked by the benchmark's qualification process. Neutral, cautionary, and listed-only mentions are not counted as valid recommendations.
9. Top-three rate is the share of qualified observations in which a brand is placed in the first three recommendation positions. Rank-one rate is the share in which a brand is the first recommendation. Average recommended rank covers rank-eligible recommendations only.
10. Borboleta Pro's coverage rests on 30 valid recommendations. Month-over-month changes on this base should be read with caution, since a single prompt moving in or out of the shortlist shifts the percentage by roughly a third of a point.
11. The benchmark records changes in recommendation coverage and placement. It does not establish why those changes occurred. Source presence in the citation layer is evidence about the information environment, not proof that a source caused a recommendation.
12. All percentages in this report are calculated against the 273 qualified observations, not the raw 324 prompt-surface observations.

See How AI Is Recommending Your Brand

The public benchmark shows where Borboleta Pro stands in AI-generated recommendations across the Beauty and Personal Care category. A company-level AI visibility audit shows why, mapping the specific prompts where the brand is shortlisted, the prompts where a competitor takes the recommendation instead, and the source and citation patterns behind both.