Billie Appears in 0.7% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
9 minutes read

Key Takeaways

  • Billie appeared in 3 of 425 benchmark answers, with 3 recommendations and 2 top-three placements, but overall visibility remained very low.
  • The latest month showed a small rise in mentions and recommendations, though the smaller sample size limits month-to-month comparison.
  • No conflicting claims were recorded in the captured answers, so the first step is to verify which product and ingredient statements actually appear.
  • The strongest question themes were razor bumps, affordable skincare, and fragrance-free lotion, which are the clearest opportunities for new content briefs.

Answer Capsule

In November 2026, Billie appeared in 3 of 425 AI answers included in the Body Care Brands benchmark (0.71%). It received 3 recommendations (0.71%), with 2 Top 3 placements and 1 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

  • How do Billie mentions, recommendations and placements compare with its Body Care Brands peers?

Billie recorded 3 mentions (0.71%) and 3 recommendations (0.71%) across 425 answers included in the benchmark. Top 3 placements numbered 2; first-place recommendations numbered 1. Framing among its mentions was 3 positive, 0 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

CeraVe

417

98.12%

271

63.76%

214

50.35%

162

38.12%

2

Neutrogena

381

89.65%

220

51.76%

146

34.35%

34

8.00%

3

Cetaphil

339

79.76%

206

48.47%

133

31.29%

34

8.00%

4

Kiehl’s

205

48.24%

103

24.24%

67

15.76%

10

2.35%

5

Sun Bum

22

5.18%

8

1.88%

5

1.18%

3

0.71%

6

Origins

32

7.53%

6

1.41%

3

0.71%

2

0.47%

7

Billie

3

0.71%

3

0.71%

2

0.47%

1

0.24%

8

Kopari Beauty

1

0.24%

1

0.24%

0

0.00%

0

0.00%

Billie appears in only a small share of the answers reviewed, and its recommendations are equally thin. The few mentions it does earn are framed positively, and a couple of those sit near the top of the answer. That combination matters: the brand is not being dismissed where it surfaces, but it is rarely surfaced at all.

The gap to the leading body care names is wide, so the practical question is not how to close it quickly but where a first foothold is realistic. A visibility comparison against the closest peers would show which answer types and question themes give Billie its best chance, and that comparison is the sensible first piece of work.

What changed since last month

Questions This Section Answers

  • How did Billie counts and coverage differ across the available monthly snapshots?

Metric

Jul 2026

Aug 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

1 / 623 (0.16%)

0 / 634 (0.00%)

1 / 518 (0.19%)

0 / 526 (0.00%)

3 / 425 (0.71%)

Recommendations

0 / 623 (0.00%)

0 / 634 (0.00%)

1 / 518 (0.19%)

0 / 526 (0.00%)

3 / 425 (0.71%)

Top 3 recommendations

0 / 623 (0.00%)

0 / 634 (0.00%)

1 / 518 (0.19%)

0 / 526 (0.00%)

2 / 425 (0.47%)

#1 recommendations

0 / 623 (0.00%)

0 / 634 (0.00%)

1 / 518 (0.19%)

0 / 526 (0.00%)

1 / 425 (0.24%)

From October 2026 to November 2026, Billie's mention count rose from 0 to 3, while its recommendation count rose from 0 to 3. The recommendation rate was 0.00% and 0.71% respectively.

Across the monthly samples, Billie's recorded mentions and recommendations were mostly absent, with occasional single appearances, before the latest month showed a small cluster. The latest month also used a smaller answer sample than earlier months, so the results are not directly comparable and the movement should be read as an observation rather than a trend.

A single month of activity is too thin to treat as momentum. The useful next step is to keep the monthly scorecard running and watch whether the same question themes keep producing mentions, rather than drawing conclusions from one sample.

AI recommendation trend

Observed recommendation rate (%), Jul 2026 to Nov 2026

0%0.2%0.4%0.6%0.8%Jul 2026Aug 2026Sep 2026Oct 2026Nov 20260.00%Jul 2026: 0.00%0.00%Aug 2026: 0.00%0.19%Sep 2026: 0.19%0.00%Oct 2026: 0.00%0.71%Nov 2026: 0.71%
  • Billie0.71%

Separate selected monthly samples. Missing points are unavailable, not zero. Provider/prompt equivalence is unverified; rate movement does not demonstrate causation.

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Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for Billie?

AI answers contained 0 conflicting claims about Billie: 0 critical, 0 high, 0 medium, 0 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

No conflicting claims about Billie were recorded in the captured answers, so there is nothing urgent to correct. That is a clean starting position, but it also means the fact-checking work should be scoped rather than assumed: confirm which product and ingredient statements actually appear in answers before building a review list.

A visibility comparison and a short list of claims worth verifying would let the client decide where effort goes first. Both are proposed work, and any correction would depend on checking current primary sources rather than on the AI answer alone.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Billie should be verified before proposed page edits?

No results are available for this part of the analysis.

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

This part of the analysis returned no results, so there are no disputed topics to work through for Billie right now. Rather than inventing issues, the sensible move is to set up a light review process that can catch conflicts if they appear in later samples.

Where an apparent conflict does surface, the entity, date and source need resolving before anyone treats it as an error; different dates alone can explain a mismatch. Page briefs would then be drafted only for confirmed gaps, using approved company facts.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Billie?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://nytimes.com/wirecutter/reviews/best-body-lotions/

4

1

0

https://cosmopolitan.com/style-beauty/beauty/g66210268/best-drugstore-skincare-brands/

2

1

0

https://allure.com/story/best-fragrance-free-body-lotions

1

1

0

https://allure.com/story/best-of-beauty-drugstore-product-winners-2025

1

1

0

https://borealisderm.com/in-the-news/skin-experts-reveal-the-best-products-for-razor-burn-and-bumps/

1

1

0

https://harpersbazaar.com/beauty/skin-care/g63844064/best-affordable-skincare-under-20-dollars/

1

1

0

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

The cited pages selected for review are general body care and skincare roundups, each linked to Billie in only a single answer. Citation counts are small and a citation does not show that a page influenced the answer, so these are candidates for reading, not for correction requests.

The proposed work is a source review: check what each page currently says, note where Billie is absent or framed differently from approved facts, and only then consider a polite, evidence-backed request. Publisher control and page accuracy cannot be assumed in advance.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Billie website pages should receive review briefs?

No results are available for this part of the analysis.

The company's website was cited 0 times across 0 distinct page addresses; the table shows 0 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

No Billie-owned pages were cited in the captured answers, so there is no owned-page evidence to interpret yet. That absence is a starting observation, not proof that the site lacks relevant content.

Page briefs would therefore begin with the pages the client considers most important, built around approved facts and the questions buyers actually ask. Each brief would be checked against existing site coverage before any new page is proposed, and a cited page would never be treated as automatically tied to a recommendation.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Billie?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

What cream is good for razor bumps?

1

1

1

Which cheap skincare is best?

2

1

1

fragrance free lotion

1

1

1

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions point to a few clear themes: razor bumps, affordable skincare and fragrance-free lotion. Billie was mentioned and recommended in the answers to each, which suggests these are the question types where the brand already has a foothold worth strengthening.

Proposed work is to check existing site coverage for each theme, then draft buyer-question content that answers directly and uses approved product facts. These are recorded answer observations, not search volume, so the briefs should be treated as content opportunities to test rather than proven demand.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Billie work and judge completion?

Period

Deliverable

Completion criterion

Days 1–30

Baseline scorecard, scoped fact-review register and page/source shortlist

Each record has an owner, evidence requirement and review status

Days 31–60

Approved page briefs and justified publisher requests

Separate confirmed edits, no-change decisions, requests and responses

Days 61–90

Buyer-content briefs and a fresh scorecard

Record work completed separately from measured answer outcomes and comparability limits

The first month would produce a baseline scorecard, a scoped fact-review list and a shortlist of pages and sources, each with an owner and a clear evidence requirement. The second month would turn confirmed gaps into approved page briefs and justified publisher requests, tracking requests and responses separately.

The final month would deliver buyer-content briefs and a fresh scorecard. Completed work would be recorded separately from measured answer outcomes, since the monthly samples differ and no visibility gain can be promised from these activities.

Methodology

Questions This Section Answers

  • How are Billie answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 425 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 5445 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reporting month

Answers included

AI services covered

Services

Jul 2026

623

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Aug 2026

634

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Sep 2026

518

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Oct 2026

526

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Nov 2026

425

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

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

The monthly samples differ in size and were collected under the benchmark's inclusion rules, so month-to-month comparisons show what was recorded, not why it changed. Mentions and recommendations are counted per company, and an answer can cover several brands, so company counts do not add up to distinct answers.

Recommendations require both endorsement and positive wording, and top placements sit inside recommendations rather than alongside them. The exact collection dates for the original answers are unverified, and cited pages and disputed claims still need independent checking.

Our first three priorities

First, run a visibility comparison against the nearest peers to identify which question themes give Billie its best chance, since the brand is rarely surfaced but framed positively when it is. Second, review the cited roundup pages for current accuracy before any publisher request, treating citations as leads rather than causes.

Third, check existing site coverage on razor bumps, affordable skincare and fragrance-free lotion, then draft buyer-question briefs using approved facts. All three are proposed work, and any correction would wait on primary-source verification.

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Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
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.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

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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