Dr. Dental Appears in 0.0% 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

  • Dr. Dental had 0 mentions and 0 recommendations across 372 benchmark answers in November 2026.
  • Competitors such as Aspen Dental, Affordable Dentures & Implants, and ClearChoice were named and recommended in the same answers.
  • The first priority is to establish a baseline scorecard and verify any claims against primary sources before making page changes.
  • The 90-day plan moves from measurement to page briefs, publisher outreach, and buyer-question content, with outcomes tracked separately from delivery.

Answer Capsule

In November 2026, Dr. Dental appeared in 0 of 372 AI answers included in the Dental Implants benchmark (0.00%). It received 0 recommendations (0.00%), with 0 Top 3 placements and 0 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 Dr. Dental mentions, recommendations and placements compare with its Dental Implants peers?

Dr. Dental recorded 0 mentions (0.00%) and 0 recommendations (0.00%) across 372 answers included in the benchmark. Top 3 placements numbered 0; first-place recommendations numbered 0. Framing among its mentions was 0 positive, 0 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Affordable Dentures & Implants

232

62.37%

23

6.18%

11

2.96%

10

2.69%

2

Aspen Dental

295

79.30%

14

3.76%

4

1.08%

3

0.81%

3

ClearChoice

192

51.61%

12

3.23%

4

1.08%

1

0.27%

4

Nuvia Dental Implant Center

45

12.10%

6

1.61%

4

1.08%

4

1.08%

5

Dr. Dental

0

0.00%

0

0.00%

0

0.00%

0

0.00%

5

G4 by Golpa

1

0.27%

0

0.00%

0

0.00%

0

0.00%

5

Gentle Dental

8

2.15%

0

0.00%

0

0.00%

0

0.00%

5

Sage Dental

5

1.34%

0

0.00%

0

0.00%

0

0.00%

5

Tend

51

13.71%

0

0.00%

0

0.00%

0

0.00%

5

Western Dental

10

2.69%

0

0.00%

0

0.00%

0

0.00%

Dr. Dental did not appear in the answers included in this benchmark, so there is no recommendation record to build a target around. That absence is the starting point, not a verdict on the brand. The competitors shown are being named and endorsed in the same answers, which means the category conversation is happening without Dr. Dental in it.

Before chasing placement, the agency would establish what the brand actually wants to be known for in implant answers and which approved facts support that. A visibility goal set against a zero baseline needs a clear definition of what counts as progress, agreed with the client up front.

What changed since last month

Questions This Section Answers

  • How did Dr. Dental counts and coverage differ across the available monthly snapshots?

Metric

Jul 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

2 / 391 (0.51%)

0 / 411 (0.00%)

0 / 366 (0.00%)

0 / 372 (0.00%)

Recommendations

1 / 391 (0.26%)

0 / 411 (0.00%)

0 / 366 (0.00%)

0 / 372 (0.00%)

Top 3 recommendations

1 / 391 (0.26%)

0 / 411 (0.00%)

0 / 366 (0.00%)

0 / 372 (0.00%)

#1 recommendations

0 / 391 (0.00%)

0 / 411 (0.00%)

0 / 366 (0.00%)

0 / 372 (0.00%)

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

From October 2026 to November 2026, Dr. Dental's mention count stayed at 0, while its recommendation count stayed at 0. The recommendation rate was 0.00% and 0.00% respectively.

Across the verified months, Dr. Dental's recorded mentions and recommendations sit at or near zero, with the earlier month showing a single recommendation that has not recurred. The monthly answer samples differ, so the movement should be read as a record of what was observed rather than an explanation of why it happened.

The practical reading is that there is no stable presence to protect or defend yet. The agency would treat the coming months as a clean baseline period, documenting each sample and its coverage so later comparisons rest on consistent ground.

AI recommendation trend

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

0%0.08%0.15%0.23%0.3%Jul 2026Sep 2026Oct 2026Nov 20260.26%Jul 2026: 0.26%0.00%Sep 2026: 0.00%0.00%Oct 2026: 0.00%0.00%Nov 2026: 0.00%
  • Dr. Dental0.00%

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

/ Take the next step

Want to Understand Your AI Citation Footprint?

We start every engagement with a full audit of how AI systems reference your brand today.

Measurable, Repeatable Programme

Build a durable foundation of credible citations that compounds over time and continues to influence AI answers as new queries emerge

Citation Architecture Review

Identify which high-authority community sources are and aren't working in your favour across AI platforms.

AI Visibility Audit

Understand exactly how LLMs are referencing your brand today and which sources are shaping those answers.

Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for Dr. Dental?

AI answers contained 0 conflicting claims about Dr. Dental: 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.

With no conflicting claims recorded about Dr. Dental, the immediate measurement task is not claim repair but establishing a reliable picture of where the brand stands. A baseline scorecard would record mentions, recommendations and placements alongside the questions that produced them, so the client can see which answer contexts matter most.

A scoped fact-review list would sit beside it, capturing any company claims that surface in answers and flagging them for verification against primary sources. This gives the client a prioritized view without treating an AI statement as proof of an error.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Dr. Dental 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.

No disputed-topic results were available for this part of the analysis, so there is nothing to correct and nothing to confirm. The agency would not draft page changes on the assumption that a conflict exists. Instead, the first step is to resolve the company entity, relevant dates and originating sources for any claim that later appears.

Where a genuine question emerges, the agency would prepare a conditional page brief: proposed wording drawn only from client-approved facts, with the verification step recorded before anything is published. Ambiguous matches stay out of the queue.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Dr. Dental?

No results are available for this part of the analysis.

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.

No source-review results were available here either, so the external work starts with selection rather than correction. The agency would review the pages that appear alongside implant questions, checking their current contents against primary sources before deciding whether any outreach is warranted.

Any publisher request would be evidence-backed and framed as a request, not an assumption of error or control. Responses, no-change decisions and confirmed edits would be logged separately so the client can see what was actually done.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Dr. Dental 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.

The company's website was not cited in the captured answers, and no pages were selected for review. That is a starting observation, not a finding that the site lacks useful content. The agency would build page briefs around approved company facts and the questions buyers actually ask, then check existing coverage before proposing anything new.

Each brief would name its audience question, the approved facts it may use and the reviewer who signs off. 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 Dr. Dental?

No results are available for this part of the analysis.

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

No buyer-question observations were available for this analysis, so content planning begins with gathering them rather than guessing at demand. The agency would collect the questions that appear in implant-related answers and group them into themes the client can act on.

Each theme becomes a content brief only after the client's existing pages are checked for coverage. Recorded questions are treated as answer observations, not search volume or proof that a page is missing.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Dr. Dental 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 produces the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and review status. The second month turns approved facts into page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately.

The third month adds buyer-content briefs and a fresh scorecard. Completed work is reported apart from measured answer outcomes, and no visibility gain is promised from delivery alone.

Methodology

Questions This Section Answers

  • How are Dr. Dental 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 372 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 5892 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

391

6

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

Sep 2026

411

6

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

Oct 2026

366

6

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

Nov 2026

372

6

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

Reliable results for August 2026 are unavailable. This is a gap in the history, not a result of zero.

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

The answers were captured without verified collection dates, and the monthly samples differ, so comparisons describe recorded results rather than causes. A recommendation requires both an endorsement and positive wording; placements sit inside recommendations rather than adding to them. Answers can name several companies, so counts are not additive.

Cited pages and any disputed company claims still need independent verification before action. August results are a gap, not a zero.

Our first three priorities

The first priority is a clean baseline: a scorecard that records what Dr. Dental's absence looks like across the questions that matter, with owners and review status attached. Without that, any later movement is hard to interpret.

The second is a scoped fact-review register built from claims that actually surface, verified against primary sources before any page brief is written. The third is buyer-question content, planned only after existing coverage is checked. Together these give the client defensible work to review while keeping measured outcomes separate from delivered tasks.

/ Learn More

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.

Archived editions

Browse earlier published research snapshots for this article. The latest edition remains at the current URL.

VIEW ALL CASE STUDIESREQUEST AN AI VISIBILITY AUDIT