AI search is changing how people find local businesses, but appearing in an AI-generated answer is not as simple as earning the top spot in a traditional search result.
In our previous analysis of how AI search recommends local businesses, we asked seven major AI platforms to explain the factors they consider when recommending a local service provider. Reviews, service relevance, location, business profile completeness, content quality, citations, and other familiar local search visibility signals appeared throughout their responses.
That raised another question: Do those priorities change when the type of business changes?
The results showed that changing the type of business changed the factors AI said matter. Changing the patient’s intent changed the recommendations again. For dental practices investing in SEO, what happened next may be the more important finding.
Our Original Study Needed a Vertical-Specific Test
Our first study looked broadly at how AI platforms evaluate local service businesses. Across the seven systems, we identified 12 recurring categories.
Reviews and service relevance were prominent, alongside traditional visibility variables such as:
- location and proximity;
- Google Business Profile completeness;
- website content quality and depth;
- multi-platform presence and citations;
- content freshness;
- schema and structured data; and
- NAP and business information consistency.
Those factors gave us a useful baseline for general local recommendations. We wanted to know what would change when the recommendation involved a specific industry with its own considerations.
Dentistry gave us a strong test case.
Why Dentistry?
Dentistry is a useful test because it sits at the intersection of local search and Your Money or Your Life (YMYL) content. Recommendations can affect a person’s health and finances, raising the stakes beyond many local service searches.
Choosing a dentist can also depend on clinical experience, treatment specialization, patient comfort, insurance, technology, and availability. Those considerations gave us a strong test of whether AI search recommendation factors change when both the industry and the stakes change.
How We Tested AI Dental Recommendations
We used the same seven AI platforms from our original study and divided the research into two phases.
Phase 1: Ask What Matters When Recommending a Dentist
We gave each platform the same prompt:
“What factors matter when you recommend a local dentistry practice? Assign a percentage weight to each factor you consider, with the percentages totaling 100%. Explain briefly what each factor means specifically for a dental practice.”
We intentionally did not provide the 12 categories from our original study. Each platform had to identify and weight the factors it considered relevant to dentistry on its own.
| Dental Recommendation Factor | Claude | ChatGPT | Gemini | Google AIO | Perplexity | Copilot | Meta AI |
| Reviews & Reputation | 25% | 25%* | 25% | — | 20% | 20% | 20% |
| Clinical Expertise & Treatment Fit | 35% | 20% | 35% | 25% | 40% | 25% | 35% |
| Access, Location & Availability | 12% | 20%† | 10% | 20% | 10% | 5% | 15% |
| Cost, Insurance & Financing | 10% | 10% | 15% | 15% | 10% | 10% | 15% |
| Patient Experience, Comfort & Communication | 8% | 15% | — | 20% | 15% | 15% | 7% |
| Technology, Facilities & Cleanliness | 5% | 5% | 15% | 20%‡ | 5% | 15% | 8% |
| Other | 5% | 5%§ | — | — | — | 10%¶ | — |
These percentages should not be interpreted as proprietary algorithm weights. They are self-reported frameworks showing how each AI system described its recommendation priorities when asked to quantify them.
Phase 2: Test Those Priorities With Real Dental Searches
Next, we ran the same 15 prompts across all seven platforms, giving us 105 recommendation responses to compare.
- Recommend three dentists in Spartanburg, South Carolina.
- Who are the best dentists in Spartanburg, SC?
- What dentist would you recommend in Spartanburg, SC for a new patient?
- Which dentists in Spartanburg, SC have the best patient reviews?
- Recommend a highly rated family dentist in Spartanburg, SC.
- Who would you recommend for dental implants in Spartanburg, SC?
- Recommend a cosmetic dentist in Spartanburg, SC.
- Who should I see for Invisalign in Spartanburg, SC?
- Where can I get a same-day dental crown in Spartanburg, SC?
- Recommend an emergency dentist in Spartanburg, SC.
- Which Spartanburg dentist would you recommend for someone nervous about dental treatment?
- Which dentist near Spartanburg has experienced dentists and strong credentials?
- What dental practice in Spartanburg would you recommend for a family with children?
- I live in Spartanburg and need a dentist. Which three practices should I consider and why?
- Compare three dental practices in Spartanburg, SC and tell me which you would choose.
The prompts deliberately move between broad local recommendations and searches where a specific treatment, patient need, or practice attribute could affect the answer.
For each platform, we recorded whether a practice received a substantive recommendation in each query. A practice mentioned multiple times within one response counted once.
We refer to the resulting metric as Recommendation Visibility Rate:
Recommendation Visibility Rate = Queries where the practice was recommended ÷ 15
This measures how consistently a practice entered a platform’s recommendation set. It does not mean the practice ranked first, was the platform’s preferred choice, or held a traditional organic search position.
We also tracked qualitative differences in the answers, including when platforms favored specialists, emphasized particular practice attributes, identified a preferred option, or suggested that the user provide more information to refine the recommendations.
We used Spartanburg, South Carolina, as a consistent test market. Individual recommendations will vary by location, but the patterns we observed around platform differences, patient intent, and digital evidence are relevant to dental practices in other markets.
A Note On The SEO/AEO Follow-Up
After the primary test, we also asked a qualitative follow-up about how digital search-related signals interact with dental recommendation factors. The question covered signals such as website content, business profile information, reviews, citations, data consistency, structured information, and freshness.
We used those responses to identify recurring concepts about discovery and verification, not to calculate additional visibility weights or compare platforms quantitatively.
Dentistry Changed What AI Search Said Matters
The original study included many familiar local SEO signals, including reviews, proximity, business profiles, content, citations, freshness, structured data, and NAP consistency. When we specified dentistry in the searches, the priorities shifted toward factors directly related to choosing a healthcare provider.
Clinical Expertise and Treatment Fit Became Major Factors
All seven platforms considered clinical expertise, credentials, safety, services, or treatment fit.
Four made an explicitly clinical or credential-focused factor their largest category. The other three gave their highest weight to reviews or reputation.
The responses also considered whether a practice offered the care the patient actually needed. That becomes especially important when we compare broad dentist searches with searches for other specific dental needs.
Reviews Still Carried Significant Weight
Six of seven platforms explicitly included reviews or reputation as a major factor. Where reviews received their own weight, they generally accounted for 20% to 25%, as self-reported.
The responses went beyond average star ratings. Review volume, recency, consistency, and patient comments also appeared in the explanations. Review text can provide information about qualities such as communication, gentle care, billing, wait times, and experiences with specific treatments.
Cost and Insurance Appeared Across All Seven Platforms
Pricing transparency barely appeared in the original general-business framework. For dentistry, all seven platforms included cost, insurance, financing, or billing transparency, generally at 10% to 15%.
This reflects a practical part of choosing a dentist: a provider may be highly qualified and well reviewed but still be a poor fit for a patient’s insurance or out-of-pocket costs.
Patient Experience and Access Became More Specific
The dental frameworks repeatedly referenced patient comfort, communication, chairside manner, cleanliness, scheduling, and appointment availability.
Location still mattered, but it was often considered alongside other factors. For some searches, being nearby may be enough. For an emergency or anxious patient, availability or patient experience may carry more weight.
Technology Was Tied to Patient Care
Technology, equipment, facilities, hygiene, or cleanliness appeared in most of the frameworks. The value was generally practical. Technology could support a particular treatment, improve the patient experience, or provide evidence of a modern clinical environment.
The Percentages Were Only the Starting Point
The seven platforms showed considerable agreement about what they considered when recommending a dentist, but a hypothetical weighting exercise cannot tell us how those factors behave in an actual search.
So we ran the same 15 dental queries across all seven platforms and recorded which practices they recommended.
The Same Searches Produced Different Recommendations Across AI Platforms
Once the platforms had to recommend real dentists, agreement dropped considerably.
A practice that appeared frequently on one platform could appear only occasionally on another. Even broad prompts such as “Who are the best dentists in Spartanburg?” produced different groups of practices.
This suggests there is no single, universal AI ranking for a local dental practice. Recommendation visibility depends partly on which AI platform the patient uses.
High Visibility on One Platform Did Not Guarantee It Elsewhere
One practice, Practice A, provides a particularly clear example. It appeared in 13 of 15 ChatGPT searches (86.7%), but only one of 15 Perplexity searches (6.7%). Its visibility fell at several points between those extremes on the other platforms.
The business, market, and prompts did not change. Only the AI platform did.
This variation appears across multiple local dental practices. Different platforms repeatedly developed different groups of frequently recommended dentists.
| AI Platform | Queries Recommended | Recommendation Visibility Rate |
| ChatGPT | 13 of 15 | 86.7% |
| Gemini | 9 of 15 | 60.0% |
| Copilot | 8 of 15 | 53.3% |
| Claude | 7 of 15 | 46.7% |
| Google AI Overview | 6 of 15 | 40.0% |
| Meta AI | 4 of 15 | 26.7% |
| Perplexity | 1 of 15 | 6.7% |
Recommendation Visibility Is Not the Same as Ranking First
A recommendation appearance did not necessarily mean the practice was the first or preferred choice. Some platforms returned three practices, while others produced much larger sets. Meta AI, for example, averaged about 5.5 substantive recommendations per query.
That makes a traditional ranking-style leaderboard misleading. High visibility shows that a practice frequently entered the consideration set, not that it consistently ranked first.
Different Platforms Appeared to Build Different Candidate Pools
The variation also suggests that platforms do not necessarily begin with the same set of local businesses. Some frequently surfaced individual dentists, while others favored practices. The size of the recommendation sets also varied considerably.
We cannot determine the exact retrieval process behind each system from these searches. The practical effect, however, is clear: high visibility on one AI platform does not guarantee comparable visibility on another.
Rather than focusing on which dentist “won” the experiment, we looked at what caused the recommendation sets to change. The clearest pattern was the intent behind each search.
User Intent Changed Which Factors Mattered Most
The clearest pattern across the 105 searches appeared when the prompts became more specific. Broad searches produced general dentists, while treatment- and patient-specific searches changed the candidate pool.
- Invisalign: Orthodontists and practices with clear Invisalign experience became more prominent.
- Dental implants: Periodontists, oral surgeons, and implant-focused providers entered the recommendation sets more frequently.
- Same-day crowns: Practices with evidence of same-day crown technology and services gained relevance.
- Emergency dentistry: Availability, urgent care, and the ability to see patients quickly became more important.
- Dental anxiety: Practices associated with gentle care, sedation, and patient comfort surfaced more often.
- Families with children: Recommendations shifted toward family dental practices and pediatric specialists.
The pattern was consistent: as the patient’s needs became more specific, the factors most relevant to those needs became more important.
AI Recommendation Factors Appear Dynamic, Not Fixed
The percentage frameworks gave us a useful baseline, but the live searches showed why those numbers should not be treated as fixed formulas.
A strong reputation could help a practice across many queries, but it did not automatically make that practice the best match for Invisalign, a dental emergency, or a same-day crown. Specific needs introduced additional requirements that could change which providers were considered.
We also saw factors work together rather than independently. In one Invisalign search, for example, a provider’s high-level Invisalign recognition was a strong credential. The same response still suggested considering another orthodontist because its reviews provided stronger evidence of Invisalign-specific patient satisfaction.
This suggests that AI was not simply looking for whichever practice had the strongest single signal. The importance of each factor changed with the patient’s intent, while other factors continued to influence the recommendation.
AI Platforms Often Asked for More Information
The platforms also frequently offered to refine broad recommendations if the user provided more details, such as the procedure, insurance plan, location preference, or another specific need.
Many responses also advised patients to confirm insurance participation, cost, and appointment availability directly with the practice. We did not count these generic statements as recommendations, but they showed how additional information could further narrow the choices.
The initial percentages are therefore better viewed as baseline recommendation priorities. As the search becomes more specific, the relative importance of those factors can change.
That creates an important question: Can an AI system find enough information about a dental practice to evaluate it when a particular factor becomes more important?
Where Digital Search Strategies and AEO Enter the Recommendation Process
The dental-specific frameworks gave less explicit weight to traditional digital search signals than our original local-business study. That does not mean those signals no longer matter.
In a supplemental follow-up, we asked the AI platforms how search-related signals interact with the qualities used to recommend a dentist. The responses repeatedly described SEO as part of the discovery and verification process, rather than a replacement for clinical quality, reputation, or patient fit.
The concepts varied, but the role was similar: SEO can affect whether an AI system can find a practice, understand what it offers, and verify the information it needs to evaluate that practice.
For example, an AI system may need to establish that a practice:
- actually offers the treatment being requested;
- has dentists with relevant training or credentials;
- provides emergency, same-day, or sedation options;
- accepts certain insurance or offers financing;
- has current hours and appointment information; and
- is consistently represented across its website, business profiles, reviews, and other sources.
Several responses also emphasized problems with missing or conflicting information. If a service cannot be verified, NAP differs across sources, or provider information is incomplete or nondescript, the system has less evidence to work with.
While traditional search factors such as GBP completeness, NAP consistency, and schema may not make the cut as self-reported recommendation factors, how well they are implemented can affect which practices AI can find, verify, and confidently recommend to a user.
Based on our testing, a useful way to think about that relationship is:
Discover → Understand → Verify → Match → Recommend
This is not a literal description of how every AI platform works internally. It illustrates the role digital search strategy and AEO can play before and during the recommendation process.
For dental practices, the goal is not simply to rank for more keywords. It is to give AI systems enough accurate, accessible evidence to understand the practice and evaluate it across the searches it wants to compete for.
AI Platforms Need a Complete and Consistent Picture of Your Dental Practice
A thin dental website may give AI enough information to establish that a practice exists, where it is located, and that it provides general dentistry. A four-page site with a homepage, About page, location page, and contact page can cover those basics.
It provides much less evidence for specific searches.
A practice may offer emergency appointments, sedation dentistry, same-day crowns, Invisalign, or implants. If those services are barely mentioned or not documented, AI has less information connecting the practice to patients searching for them. The same applies to provider credentials, technology, insurance, appointment options, and patient-care attributes.
Think Beyond Keyword Coverage to Evidence Coverage
Traditional SEO often looks at which keywords and topics a website covers. AI recommendations add another useful question:
What can an AI system confidently establish about this practice from the information available online?
This is what we mean by evidence coverage. Service pages, provider bios, GBP information, reviews, and credible third-party sources can collectively establish what a practice offers and who it may be a good fit for.
The goal is not to create a page for every possible query. It is to make the practice’s real services, strengths, and patient options clear enough to be found, verified, and matched to relevant searches.
Information also needs to be accurate and reasonably consistent. AI may encounter practice details across the website, Google Business Profile, directories, review platforms, and other sources. Conflicting hours, outdated provider information, inconsistent service listings, or different location details can make those details harder to verify.
The goal is a complete, accurate, and corroborated digital picture of the practice that AI can confidently use when evaluating it for different patient needs.
What Should You Prioritize for AI Search?
The results do not point to one optimization that makes a dental practice more likely to appear in AI recommendations. They point toward building a digital presence that gives AI enough information to evaluate the practice across different patient needs.
Based on our testing, dental practices should prioritize:
- Build strong service coverage. Clearly document the treatments the practice actually provides, especially services patients commonly search for individually.
- Make provider expertise easy to verify. Include relevant education, advanced training, credentials, experience, professional recognition, and treatment-specific qualifications where appropriate.
- Maintain an accurate Google Business Profile. Services, categories, hours, contact information, and other practice details should reflect current operations.
- Develop a representative review profile. Rating matters, but so do review volume, recency, consistency, and the experiences patients describe.
- Document meaningful differentiators. Same-day technology, sedation options, emergency availability, financing, advanced equipment, and similar features should be easy to find when they are genuinely offered.
- Keep important information consistent. Practice details should agree across the website, business profiles, directories, and other credible sources.
- Keep decision-relevant information current. Hours, providers, insurance information, services, and availability can lose value when they become outdated.
- Support the content with sound technical signals. Structured data and other technical signals can help machines interpret information, but they should support clear, accurate content rather than substitute for it.
For a dental practice, maintaining this level of coverage can be substantial while providers and staff remain focused on patient care. A strong dental SEO strategy manages services, credentials, reviews, content, and business information as a connected system.
Effective search visibility and AEO do not make a practice more qualified, but they can help make qualified practices easier to find. At Spartan SEM, the goal is to build that complete digital presence, not simply optimize individual rankings or pages.
What 105 Searches Taught Us About AI Recommendations
This study does not reveal a universal AI ranking formula. The percentage weights reflect how each platform described its own priorities, not proprietary algorithm weights. Our live test also represents 105 searches in one market at one point in time, and it does not isolate individual search strategy variables.
What it does provide is a clearer picture of how local AI recommendations behave.
Across seven platforms, there was considerable agreement about what makes a dental practice recommendable, but far less agreement about which practices should be recommended. Those recommendations changed again when the patient’s needs became more specific.
That shifts the focus away from trying to identify one AI ranking formula. Dental practices need a digital presence that gives different platforms enough information to understand their services, expertise, reputation, availability, and other relevant qualities.
The opportunity is not to optimize for one version of the “best dentist” search. It is to make sure the practice can be found, understood, and evaluated across the many different ways patients actually search for dental care.
Make Sure AI Can Understand What Sets Your Practice Apart
Your dental practice may already offer the services, expertise, and patient experience people are searching for. The next step is making sure search engines and AI platforms can find and understand that evidence.
Spartan SEM helps dental practices build a connected digital presence designed for traditional search and the changing AI search landscape.
Notes on Category Grouping
The AI platforms did not use identical terminology, so closely related factors were grouped for comparison. Some original categories combined multiple concepts and are noted below.
- * ChatGPT — Reviews & Reputation: The original 25% category was “Quality & Reputation,” which included reviews, feedback consistency, professional reputation, clinical outcomes, and patient care.
- † ChatGPT — Access, Location & Availability: ChatGPT separately assigned 15% to “Location & Convenience” and 5% to “Appointment Availability.” These are combined here.
- ‡ Google AI Overview — Technology, Facilities & Cleanliness: Google AI Overview grouped “Safety, Hygiene & Modern Technology” into one 20% category. We placed it here rather than also counting it under clinical expertise.
- § ChatGPT — Other: ChatGPT separately assigned 5% to “Trust, Safety & Professionalism.”
- ¶ Copilot — Other: Copilot separately assigned 10% to “Preventive Care Philosophy.”
Percentages reflect the platforms’ self-reported conceptual frameworks, not published or proprietary algorithm weights.
