Question 1

What does the 0–100 AI Acquisition Score measure?

Accepted Answer

The AI Acquisition Score measures observed ChatGPT recommendations for realistic treatment-and-location patient searches. It records whether your practice is surfaced and how relevant the recommendation is for that prompt. It is not a Google ranking, an advert-performance metric, or a guarantee that a patient will contact or choose your practice.

Question 2

What does the AI Readiness Score measure?

Accepted Answer

The AI Readiness Score measures how well a practice’s online signals can be retrieved, understood, trusted, and cited by AI systems. It uses the approved weights: Trust/consensus 35%, Authority 30%, Structure/clarity 20%, and Expertise 15%. It reports evidence status, coverage, freshness timestamps, and limitations. Readiness does not guarantee recommendations, and it is a separate diagnostic from the AI Acquisition Score — the two scores must not be blended.

Question 3

What goes into the score?

Accepted Answer

The AI Acquisition Score reflects the treatment and location scope you submit, whether your practice is mentioned, where it appears in the answer, and how relevant that mention is to the patient prompt. It also considers the source and local-authority signals behind the answer, so the result is not reduced to a simple name-count or a promised causal conversion score.

Question 4

Why do treatment and location choices matter?

Accepted Answer

Patients ask different questions about dental implants, Invisalign, orthodontics, cosmetic dentistry, dental bonding, nervous patient care, teeth whitening, general dentistry, and dental hygiene in different towns. The scorecard uses your selected treatments and town to scope the prompts, so a practice can be visible for one patient need and absent for another without those results contradicting each other.

Question 5

Is the score a forecast of new patient enquiries?

Accepted Answer

No. It shows the recommendation surface an AI assistant presents to a patient and the evidence supporting that surface. It can help prioritise visibility work, but it does not claim to predict enquiries, bookings, revenue, or a causal lift from any particular marketing action.

Question 6

How is the OpenAI evidence sourced?

Accepted Answer

The public scorecard runs realistic patient prompts through ChatGPT's live-search path where that path is available. It records the response text and cited URLs returned by the run, rather than substituting Google rank positions or generic model-only commentary. If live search is unavailable or the answer has no usable grounding, that limitation stays visible in the result.

Question 7

What is recorded and timestamped?

Accepted Answer

For each prompt check, the scorecard keeps the response evidence, the practice-name and submitted-website match checks, the cited source URLs, and the run timing. Evidence records carry a recordedAt value and completed runs expose their analysis timestamp, so a report can be understood as a dated observation rather than a permanent claim about ChatGPT.

Question 8

What is the difference between verified and unverified output?

Accepted Answer

Verified evidence requires the expected response, a case-matched practice name or submitted website, a valid timestamp, grounded cited sources, and the verdict checks to pass. Unverified output may be retained for context, but it is not treated as proof of visibility. A model-only answer, missing source, unavailable live search, or failed match check stays unverified instead of being presented as a clean result.

Question 9

Can incomplete evidence produce a trusted score?

Accepted Answer

No. The scorecard requires complete verified coverage for the prompts in scope before it presents a trusted analysed result. If the evidence is incomplete, unattributed, or not grounded, the report explains that it needs a rerun rather than turning missing evidence into a negative practice verdict.

Question 10

What do selected beta testers receive, and what do they give in return?

Accepted Answer

The confirmed exchange is practice-specific client testing, a practice-specific report, and a review of the experience. Selected testers receive the test and report; in return, they give practical feedback on accuracy and usefulness and review the experience. Any additional commercial terms, compensation, leads, ongoing monitoring, or cohort-specific arrangements are confirmed directly before participation and are not promised by this page.

Question 11

What practice data do I submit?

Accepted Answer

The current intake asks for your practice name, town, website, and the treatments you want to check. An optional submitter email can be included so the app can notify you when the scorecard is ready. Those fields define the scorecard scope; this FAQ does not add any unlisted data requirement.

Question 12

How is my practice data used after submission?

Accepted Answer

The submitted practice details are used to run the scorecard and produce its evidence, citations, timestamps, and verdict. A signed-in submission can be associated with that account. If you provide an email, the app can send a scorecard-ready notification. Anonymous visitors receive a public scorecard result link, and completed reports can be shared through the app’s public report routes when a public share is created.

Question 13

What privacy or retention promise applies to beta data?

Accepted Answer

The current product materials do not define a deletion timeline, retention period, anonymisation guarantee, or separate beta privacy policy. Please ask for the cohort terms before submitting information you do not want used for this testing workflow. The app’s public report behaviour is described above; no broader privacy promise should be inferred from the scorecard or this FAQ.

Before you trust the score, understand the evidence.

Scoring

Evidence

Beta

Scoring

01What does the 0–100 AI Acquisition Score measure?

02What does the AI Readiness Score measure?

03What goes into the score?

04Why do treatment and location choices matter?

05Is the score a forecast of new patient enquiries?

Evidence

01How is the OpenAI evidence sourced?

02What is recorded and timestamped?

03What is the difference between verified and unverified output?

04Can incomplete evidence produce a trusted score?

Beta

01What do selected beta testers receive, and what do they give in return?

02What practice data do I submit?

03How is my practice data used after submission?

04What privacy or retention promise applies to beta data?