From patient answer to clinic audit

After the course, you will be able to record what an AI assistant says about a dental clinic and separate stable description from claims that are vague, borrowed, outdated, or contradicted by public evidence. You will learn how to check whether the clinic’s Thai and English names point to the same practice, whether the district and province signals are specific enough, whether the service category fits the clinic’s actual work, and whether treatment claims are supported by current public pages. You will also learn how to read reviews without letting them replace clinical evidence and build a prioritized correction routine that makes the clinic easier to identify, locate, classify, and cite.

The sequence starts with one patient-style question and an unedited AI answer. It then moves through the practical surfaces that shape that answer: names, places, categories, services, sources, languages, and reviews. Later lessons turn the reading into repair work, so students finish with a clinic visibility record and a repeatable self-audit instead of a pile of disconnected notes.

You should have access to the clinic website, map listing, social pages, and at least a few public profiles, directories, booking pages, or review sources. You do not need coding, SEO software, structured data knowledge, or experience with language models. The course assumes you already understand clinic services, patient questions, appointment flow, and the difference between general, cosmetic, restorative, and specialist dental care.