Case study: How a dental practice went from invisible to top AI recommendations

The starting point

When Millbrook Dental first ran a Lensora scan, the results were sobering. Despite being a well-established practice with over 400 active patients and strong Google reviews, they were invisible across every AI platform. Competitors with fewer reviews were appearing consistently.

The audit

The Lensora audit identified several gaps. There was no schema markup, so AI models had no machine-readable information about the practice. Service pages had around 180 words with minimal detail. There was almost no mention of the practice on external websites. Phone numbers appeared in three different formats across directories. Common patient questions had no answers on the site.

The 8-week plan

Weeks 1 and 2: Foundation fixes

The team standardised NAP data across all directories, added LocalBusiness and Dentist schema markup to the homepage, and fixed inconsistent listings on minor directories.

Weeks 3 to 5: Content overhaul

Each core treatment page was rewritten with word counts increasing from around 180 words to 800 to 1,200 words. Each page now answers the five most common patient questions about that treatment. Costs, timelines, and what to expect are covered explicitly. FAQPage schema was added throughout.

Weeks 6 and 7: Authority building

The practice reached out to local parenting blogs, a local lifestyle magazine, their dental supply company, and the local business association, earning mentions and directory listings from each.

Week 8: Review push

A systematic review request was added to the post-appointment email sequence, resulting in 23 new Google Reviews from real patients.

The results

After 8 weeks, the practice appeared in responses to 6 of their 10 target queries. They were appearing on ChatGPT, Perplexity, and Google AI Overviews. Average position improved to first or second recommendation. Sentiment was consistently positive.

The practice manager said: We have had three new patients specifically mention they found us through an AI recommendation. This has already paid for itself many times over.

Key lessons

The fixes that drove the most improvement were schema markup for immediate impact on AI understanding, content depth to answer the questions AI models respond to, and third-party mentions as authority signals that AI models trust.