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Whitelabel

The AEO/GEO play that turned a dental clinic into an AI-cited source

Project Overview

Organization

Multi-location dental & implant clinic group (anonymised under NDA)

Industry

Healthcare - dental & implants

Starting Position

Strong clinical reputation. Steady classical search rankings. Zero presence in AI answers.

Location

Perth metro area, WA

Engagement Period

December 2025 – May 2026

Products / Services Used

  • AI Search Visibility
  • AEO
  • GEO
  • AIO/LLMO
  • SEO Foundation

A multi-location dental and implant group in the Perth metro area came in with something most healthcare brands would kill for - a strong clinical reputation and steady rankings on classic search. What they didn't have was any presence in the answer patients had started using instead of a Google results page.

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Ask an assistant for "the most trusted dentist near me" and you get a three-name shortlist. If the clinic isn't in that shortlist, it isn't considered. Doesn't matter what page one says. Doesn't matter how good the Google reviews are. The consideration set closes before the patient ever scrolls.

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That's the market the clinic was competing in. And losing quietly.

Performance Insights

Key results for the client

0 → 6/6

Buyer prompts cited in Google AI Overviews

0 → 6/6

Buyer prompts cited in ChatGPT

+56%

Organic sessions, Dec to May

+52%

Organic key conversions, Dec to May

Client Objectives

Ranked, but not recommended

The starting point was blunt. In December 2025, across the six tracked buyer prompts most likely to end in an actual booking, the brand was cited zero times in Google AI Overviews and zero times in ChatGPT. 

The traditional search rankings held up fine -  around position 14 for the core local term. Present. Not preferred.

The six prompts weren't fishing queries. Each one was tied to concrete commercial intent:



  1. "Most trusted dental clinics in Melville" - vendor shortlist
  2. "Emergency dentists in Booragoon" - urgent, high-intent
  3. "Reliable dental implants in Booragoon" - treatment + trust
  4. “Most recommended dentist in Booragoon" - recommendation
  5. "Best dental implants in Melville" - treatment shortlist
  6. "Cosmetic dentist in Melville" - service-specific


These are the questions that decide the sale. AI wasn't naming the clinic in any of them.

Mavlers Strategy

Every AI search factor, engineered as one system.

Four disciplines - AEO, GEO, AIO/LLM - running on one SEO foundation. Eight factors treated together because models don't grade them separately.

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1.
Made the pages readable to AI systems.

Audited crawl access, render behaviour, and how content resolves when an AI system fetches the page. JavaScript-only content invisible to crawlers, blocked resources, conflicting canonicals, slow render paths - fixed at the source.

2.
Built entity signals models can cross-reference.

Aligned name, address, service list, and practitioner credentials across every property AI cross-checks — Google Business Profile, Healthengine, Smile.com.au, Perth-metro directories. Fragmentation across those sources is a top reason models decline to name a clinic that "exists."

3.
Schema built for how the parser reads.

Organization, LocalBusiness (Dentist), MedicalOrganization, FAQPage - marked up with the properties that matter for healthcare recall: service area, specialties, insurance accepted, hours, practitioner info. Machine-readable context, not badge decoration.

4.
Rewrote content in the shape models can lift.

Every tracked prompt had a direct answer at the top of the relevant page section - complete sentences that resolve without surrounding paragraphs. Natural-language variations included, because patients phrase the same question ten different ways.

5.
Third-party trust from sources AI verifies.

Reviews on Google and Healthengine, references in Australian dental publications, mentions across Perth-metro health directories. Reference quality from sources models actually pull from in the healthcare vertical.

6.
Prompt-level tracking, screenshot-verified, monthly.

Reviews on Google and Healthengine, references in Australian dental publications, mentions across Perth-metro health directories. Reference quality from sources models actually pull from in the healthcare vertical.

7.
AI-referral traffic surfaced properly in GA4.

Custom events, referrer classification, and UTM handling rebuilt so AI-assisted sessions show up as a distinct channel - with engagement rate, conversion, and booking data attached to the correct bucket instead of being folded into organic.

8.
Landing architecture matched to prompt intent.

Emergency prompts routed to phone-first, hours-above-fold pages. Implant prompts routed to treatment pages with pricing and consultation booking. Cosmetic prompts routed to case galleries. Every citation earned had a page built to convert the intent behind it.

Results

Six months. Zero to full coverage.

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Every citation is dated and screenshot-verified. The pattern of AI Overviews moving ahead of ChatGPT repeats across engagements. 

The engagement metrics moved in the same window:

  1. Organic sessions in May: 112, up from 72 in December (+56%)
  2. Organic key conversions in May: 105, up from 69 (+52%)
  3. Organic engagement rate: 72.3%
  4. Improved Quality Scores, contributing to lower CPCs and more efficient campaign performance
  5. 61 appointment-booking conversions in May from organic and AI-assisted traffic
Phone clicks, direction requests, form enquiries - tracked alongside bookings.

For agencies

The same system, applied to your clients

This programme is available white-label. Your brand, your client relationship, your strategy. The delivery and measurement sits with Mavlers.

  1. Same system - The eight-factor programme applied to your client's specific prompts and local market.
  2. Your baseline -  A measurable starting snapshot per client, so movement is provable from day one.
  3. Fixed cost, no headcount -  Add AI search to your service offering without building a new team.
  4. Next step -  pick one client and one set of buyer prompts. The baseline snapshot runs first. You bring the result to the table.

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Sandra Field

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