Four-site dental group: from scattered enquiries to booked consultations
An illustrative four-site dental group spends heavily on implant and cosmetic advertising, but enquiries arrive through five channels and nobody can say which campaigns produce booked consultations. The system puts every enquiry in one place, answers it within minutes, follows up unaccepted treatment plans and reports accepted treatment by campaign and practice.
This is a worked example: a realistic scenario we've built to show how we'd approach the problem. The organisation is fictional, and every number is a stated assumption or a calculation from those assumptions. It is not a client case study and makes no claim about results.
The situation
The group has grown by adding practices, and each one handles enquiries its own way. Website forms land in a shared inbox that is checked between patients. Facebook and Instagram messages wait in the Meta inbox until someone has time. Calls ring at the front desk, and when the desk is busy they go to voicemail.
Marketing reports clicks, form fills and cost per lead. The practice management system knows who booked and which treatment was accepted. Nothing joins the two, so the owners can't tell whether the implant campaign produces implant consultations or calls about check-ups. Treatment plans for implants and aligners are presented, then followed up when someone remembers.
The do-nothing baseline is easy to predict. Campaigns scale, enquiry volume rises, the front desk stays the same size, response times stretch further and budgets get cut by instinct rather than evidence.
Constraints we'd work within
- Clinical records and the appointment book stay in the existing practice management system. The group has no appetite for a migration.
- Advertising, including social posts, landing pages and any reviews the group republishes, must meet s133 of the National Law: no testimonials about clinical aspects of care, and any offer must state its terms and conditions.
- Enquiry and treatment details are health information. Using them for direct marketing needs the patient's consent, and SMS and email follow-up must meet the Spam Act's consent, identification and unsubscribe rules.
- Front desk teams are already at capacity, so every new step has to take less time than the one it replaces.
- AI may help with wording and logistics, never with clinical advice. Anything clinical goes to a clinician.
What the Diagnostic would find
Findings by lens, with the commercial effect of each. See how the Diagnostic works.
| Lens | Observation | Commercial effect |
|---|---|---|
| Operations & process | Web forms, social messages and voicemails are answered between patients, so first responses range from a few minutes to the next day. Enquiries made in the evening, when many people research treatment, wait until morning. | High-intent implant and cosmetic enquiries cool off or book elsewhere, so part of the advertising budget is spent twice to win the same patient. |
| Data & reporting | Ad platforms report leads and the practice system reports bookings, with no shared identifier between them. Phone calls carry no source at all. | Budgets are set on cost per lead, which rewards cheap enquiries rather than booked consultations. The group can't tell which campaign or practice produces accepted treatment. |
| Workforce capability | Front desk staff re-key form details into the practice system, write phone messages on paper and forward social messages as screenshots. Each practice has its own wording for fees, payment plans and what happens at a consultation. | Admin grows with every campaign, details get lost or mistyped, and patients get different answers depending on which practice they contact. |
| Growth & marketing maturity | Unaccepted treatment plans have no follow-up process. Whether a patient hears from the practice again depends on the clinician and how busy the week is. | Patients who were interested enough to attend a consultation drift away, and the cost of acquiring them is written off. |
| Risk, governance & change readiness | Practice managers boost posts and share reviews independently. One practice's social page republishes patient reviews that praise treatment results. | Under s133, reviews about clinical aspects of care used in advertising are testimonials. Ahpra lists maximum penalties of $120,000 per offence for a body corporate, and the exposure sits with the group. |
| AI readiness & opportunity | Most first questions are about fees, payment plans, parking, hours and what a consultation involves. Some staff already paste enquiries into a free chatbot to help with wording. | Drafting replies from approved answers is a strong fit for AI, but the current unofficial use puts health information into a public tool, which the OAIC advises against. |
The moves
Every recommendation resolves to one of nine moves: build, buy, improve, integrate, automate, remove, change, train or leave alone. Building is only one of them.
- Leave alone
The practice management system. It remains the clinical record and appointment book. We connect to it rather than replace it, because the migration risk outweighs any gain.
- Buy
An established CRM platform with access controls, an audit trail and suitable data hosting, plus a call-tracking service. For a group of four practices, a custom CRM wouldn't earn back its cost.
- Integrate
Website forms, Meta lead forms and messages, tracked calls and Google Ads all feed the CRM. Bookings and accepted treatment come back from the practice system, within what its integration options allow, so every enquiry carries its source through to the outcome.
- Automate
Instant acknowledgement by SMS and email with a booking link, routing by practice and treatment, an alert when an enquiry sits untouched beyond an agreed time in opening hours, and treatment-plan follow-up for patients who have consented.
- Build
A library of approved answers that the AI drafts replies from, and a booked-revenue dashboard. Staff review and send every draft; the assistant can't send on its own.
- Improve
Treatment and practice pages rewritten to answer patients' real questions, with structured data and a Google Business Profile for each practice, so search engines and AI assistants describe each location accurately.
- Change
One advertising approval process, run centrally, with a checklist against s133 and Ahpra's guidelines. Practice managers stop boosting posts on their own, republished reviews are limited to unedited non-clinical comments, and the shared inbox, paper message pads and the free chatbot are retired.
- Train
Front desk teams on the new inbox, reviewing AI drafts and logging call outcomes. Treatment coordinators on the follow-up process and what can and can't be said in it.
The system, end to end
Every enquiry lands in the CRM with its campaign, channel and practice attached, gets an instant acknowledgement, and a staff member sends an AI-drafted reply after checking it. Bookings and accepted treatment flow back from the practice management system, so the dashboard shows spend, enquiries, consultations and accepted treatment by campaign and practice.
- Google Ads, Meta and search
- Web forms, calls and social messages
- CRM record with source attached
- Instant acknowledgement and AI-drafted reply
- Staff review and booking in the practice system
- Treatment-plan follow-up
- Booked-revenue dashboard
One enquiry inbox
Website forms, Meta lead forms, Facebook and Instagram messages and tracked calls create or update a single CRM record, matched on phone and email and tagged with practice, treatment interest and source campaign.
Call tracking by campaign and practice
Tracking numbers on ads and the website, missed-call alerts with an SMS reply, and a quick outcome log for staff, so calls are counted alongside forms.
Approved answers and AI drafting
A library of answers on published fees, payment plans, parking, hours and what happens at a consultation, each checked against s133. The assistant drafts only from this library, flags anything clinical for a clinician and never sends without a person.
Treatment-plan follow-up
When a plan isn't accepted within an agreed period, the coordinator gets a task and consenting patients receive plain, factual messages offering a second conversation. No urgency tactics, and no offers without their terms.
Booked-revenue dashboard
Spend, enquiries, response times, consultations booked and attended, and treatment accepted, by campaign, treatment and practice, refreshed daily from the CRM and the practice system.
Compliant search content
Treatment and practice pages, FAQs and structured data, published through a pre-launch checklist covering testimonials, before-and-after images, offers and practitioner titles.
Delivery stages
Indicative timings.
Diagnostic and data map
Map every channel and handover, sample current response times, confirm the practice system's integration options and consent records, and set the baseline for every measure.
2 to 3 weeks (indicative)
Capture and tracking
CRM, call tracking, and form and message integrations, piloted at one practice before the other three.
4 to 6 weeks (indicative)
Response and follow-up
Approved-answer library, AI drafting with staff review, routing rules, treatment-plan follow-up and front desk training, rolled out practice by practice.
4 to 6 weeks (indicative)
Booked-revenue reporting
Practice system sync, the dashboard, and a monthly review that moves budget decisions from cost per lead to cost per booked consultation.
3 to 4 weeks, then monthly (indicative)
Search and content
Treatment and practice pages, Google Business Profiles and the compliance checklist, running alongside the other stages.
Ongoing from month 2 (indicative)
The arithmetic
Assumptions first, then the calculations they produce. Change an assumption and the result changes with it, which is the point.
| Assumption | Value |
|---|---|
| Enquiries per month, all channels and practices | 600 (assumption) |
| Enquiries about high-value treatment (implants, aligners, cosmetic) | 25% of all enquiries (assumption) |
| Staff handling time per enquiry, including re-keying and chasing | 6 minutes today, 3.5 minutes with one inbox and AI-drafted replies (assumption) |
| High-value enquiries that book a consultation | 30% today, 34% with faster replies and follow-up (assumption, modelled scenario) |
| Booked consultations that lead to accepted treatment | 40% (assumption) |
| Average accepted value of a high-value treatment plan | $5,000 (assumption) |
| Advertising spend | $20,000 a month, aimed at high-value treatment and paid directly to the platforms (assumption) |
| Enquiry growth over 12 months if campaigns scale and nothing else changes | 15% (assumption) |
Front desk handling time
Today: 600 × 6 min = 3,600 min = 60 hours a month. Improved: 600 × 3.5 min = 2,100 min = 35 hours a month. (60 − 35) × 12 months
About 300 hours a year released across four front desks (modelled)
Do-nothing baseline for the front desk
600 × 1.15 = 690 enquiries a month × 6 min = 4,140 min
69 hours a month of handling for the same team, up from 60 (modelled)
Booked high-value consultations
600 × 25% = 150 high-value enquiries. Today: 150 × 30% = 45. Improved: 150 × 34% = 51
6 more booked consultations a month (modelled)
Accepted treatment value from those consultations
6 × 40% = 2.4 accepted plans a month × $5,000 = $12,000 a month × 12 months
About $144,000 a year in accepted treatment. Revenue, not profit, and a scenario rather than a forecast (modelled)
Cost per booked high-value consultation
Today: $20,000 ÷ 45 = $444. Improved: $20,000 ÷ 51 = $392
About $52 less per booked consultation at the same spend (modelled)
What we'd measure
- Median time to first response, in and out of opening hours, by practice
- Share of enquiries and calls with a known source campaign
- Cost per booked consultation, by campaign and treatment
- Consultation-to-accepted-treatment rate, by practice and treatment
- Unaccepted treatment plans with a follow-up conversation inside the agreed period
- Front desk handling time per enquiry, sampled each month
Risks and how we'd manage them
Practice system integration limits
Some practice management systems offer limited integration. We confirm what's possible in the Diagnostic. Where there's no live sync, we use a scheduled export or a booking-outcome field that staff complete, and the dashboard shows which figures are measured and which are matched.
Front desk adoption
A new inbox fails if it adds clicks. We pilot at one practice, design the workflow with the front desk team, switch off the old channels once the new one works, and check handling time before rolling out further.
AI drafts that stray into clinical advice
The assistant drafts only from approved answers, can't send without a person, and routes clinical questions to a clinician. We test it on de-identified past enquiries before launch and review a sample of drafts every month. Patient details stay in business platforms with access controls, never in public AI tools.
Advertising rules, privacy and consent
Every page, ad and follow-up message goes through the s133 checklist before it's published. We check against the rules, but we aren't lawyers, so complex cases go to the group's legal adviser. Marketing follow-up goes only to patients who have consented, and unsubscribe requests are actioned within the five working days the ACMA requires.
The takeaway
In this example the biggest gain doesn't come from spending more on ads. It comes from answering every enquiry quickly, following up patients who were already interested, and tracing spend to accepted treatment, so budget decisions rest on booked consultations rather than lead counts.
Services in this example
- Business process automationAutomate intake, quoting, follow-up, onboarding and reporting across the systems you already use. Measured in hours released, with people on exceptions.
- AI-augmented workforceHelp your existing team do more valuable work with AI: role-based training, approved tools, prompt libraries and adoption tracking. Capacity, not cuts.
- System integrationsConnect your CRM, Xero, job system and email so nobody re-keys data. APIs, webhooks and sync rules, plus monitoring that alerts you to failures first.
- Reporting & dashboardsOne source of truth for finance, sales, marketing and operations: agreed definitions, automated data pipelines and AI commentary that explains the numbers.
- Paid mediaGoogle, Meta, LinkedIn and YouTube ads managed to booked revenue, with CRM sales sent back to the platforms. Spend paid direct to them, never marked up.
- SEO & GEOTechnical, local and AI search optimisation so Google, ChatGPT, Perplexity and Copilot can find, trust and cite you. No ranking promises, just the work.
Recognise your business in this?
A 30-minute call is enough to tell whether the same moves would pay off for you.
Sources
Third-party facts on this page, checked 14 October 2026.
- Testimonials: Understand the requirements, Australian Health Practitioner Regulation Agency (Ahpra). www.ahpra.gov.au/Resources/Advertising-hub/Resources-for-advertisers/Testimonial-tool.aspx
- Advertising and the law, Australian Health Practitioner Regulation Agency (Ahpra). www.ahpra.gov.au/Resources/Advertising-hub/Advertising-guidelines-and-other-guidance/Advertising-and-the-law.aspx
- Communications with patients, Office of the Australian Information Commissioner. www.oaic.gov.au/privacy/privacy-guidance-for-organisations-and-government-agencies/health-service-providers/communications-with-patients
- Avoid sending spam, Australian Communications and Media Authority. www.acma.gov.au/avoid-sending-spam
- Guidance on privacy and the use of commercially available AI products, Office of the Australian Information Commissioner. www.oaic.gov.au/privacy/privacy-guidance-for-organisations-and-government-agencies/guidance-on-privacy-and-the-use-of-commercially-available-ai-products