Driving operational efficiencies for an oculofacial plastic surgery practice.

This engagement was a Year 1 result. The clinic engaged in April 2025. By year-end, tracked ROAS landed at 4.26× with $305K in Year 1 new-patient revenue and 42 ops hours saved every month. Cost per paid lead came in at $131.66 and continued declining month-over-month.

The unlock is attribution. Most oculofacial practices we audit are running paid spend with no way to tie a click back to a booked procedure. Once the platform is wired into the EMR, the ROAS picture becomes real inside 60–90 days, and you can start optimising on the actual booking signal instead of proxy form-fills.

It unlocks end-to-end attribution, click → lead → consult → booked procedure, all in one ledger. Before the integration, this clinic was running three disconnected systems (paid platforms, intake forms, EMR) with manual reconciliation between them. After, marketing, intake, and operations all spoke the same language.

The downstream effect was 42 hours of ops time recovered every month, capacity that went straight back into care delivery and patient experience instead of back-office reconciliation work. healthhue.com covers the full platform.

Three sources of revenue don’t make it into the ad platform’s default ROAS calculation: phone calls that never touch a form, patients running ad blockers that strip the conversion pixel, and cross-device journeys where the patient researches on one device and books on another.

For a high-consideration surgical procedure like blepharoplasty or brow lift, those three categories make up the majority of bookings. When we factored that revenue back in, the real ROAS landed closer to 6×. The dashboards are conservative on purpose, the actual money is always bigger than the platforms report.

Yes, especially for surgical practices, because procedure searches are high-consideration, comparison-heavy, and the AI engines are increasingly where that comparison happens. This clinic’s organic search footprint went from 271 to 991 in four months after we built the AI Lead Generation foundation. That visibility produced $280K+ in AI Lead Generation revenue inside Year 1.

Traditional search optimisation targets Google’s blue-link results. AI Lead Generation, built on Generative Engine Optimization, engineers content and schema so ChatGPT, Gemini, Claude, and Google AI Overviews cite the practice when patients ask comparison or recommendation questions about specific procedures.

Operational efficiency is a revenue multiplier, not a cost-saving line item. Recovered ops capacity becomes new-patient capacity, the 42 hours a month that used to go to manual attribution, intake reconciliation, and follow-up scheduling went straight back into care delivery and patient experience.

For a procedure-led surgical practice where consult-to-booking conversion is the throttle on growth, more time with patients translates directly into higher booking rates, better surgical-day prep, and better post-op continuity, which is what drives the next round of referrals.

The patient is on a longer, higher-consideration journey. A medspa patient might book Botox the day they see the ad. A blepharoplasty patient researches across weeks, compares surgeons, watches before-and-afters, and books a consult before booking the procedure. The funnel has to hold up across that full window, not just the first click.

That’s why attribution is everything here. Without end-to-end tracking, you can’t see which channels are actually driving the procedure bookings, you can only see which channels are driving the consult requests, which is a leading indicator at best. The Health Hue platform → OSCAR Pro integration is what closed that loop for this practice.