How Northwind Dental Tripled Implant Consults Without Increasing Ad Spend
A six-location dental group was spending $22,000 a month to generate cleanings it lost money on. We rebuilt the account around case value and tripled high-value consults on the same budget.
- +212%
- Implant consults / month
- Flat
- Ad spend
- -64%
- Cost per implant consult
- -19pts
- Consult no-show rate
From 17 to 53 booked consults per month
Held at $22k/month for the full engagement
From $1,294 to $415
From 31% to 12%
Results over time
- Traffic
- Leads
- Revenue
Indexed to 100 at the start of the engagement. We publish the shape of the growth, not the client's absolute revenue.
Overview
Northwind Dental runs six locations across the Pacific Northwest. Strong clinical reputation, healthy hygiene book, and a growing implant and orthodontics practice that was not filling. They came to us after two years with a agency that reported enthusiastically on lead volume.
The problem
The practice was generating roughly 300 leads a month at an apparently excellent $58 per lead. The problem was what those leads were. Nearly 80% were hygiene enquiries worth around $90 each, against implant cases worth $4,000+ that the practice had capacity for and was not filling. The account was optimised, precisely and expensively, for the wrong outcome.
Research
We started with tracking, because we did not trust the numbers. Within a week we found that form fills and calls were both being counted, and roughly 20% of "leads" were the same person doing both. Actual lead volume was closer to 240. We then pulled 18 months of practice-management data and joined it to the ad account for the first time, which let us see close rate and case value by campaign rather than by guess.
Strategy
Segment ruthlessly by case value. Separate campaigns, budgets and targets for implants, orthodontics, cosmetic and hygiene. Feed real case values back into Google so smart bidding was chasing revenue rather than form fills. Then rebuild the implant landing experience, which was a generic contact page doing nothing to address the two things implant patients actually worry about: pain and cost.
Implementation
We rebuilt the account over six weeks, then spent three months on landing pages and tracking before touching budget. Budget stayed flat at $22,000 a month for the entire engagement — every gain came from allocation and conversion rate, not spend.
What we actually did
Google Ads
Rebuilt from a single catch-all campaign into four value-segmented campaigns with offline conversion imports.
- Split campaigns by procedure value, with separate tCPA targets per segment
- Imported closed-case values from the practice management system via offline conversion tracking
- Cut 340 search terms that had produced zero consults in 18 months
- Moved hygiene to a small maintenance budget rather than competing with implants for spend
Local SEO
Six location pages built properly, plus a review engine that made the map pack defensible.
- Rewrote all six location pages around procedure intent rather than "dentist near me"
- Built a post-appointment review request flow, taking the group from 4.2 to 4.8 stars
- Fixed NAP inconsistencies across 40+ directories
Conversion Rate Optimization
Rebuilt the implant journey around cost and pain — the two objections the old page ignored entirely.
- Built a dedicated implant page with transparent pricing bands and financing options up front
- Added a sedation and comfort section addressing pain anxiety directly
- Replaced the generic contact form with a three-question consult booker
Automation
Speed to lead went from 7 hours to under 4 minutes.
- Instant SMS acknowledgement on every enquiry
- Automated reminder sequence cutting consult no-shows from 31% to 12%
“Sellecomm rebuilt our tracking in the first month and showed us 40% of our ad budget was going to searches from people who were never going to book. Cutting that alone paid for the retainer.”
Lessons learned
The counterintuitive result: total lead volume fell 12% and revenue rose 212%. The practice had spent two years optimising a number that was actively misleading them. We also learned to insist on practice-management data access before quoting — without the join between spend and closed cases, we would have been optimising blind like everyone before us.