Case Study · Dental Lead Generation
Five years. $150K per month scaled to $400K+. Cost per scheduled appointment reduced 50 to 100 percent depending on market and traffic source. 1,000 appointments per month at peak.
A national dental lead generation company connecting cosmetic dentistry patients with participating dental practices came to LGG Media in 2020 spending $150K per month. The dental practices buying leads measured one outcome: patients who showed up. Our approach for this vertical is on the dental lead generation service page.
The business model required patients to complete a four-step process. Submit an inquiry, complete a financing application, schedule a consultation, and show up for that appointment.
The campaigns were optimizing on form submissions. That is the first step in the funnel and the least predictive of whether a patient would complete all four.
Cost per scheduled appointment ranged from $600 to $800 before the shift, depending on market and traffic source. The target after the shift was under $400.
A single conversion event at form submission tells the algorithm nothing about steps two, three, and four. Each drop-off point is a distinct population with distinct traffic characteristics.
A prospect who submits a form but never completes the financing application is different from one who completes it but does not schedule. A prospect who schedules but does not show up is different again.
Without separate conversion events at each stage, the algorithm cannot tell these groups apart. It optimizes toward the cheapest early action instead of the outcome the practices pay for.
LGG Media mapped four conversion events to the patient journey: inquiry submission, financing application completion, appointment scheduled, and appointment confirmed. Each carried a distinct weighted value reflecting its proximity to the show-up event.
A custom API connected the company's proprietary CRM to a conversion tracking server. Every significant event fired with the device fingerprint and original click ID attached.
A completed financing application carried one weighted value. A scheduled appointment carried a higher one, set to reflect its closer proximity to the show-up the practices paid for.
Both application and appointment payloads passed to Google Ads and Meta with those weighted values. Budget shifted toward traffic that completed both steps, not traffic that stalled at inquiry.
The reduction did not come from spending less. Monthly spend grew from $150K to $400K+ over the same period. Cost per appointment fell because the algorithm concentrated budget on the traffic patterns that produced patients who scheduled and showed up.
Monthly spend scaled from $150K to over $400K while cost per scheduled appointment fell from the $600 to $800 range to under $400, a reduction of 50 to 100 percent depending on market. At peak the account produced roughly 4,000 completed financing applications per month at under $100 each and 1,000 scheduled appointments per month at under $400 each. Both cost targets held as spend grew past two and a half times the starting level.
The engagement ran for five years. At its conclusion in Q1 2025, cost per application held under $100 and cost per scheduled appointment held under $400 across all active markets. The partnership ended due to business challenges the company faced that were unrelated to advertising performance.
The four-step architecture produced a market-level performance map the company had not previously had. Every appointment event carried the practice location. Every show-up confirmation was matched back to the originating click and market.
Over time, the data identified which markets produced patients who completed all four funnel steps and which produced high inquiry volume with low follow-through. The company used that map to run two decisions off the same conversion data.
The first was campaign budget. Markets with strong show-up rates received more spend; weak markets received less or were paused. The second was recruitment. New practice partnerships were prioritized in markets where the data showed the strongest patient completion rates.
This is the same pattern documented in the immigration law firm case study, attribution data informing physical location decisions beyond its primary function as an advertising tool.
Explore the approach: Dental lead generation → · Lead generation →
The infrastructure behind it: device fingerprinting, click-level attribution, and offline conversion sync are the same stack we deploy on every account. How the attribution layer works → See how the underlying tracking works in our guides to Google Ads call tracking and offline conversion tracking.
The same discipline applied to your highest-value cases: see our dental implant marketing page.
Next Step
If application completion and appointment show-up rates are inconsistent across markets, the conversion signal reaching the algorithm is missing the funnel stages that predict revenue.
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