Jefferson Dental & Orthodontics

The brand

Jefferson Dental & Orthodontics is a large regional dental services organization with more than 60 offices throughout Texas, providing dental and orthodontic care through what they call their "Smile Roadmap."

Challenge

A new CEO and marketing leadership arrived in 2024 with a suspicion that the company was over-invested in certain channels. They couldn't get to the true unit economics of media spend, and they didn't fully trust what Google Analytics or the ad platforms were telling them.

Dental services organizations have a structural problem here. Patient CRM, patient billing, and marketing systems tend not to talk to each other, so the data fragments and leaders lose visibility exactly where they need it most.

The team was also onboarding a new agency partner, and wanted a clear read on media efficiency to orient the new go-to-market strategy.

Approach

The framing question matters more than it sounds. Measurement has to target outcomes marketing can reasonably drive, like appointments booked, while also drawing a straight line to the unit economics a CFO cares about, like appointments completed. Both became dependent variables.

The work ran as a structured Advanced Attribution Audit:

• Data harmonization. Eighteen months of history on appointments, revenue, and media, processed for modeling.
• Preliminary analysis. Trend analysis, correlations, and a basic MMM to test how individual variables fit against appointments and revenue.
• Marketing mix modeling. Thousands of iterations and hundreds of tranches across segments to find best-fit models explaining appointment drivers for new and existing patient groups.
• Triangulation. Using the MMM decompositions to understand what media contributed to both bookings and completed appointments.

Channels analyzed included Google Search (brand and non-brand), Facebook, CTV, and direct mail.

The Marketing Accounting Framework was built around incremental scheduled appointments, completed appointments, and production revenue driven by media, split across new and existing patient cohorts. That produced a 4 P&L structure: one model each for new patient booked, new patient completed, existing patient booked, and existing patient completed.

Results

What it meant

Growth was available inside the existing budget by shifting toward tactics that performed better on incremental appointments. The models also pointed to where incrementality testing and geospatial analysis would tighten confidence before scaling any of those shifts.

The outputs validated what the marketing team's instinct had been telling them, which is worth something on its own. They also raised hypotheses that needed testing. Those tests refine the models and update iROAS figures, so that big investment moves rest on validated numbers rather than a single modeling round. Growth here is iterative by design.