The number your portfolio average is hiding
In a 100-location healthcare platform, a same-site growth number of 6 percent sounds healthy. But that number might be concealing 20 locations growing at 15 percent and 20 locations that are flat or declining – with the remaining 60 somewhere in the middle. The average is real. The average is also misleading.
When operating partners and sponsors evaluate same-site performance, they are not just looking at the portfolio number. They are looking for evidence that you understand why the variance exists and have a plan to close the gap at the underperforming locations. A CMO who can only report the average is reporting on the symptom. The ones who survive scrutiny can explain the distribution.
Four variables that drive same-site variance – and the one most often misread
Not all location performance variation has the same cause, and treating it as if it does leads to generic solutions that don’t work. The variables that explain same-site underperformance generally fall into local market conditions, patient mix, service mix, and marketing execution – and most platforms stop at local market conditions because it’s the easiest explanation to accept.
Of the four, local market characteristics is the one CMOs most often use to explain underperformance when marketing execution is actually the issue. “It’s a tough market” is a plausible explanation for one location. When it’s the explanation for six locations in six different geographies, it’s worth examining whether the market is the variable or the marketing is. Local market factors are largely fixed. Marketing execution quality is the most addressable lever in the set – which makes it the most important one to isolate correctly.
High-margin services require a different kind of marketing
Elective procedures, complex care pathways, specialty consultations, and premium service tiers represent the highest-margin production available to most multi-site platforms. They’re also the services most sensitive to marketing – because they require more from the patient before they say yes.
A patient pursuing a routine annual visit needs a reminder and a convenient appointment. A patient considering a significant elective procedure or complex care commitment needs to be educated about the benefits, confident in the provider, and given a reason to act now rather than defer. Marketing campaigns built around that patient journey – that address the education gap, build provider credibility, and reduce commitment friction – directly improve case acceptance rates. That’s the mechanism that shifts the production mix.
Building the matrix: what to score and how to read it
A location-level performance matrix scores each site across five same-site metrics: revenue per active patient, high-margin service percentage, new patient acquisition rate, lapsed patient rate, and same-site revenue growth trend over the trailing four quarters. Each metric is normalized relative to the portfolio median rather than an absolute benchmark – performance context matters more than absolute numbers when locations operate in different service categories and markets.
When locations are scored and ranked on these dimensions, patterns emerge quickly. A location in the bottom quartile on lapsed patient rate and high-margin service percentage but near the median on new patient acquisition has a retention and mix problem, not a top-of-funnel problem – which means the marketing response should be reactivation and service mix campaigns, not awareness spend. A location in the bottom quartile on new patient acquisition but above median on everything else has a top-of-funnel constraint. The matrix doesn’t prescribe the solution, but it makes the diagnostic specific enough to act on.
Letting location data drive budget allocation
Most multi-site platforms allocate marketing budget by location count or revenue – a roughly equal distribution that treats a high-performing location the same as a struggling one. A location-level performance matrix enables a more deliberate approach.
In practice, this means establishing two or three defined investment tiers based on performance quartile and diagnostic profile. Locations in the bottom quartile with a clear marketing gap – where the matrix shows underperformance on metrics that marketing directly influences – receive a weighted budget premium, typically 1.5 to 2x the per-location baseline, with campaign strategies matched specifically to their diagnostic. Locations performing above portfolio median may maintain baseline investment or shift budget toward service mix and retention programs rather than new patient acquisition. The reallocation isn’t permanent – it’s reviewed quarterly as performance moves. That cadence is what makes it a management tool rather than a one-time exercise.
Why attribution infrastructure has to come first
Location-level benchmarking is only actionable if the attribution infrastructure exists to connect marketing activity to location-level outcomes. Without it, the matrix can identify under performers but cannot distinguish whether marketing is the cause, the solution, or irrelevant to the gap.
The infrastructure required is not exotic, but it has to be consistent across every location: call tracking numbers that route and record by location, campaign-specific landing pages with conversion tracking, and CRM or practice management integration that connects a scheduled appointment back to the campaign that generated the inquiry. When those three elements are in place and working together, a campaign that drove 40 new patient inquiries at Location A can be compared directly against the same campaign at Location B – and the performance gap becomes a specific, investigable question rather than an unexplained variance.
“Portfolio averages are a reporting tool. They’re not a management tool. The work happens at the location level.”
The point of the matrix is to stop averaging
Location-level benchmarking is not analysis for its own sake. It is the precondition for moving from portfolio-level marketing to location-specific marketing – and that shift is where the same-site EBITDA improvement actually comes from.
A reactivation campaign deployed uniformly across 100 locations will produce uniform-ish results. The same budget deployed selectively – concentrated at the 20 locations where the lapsed patient rate is highest and the reactivation opportunity is largest – produces materially better returns on the same spend. The matrix is what makes selective deployment possible. Without it, you’re averaging. With it, you’re allocating. Those two things produce different outcomes at scale, and the difference shows up in same-site EBITDA.
Agency Creative builds the analytics infrastructure and campaign strategies that make location-level benchmarking actionable. Let’s start with a portfolio diagnostic. Most platforms are surprised by what the location – level data actually shows – and where the budget has been going that shouldn’t be.
Learn how Agency Creative can help boost your brand by calling us at 972.488.1660 or by contacting us online.
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