When a multi-location aesthetic clinic group in southern Taiwan set out to make its paid-social budget work harder, leadership recognized that spending more would not by itself close the gap between cost and reach. Leaders wanted clear, evidence-based visibility into which channel, placement, and region actually converted that spend into reach.
The Opportunity
A familiar channel, an unproven allocation
Throughout 2024, the clinic ran all of its paid social advertising through a single social advertising network, spanning two channels' feed, stories, reels, and related placements. Spend followed a pattern shaped less by evidence than by history: the incumbent channel, the one the clinic had used the longest, absorbed the large majority of every media dollar, while the emerging channel received a comparatively small share. Reporting told the team how much had been spent and how many impressions resulted, but did not explain which channels, placements, or regions were doing the heavy lifting.
That gap mattered because aesthetic and cosmetic treatments depend heavily on repeated visibility and brand familiarity to move a prospective patient toward booking a consultation, and the clinic was operating on a comparatively modest annual media budget with little room for inefficiency. Leaders recognized that continuing to allocate spend by habit risked leaving low-cost reach on the table. They set out to build a rigorous, evidence-based view of where the budget was actually converting into visibility, across platform, placement, and region.
The Solution
A channel-level model built for a lean budget
To answer that question, Vizuro built a marketing mix model using a full year of weekly spend and impression data across the clinic's two paid-social channels.
Rather than reallocating budget by habit, the model works as a channel-level decision engine across three areas.
Each estimate carries a plausible range rather than a single fixed number, giving the clinic a conservative basis for its next budget decision, particularly with a single year of data behind it.
The same lens was then applied one level down, to individual placements and to the regions where each ad ran, giving the clinic a channel, placement, and regional view of where budget was truly converting into reach — and where it was not.
The Impact
Where the budget was already working, and where it could work harder
The clearest finding was also the simplest: across the full year, the emerging channel delivered impressions at roughly one-eighth the incumbent channel's cost per thousand, yet received well under a third of total spend. The incumbent channel, still the default, accounted for the large majority of the budget while contributing a comparatively small share of the impressions the model attributed to paid social.
The gap was sharper at the placement level, and regional spend concentration matched the clinic's own footprint in southern Taiwan, with close to three-quarters of the budget sitting across four core cities and one adjacent market identified as a candidate for a modest test increase.
What's Next
From reach to revenue
The reallocation the model points to is a starting point rather than a finish line. The next phase of this work is designed to move from a reach-based view of performance to a revenue-based one, incorporating conversion tracking so that future budget decisions connect directly to consultation bookings rather than impressions alone. A complementary click-based objective, aimed at re-engaging people who have already interacted with the clinic's ads, is positioned to extend the current awareness-led approach further down the funnel. As this next phase takes shape, Vizuro will continue to work alongside the client, turning each new stage of measurement into a practical next step for the budget.