Inpatient / Residential · Paid Media
How an Inpatient Rehab Facility Scaled to 95 Admits While Cutting Cost Per Admission by 24%
Campaign consolidation and PMAX optimization drove 30% admission growth with improved efficiency — all while spending less.
TL;DR
The Short Version
The Problem
- Fragmented campaigns starving Google's algorithm of conversion data
- White PMAX struggling with high costs and landing page issues
- Budget split across too many ad groups to optimize properly
The Strategy
- Consolidated fragmented campaigns into unified structures
- Paused, fixed, and relaunched White PMAX with better landing pages
- Shifted focus from lead volume to VOB quality metrics
The Result
- 30% more admissions in Q3 vs Q2 while spending slightly less
- $3,617 savings per admission vs. Q2
- White PMAX became one of the most efficient campaigns at $11,572 CPA
The Challenge
A Fragmented Paid Media Strategy Was Capping Growth
An inpatient rehab facility came to us in Q2 2025 facing a common paid media problem: fragmented campaigns weren't generating enough volume for Google's algorithms to optimize effectively. Their strategy of splitting campaigns to control costs had backfired — budget was spread too thin across multiple ad groups, preventing Google's systems from learning which audiences actually converted to high-value admissions.
Additionally, their White PMAX campaign was underperforming with high CPAs and landing page issues that hurt conversion rates. They needed a complete strategy overhaul to scale admission volume while improving cost efficiency.
- Q2 2025 Baseline
- 73 admits per quarter
- $15,177 cost per admission
- PMAX struggling with conversion issues
Core Problems
Algorithm StarvationNot enough conversion data in any single campaign for Smart Bidding to optimize properly
Wrong Quality SignalCampaigns optimizing for lead volume instead of VOB quality, attracting the wrong patients
PMAX Landing Page FailuresWhite PMAX driving traffic to pages that weren't converting, inflating CPA
Inefficient Budget SplitToo many campaigns competing for the same budget, diluting performance across the board
The Strategy
Three Shifts That Unlocked Algorithmic Performance
Rather than patch the existing structure, we overhauled the campaign architecture and changed the core optimization goal — from volume to quality.
01
Campaign Consolidation
We reversed the fragmentation strategy by merging all ad groups back into main campaigns. This gave each campaign sufficient budget and conversion data for Google's algorithms to properly optimize for high-value VOBs. Instead of trying to manually control costs through splitting, we let consolidated budgets and smart bidding drive efficiency.
02
PMAX Pause, Fix & Relaunch
Rather than accepting poor PMAX performance, we made the decision to pause, rebuild landing pages, and relaunch with refined conversion goals. This allowed the algorithm to restart learning with better quality signals and improved user experience. White PMAX became one of our most efficient campaigns within weeks of relaunch at $11,572 CPA.
03
Quality-First Targeting Refinements
We implemented geo-targeting with insurance coverage layers to pre-qualify leads. Device bid adjustments optimized the mobile vs. desktop performance mix, and demographic refinements based on weekly performance patterns ensured budget flowed to the highest-converting audience segments.
What We Did
Execution Across Every Layer
Campaign Architecture Overhaul
- Consolidated fragmented campaigns to restore algorithm learning
- Merged ad groups into unified campaigns for better optimization
- Implemented low-intent conversion actions to focus Smart Bidding on quality
Landing Page & Creative Refresh
- Rebuilt landing pages to reduce bounce rates and improve qualification signals
- Implemented periodic creative rotations to combat ad fatigue
- Fresh landing pages showed +357% test volume growth in search campaigns
Advanced Audience Optimization
- Geo-targeting with insurance pre-qualification layers
- Device bid adjustments for mobile vs. desktop optimization
- Weekly demographic refinements based on performance data
Algorithm Optimization
- Shifted focus from lead volume to VOB quality metrics
- Relaunched underperforming campaigns with conversion goal refinements
- Removed low-intent actions, allowing Smart Bidding to optimize for admit quality
The Results
Q3 2025: A Breakthrough Quarter
Admission Growth
30%
More admits in Q3 vs Q2 — 95 vs 73 — while spending slightly less budget
CPA Improvement
24%
Reduction in cost per admission — from $15,177 down to $11,560 per admit
Efficiency Gains
$340K+
In total efficiency gains on current admission volume — $3,617 saved per admit
Admissions Performance
- 95 total admits vs. 73 in Q2 — 30% growth quarter over quarter
- Achieved while spending flat compared to Q2
- Demonstrated true efficiency gains, not just increased spend
Cost Per Admission
- $11,560 CPA — down from $15,177 in Q2
- $3,617 savings per admit vs. prior quarter
- $340,000+ in total efficiency gains on current volume
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Why This Strategy Worked
01
Trusting the Algorithm with Sufficient Data
Campaign consolidation gave Google's Smart Bidding enough budget and conversion data to properly optimize. This counterintuitive move — giving up manual control — actually improved performance across the board.
02
Quality Over Volume Focus
Shifting optimization from lead generation to VOB quality metrics meant the algorithm learned what a good admit actually looked like for the facility's business model. We focused on generating $2,000+ daily payer VOBs, not just any VOBs.
03
Willingness to Pause and Rebuild
The White PMAX turnaround showed the value of being strategic about when to persist and when to reset. Pausing to fix fundamental issues — then relaunching — delivered better results than trying to optimize broken campaigns in place.
04
Granular Targeting Refinements
Geo-targeting with insurance coverage layers, device optimizations, and demographic adjustments ensured budget flowed to the highest converting segments without fragmenting campaigns or starving the algorithm.
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