--- title: "Widespread Wellness" description: "Residential / Inpatient  ·  Paid Media  ·  Multi-State How Widespread Wellness Went From Zero Ad History to 226% QoQ Growth in OON Viable VOBs A brand-new advertiser across 4 facilities, launched simultaneously with no prior data. Webserv built the full conversion architecture from scratch and scaled efficiently every month. Timeline Nov 2025 – Mar 2026 […]" featured_image: "https://webserv.io/wp-content/uploads/2026/06/widespread-wellness.jpg" url: "https://webserv.io/about-us/case-studies/widespread-wellness/" date_modified: "2026-07-02T07:03:55-08:00" okf_concept: "https://webserv.io/okf/case-studies/widespread-wellness.md" related_okf_concepts: - "https://webserv.io/okf/services/paid-search.md" - "https://webserv.io/okf/services/paid-social.md" --- Residential / Inpatient  ·  Paid Media  ·  Multi-State # How Widespread Wellness Went From Zero Ad History to 226% QoQ Growth in OON Viable VOBs A brand-new advertiser across 4 facilities, launched simultaneously with no prior data. Webserv built the full conversion architecture from scratch and scaled efficiently every month. Timeline Nov 2025 – Mar 2026 Service [PPC / Paid Search](https://webserv.io/capabilities/paid-media/) Location Multi-State · 4 Facilities --- QoQ Growth 226% Quarter-over-quarter increase in OON viable VOBs from Q4 2025 to Q1 2026 OON Viable VOBs 166 Total OON viable VOBs delivered across all four campaigns since launch Total VOBs 512 VOBs delivered across the full portfolio in the first five months Cost Efficiency ↓14.2% Drop in cost per OON viable while spend scaled 71.7% over the same period TL;DR ## The Short Version The Problem - Brand-new advertiser with zero conversion history, no prior ad data, and no audience signals - Four separate facilities across multiple states needing campaigns launched simultaneously - OON residential acquisition costs rising nationally due to increased competition and stricter insurance requirements The Strategy - Built full conversion architecture from scratch before scaling any budget - Launched four independent campaigns, each tuned to its own market and competitive landscape - Performance-gated scaling model where every budget increase was earned by prior-period data, not timelines The Result - 226% QoQ growth in OON viable VOBs from Q4 2025 to Q1 2026 - Cost per OON viable declined every month as spend scaled - March alone delivered more viable VOBs than the entire Q4 period combined The Challenge ## Four Facilities. One Launch. No Prior Data to Lean On. Most paid media campaigns get to inherit something: historical keywords, audience lists, conversion trends. Webserv had none of that. When Widespread Wellness came aboard in November 2025, the brief was to stand up four simultaneous campaigns for four distinct behavioral health brands across multiple states, with a blank conversion account and no prior ad signals. The challenge was not just launching. It was launching in a way that would compound over time. The paid search landscape for OON residential treatment is expensive and competitive. Bidding blindly burns budget. Every dollar spent in the early weeks was both a patient acquisition attempt and a data-building exercise for the campaigns that would follow. At the same time, the admissions team was managing significant internal change with new hires coming online and weekly VOB scoring backlogs. Getting clean conversion data back to the campaigns quickly was critical, and it required just as much operational discipline on the client side as campaign execution on ours. In Their Own Words "I want our campaigns to be the best in the nation. I do not want a referral fee. I want these campaigns to crack." Widespread Wellness Group - Starting Point - **Zero conversion history** across all four accounts at launch in November 2025 - **4 independent facilities** each with different markets, insurance landscapes, and competitive dynamics - **Rising acquisition costs** nationally due to increased auction competition and stricter insurance requirements - **Admissions team scaling** while scaling. VOB scoring cadence directly impacts campaign learning speed Core Problems 🔲 **No Historical Data**Zero prior conversion signals meant the campaigns had to build their own audience intelligence from the ground up, with no shortcuts. 🏥 **Four Markets at Once**Each facility had its own competitive landscape. A one-size strategy would have averaged away what was working and hidden what was not. 📋 **Admissions Team in Transition**New staff being onboarded mid-campaign meant VOB scoring delays, which slow campaign learning and stall optimization. 💸 **Expensive, Competitive Market**OON residential acquisition costs were rising nationally. Scaling before the data was ready would have meant paying more for worse results. Our Strategy ## Build the Foundation First. Earn Every Budget Increase. Rather than launching with large budgets and hoping the algorithm would figure it out, Webserv built a phased framework where every dollar increase had to be justified by the data that came before it. 01 Conversion Architecture Before Spend Before a dollar was spent reaching patients, Webserv built the full conversion tracking system segmented VOB and viable signals, intent-based targeting, and audience exclusions for Medicaid and lower-income regions that would dilute campaign learning. For the first time, every lead, VOB, and viable could be tied back to the exact campaign that produced it. The infrastructure came before the scale. 02 Four Independent Strategies, Not One Each of the four brands Lotus Wellness, Green Acres, Chattanooga Recovery Center, and Graceland Recovery ran as an independent strategy tuned to its own market, competitive set, and audience pool. Lotus and Green Acres ran on Search. CRC and Graceland ran on PMax. Averaging performance across all four would have hidden what was working and diluted what was not. 03 Performance-Gated Budget Scaling No campaign received a budget increase on a timeline only on performance. Each increase required prior-period cost per viable data to justify it. This kept spend efficient and prevented campaigns from scaling before their targeting models were stable. When the admissions team flagged they needed time to get new staff trained, we held budget accordingly rather than scaling into a bottleneck. What We Did ## Execution Across Every Layer Campaign Structure - Launched all four campaigns simultaneously with conservative Day 1 budgets - Built independent Google Search campaigns for Lotus Wellness and Green Acres - Built PMax campaigns for Chattanooga Recovery Center and Graceland Recovery - Added Recover Now Georgia as a fifth campaign in March 2026 - Shifted to conversion value optimization mid-cycle to push toward VOB and viable signals over raw lead volume Targeting and Optimization - Built negative keyword lists pre-launch to protect budget from top-of-funnel research queries - Excluded Spanish-speaking and lower-income regions to protect VOB quality - Removed low-performing Georgia counties spending without conversion data - Restricted Graceland PMax to 98% Search after display drift was detected - Shifted Graceland to dual-diagnosis messaging mid-March measurable improvement in April followed Admissions Alignment - Implemented CTM-first scoring to get conversion signals back to Google faster - Weekly VOB audit cadence to keep CRM data synced with campaign performance - Coordinated budget hold while the admissions team expanded to avoid scaling into a bottleneck - Built NSM projections for each facility using 4.5 months of real funnel conversion data Weekly Performance Management - Reviewed CTM lead scoring weekly to catch unscored viable policies - Monitored search term reports and added negatives in real time - Tracked cost per VOB and cost per viable week over week against projections - Full reporting transparency on outcomes across all four accounts every week The Results ## Nov 2025 to Mar 2026: A System That Got More Efficient Every Month QoQ Growth 226% Increase in OON viable VOBs from Q4 2025 to Q1 2026 39 viables in Q4 grew to 127 in Q1 Lotus Wellness 41.7% Lead-to-VOB rate for the strongest campaign in the portfolio more than double the industry average Chattanooga Recovery 65% Below cost per VOB target exceptional efficiency for a smaller localized market in Q1 #### Campaign Performance - 166 OON viable VOBs and 512 total VOBs delivered across all four campaigns since launch - March alone produced 54 viable VOBs more than the entire Q4 period combined - Lotus Wellness finished Q1 with 73 OON viable VOBs and a 41.7% lead-to-VOB rate - Chattanooga Recovery delivered 21 viable VOBs at a cost per viable well below projections #### Efficiency Trend - Cost per OON viable dropped from $4,447 in November to $2,892 in March as data accumulated - Cost per VOB dropped from $1,840 to $1,132 over the same five-month period - Campaigns outperformed industry averages on cost per lead, cost per VOB, and cost per OON viable by Q1 end - The portfolio is now positioned for its next phase a national Widespread Wellness campaign launch On the Partnership "We appreciate y'all's input, as always. Working with us, being patient with us, and all that good stuff." Jacob Widespread Wellness Group ## Ready to build your admission pipeline from zero? See how the Predictable Patients methodology could work for your facility in a free intro call. [Book a Free Strategy Call](https://webserv.io/intro-meeting/) Why This Worked ## What Made the Difference 01 Conversion Architecture Before Spend By building segmented tracking infrastructure before scaling budgets, campaigns were optimizing to viable insurance holders from day one not raw lead volume. This directly accelerated the algorithm's ability to find high-quality audiences and meant every dollar spent in month one was also building the model for month five. 02 Performance-Gated Budget Scaling Every budget increase required proof from the prior period. This prevented the common mistake of scaling before campaigns are stable, and meant that when budgets did increase, the campaigns were already tuned to handle more spend efficiently. It also meant holding budget when the admissions team needed time protecting ROI rather than chasing volume. 03 Four Independent Strategies, Not One Lotus, Green Acres, CRC, and Graceland each got their own strategy tuned to their market, insurance landscape, and competitive environment. Averaging performance across all four would have hidden what was working and diluted what was not. Campaign-level individuation is what allowed each facility to scale on its own merits. 04 Real-Time Pivots When the Data Spoke When Graceland's PMax started drifting toward display ads, it was caught and corrected within days pushing the campaign back to 98% Search. When dual-diagnosis messaging opened a larger audience pool mid-March, it was implemented immediately and showed measurable improvement in April. The strategy followed the data, not the calendar.