Case study
How We Fixed a Telehealth Company’s PPC Program and Cut CAC by 54%
The Opportunity
Fixing an acquisition model that was generating leads, but not enough economic value
The client, a mid-size, regional telehealth company offering therapy and mental health services across multiple U.S. states, had a growth engine that looked productive on the surface but was underperforming where it mattered most: efficient patient acquisition.
Paid search was driving volume, but the business was paying too much for too little downstream value. True CAC had reached $1,450 per attended first appointment, well above target and increasingly difficult to support as the company pushed for growth. The issue was not demand. It was conversion quality, signal quality, and operating-model misalignment.
The core problem was straightforward. Media was optimized to lead conversion proxies such as form fills and calls, while the business generated revenue only when a qualified patient booked and attended care. In practice, too many paid leads were the wrong fit: outside licensure coverage, misaligned on insurance, lower intent, or operationally difficult to convert. At the same time, campaign architecture had become overly fragmented, which weakened platform learning and reduced spend efficiency.
The company needed to do three things at once: lower CAC, improve lead quality, and create a model that could scale within the realities of regulated healthcare delivery.
The Solution
Rebuilding paid media around the outcomes that mattered to the business
We started by resetting the performance model. Instead of optimizing to lead volume, we shifted the program toward downstream value: insurance-verified consults, attended first appointments, and patient-quality signals tied to actual business outcomes.
That required upgrading the measurement infrastructure. Working with product, engineering, analytics, and intake operations, we improved conversion tracking across GA4, Google Tag Manager, CRM integrations, enhanced conversions, and offline conversion imports. The objective was simple: give platforms better feedback on which clicks actually turned into valuable patients.
To make the media program more precise, we strengthened both audience activation and measurement. Hightouch enabled the team to push more actionable first-party data into media platforms, improving audience segmentation, suppression, re-engagement, and funnel-stage targeting based on real CRM and conversion signals. This reduced wasted spend and allowed campaigns to align more closely with actual patient progression rather than relying only on in-platform proxies.
At the same time, Northbeam provided a more complete view of performance across channels. As investment expanded into upper-funnel media, platform attribution alone was not sufficient to understand true contribution. Northbeam helped the team evaluate blended efficiency, assisted conversion impact, and channel interplay more clearly, which improved budget allocation and made scaling decisions more disciplined.
Once the signal was fixed, we simplified and sharpened the account structure. The existing setup had too many fragmented campaigns, which diluted learning and made optimization harder than it needed to be. We consolidated around a smaller number of commercially meaningful variables: service line, geography, payer fit, and intent. That gave bidding algorithms more data density and allowed budget to flow toward what was actually working.
Search remained the economic core of the program, but we broadened the channel mix where it improved efficiency. Google Search captured high-intent demand. Microsoft Ads added efficient incremental volume. YouTube and Demand Gen helped build consideration and improve branded demand over time. Meta supported upper-funnel education and trust-building using compliant creative and broad audience structures appropriate for healthcare. Each channel had a clear role, but all were managed against the same commercial objective.
We also addressed the post-click experience, because media was absorbing the cost of landing-page inefficiencies. We redesigned landing flows to better align users with the right service, state availability, and insurance pathway. Forms were shortened, trust signals were elevated, and qualification information was surfaced earlier. Using Optimizely, we tested message hierarchy, CTA language, mobile UX, and page speed improvements to reduce friction and improve conversion productivity.
Finally, we introduced a tighter operating cadence around growth and efficiency. Budget allocation was managed not just by channel performance, but by provider capacity, state readiness, and downstream patient conversion rates. Reporting in Looker Studio connected media spend to attended appointments, no-show rates, payer mix, and channel-level economics, which made decision-making faster and more grounded in business value.
The Impact
Lower CAC, stronger patient quality, and a platform for efficient growth
Reduction in CAC, from $1,450 to $665 per attended first appointment
Increase in qualified patient starts, from 143 to 457 per month
Increase in monthly media spend, from $208K to $304K, while staying below $700 CAC target
The results came from improving the full system, not from any single media tactic. Once campaigns were optimized to attended care rather than low-value lead signals, bidding performance improved. Once landing experiences better qualified and routed users, conversion quality increased. Once intake teams received more commercially viable patients, downstream efficiency improved further.
The gains showed up across the funnel. Landing-page conversion rate improved 38%. Insurance-verified consult bookings increased 2.4x. No-show rates declined 21% as the path to care became clearer and qualification improved upstream. Upper-funnel media also contributed to stronger branded search demand, improving blended acquisition efficiency over time.
Most importantly, the client moved from a volume-led acquisition model to a value-led one. The company was no longer paying premium CAC for inconsistent lead quality. It had a more scalable paid media engine, better aligned to how the business actually created value.
Lessons Learned
Strategic Roadmap
Optimize to economic value, not activity
In healthcare, lead volume is often a weak proxy for growth. The real unlock came from aligning optimization to attended care and patient quality rather than top-of-funnel actions that looked efficient but converted poorly downstream.
Operating Model
Better media performance starts with better cross-functional alignment
The biggest gains came from coordination across media, analytics, engineering, compliance, and operations. In regulated categories, paid media performance is rarely just a channel issue. It is an execution issue across the full acquisition system.
More Enrollments
Remove friction before adding spend
The program did not scale because more budget was pushed into market. It scaled because the user journey became more efficient: better routing, clearer qualification, faster pages, and fewer handoff failures. That made every media dollar work harder.
Adoption & Scaling
Scale works when the operating model can absorb it
Growth became more efficient because media decisions were tied to provider capacity, market readiness, and conversion quality at the patient level. In healthcare, sustainable scale comes from matching media investment to operational reality.
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