Most healthcare dashboards celebrate form fills, MQLs, and last-click conversions — none of which fill the operatory. We measure against confirmed bookings in your EMR or PMS through a patented multi-touch attribution model, so you finally see which channels actually bring patients in.
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Analytics & Attribution
Healthcare marketing analytics should answer one question: which channels actually produce booked patients. We build multi-touch attribution that follows the real care journey, from first impression through call, form, and confirmed appointment, so spend maps to outcomes instead of clicks or impressions. As a healthcare-only marketing attribution agency since 2005, we engineer measurement to be HIPAA-aware and 42 CFR Part 2 fluent, keeping protected and substance-use information out of ad platforms and analytics tools where it does not belong. That means consent-aware tracking, server-side controls, and reporting that ties dollars to demand without exposing patient identity. Senior operators design the model, validate the data, and read it with you, so attribution reflects how patients truly find and choose care. The result is clear credit across paid, organic, and referral touches, a defensible view of cost per booked patient, and decisions grounded in revenue rather than platform-reported metrics that overstate their own influence.
Headquartered in Eagle, Idaho, serving Boise and the Treasure Valley and healthcare organizations across the United States.
What is healthcare marketing attribution, and why does it need to be HIPAA-aware?
Marketing attribution assigns credit across the touches that lead to a booked patient. In healthcare it must be HIPAA-aware and, for substance-use care, 42 CFR Part 2 fluent, so protected information never flows into ad platforms or analytics tools. We use consent-aware, server-side measurement that ties spend to outcomes while keeping patient identity out of channels that should never hold it.
How does multi-touch attribution work for a patient journey?
Patients rarely convert on a single click. Multi-touch attribution tracks the full path — search, ads, referrals, and direct visits — then assigns proportional credit to each touch through the call or appointment. This shows which channels truly drive booked patients and a defensible cost per booking, rather than crediting only the last click.
Will analytics expose patient information?
No. We design measurement so protected health information and 42 CFR Part 2 data stay out of ad platforms and third-party analytics. Tracking is consent-aware and server-side where appropriate, so you get accurate, revenue-linked reporting without compromising patient privacy.
Every channel measured against confirmed bookings in your EMR — not form fills. One patented multi-touch model, working live.
HIPAA-aware AI, deployed inside the systems that actually produce revenue.
Branded, last-click search hogs credit for work it never did — the awareness impressions, organic content, KOL posts, and referrals that actually moved the patient. So awareness channels get defunded, the assists disappear, and the funnel collapses within a quarter.
We pipe the confirmed-booking signal back into the attribution graph, so every channel is measured against real scheduled appointments — not the last ad someone happened to click. It is the core of our patient acquisition systems practice.
GA4 will show you assisted conversions, but it defaults to last-click for revenue. Healthcare then adds data-sharing constraints the platform was never built for: form submits are HIPAA-sensitive, calls route through call-tracking, and bookings live in an EMR behind a firewall.
So an off-the-shelf dashboard never sees the booking event — and what it cannot see, it cannot attribute. Our stack closes that loop through HIPAA-compliant, server-side integrations, without ever exposing PHI to ad platforms.
From collection to activation, every layer is engineered to keep the confirmed booking as the ground truth.
Server-side, HIPAA-aware tagging; pixels replaced where regulation demands; no PHI to ad networks. Data flows are audited against minimum-necessary before launch.
EMR / PMS / scheduler connected back to the graph as the ground-truth booking event through secure middleware, encrypted in transit and at rest.
The founder-patented multi-touch attribution engine (US 12,091,041 B2) weighs every touchpoint so awareness, organic, and KOL all get credit — and branded search stops hogging the last click.
Dashboards tuned to the decisions ops, the CMO, and the board actually make: patient LTV by source, channel efficiency vs. booking volume, attribution-drift alerts — plus weekly commentary from a senior strategist, not an automated PDF.
Distribution budget rebalanced weekly on real booking performance — not platform dashboards.
Four signals that map directly to revenue — not vanity metrics.
Confirmed bookings pulled from your EMR/PMS via HIPAA-compliant integrations — the only conversion event that pays the lease.
Segment lifetime value by acquisition source so you stop optimizing for cheap leads that never return for the treatment plan.
Which touchpoints assist bookings and which cannibalize credit across paid, organic, social, video, and KOL — not the last-click illusion.
Models decay; privacy changes and OS updates break pixels. We flag when attribution drifts from ground-truth bookings before budget goes sideways.
Senior-only delivery from 10+ year healthcare operators — no offshore content factory — plus a client's nine-figure telemedicine exit in our track record. See the healthcare case studies and the broader AI capabilities behind the model.
"Insight without action is a PDF. We measure against booked appointments, then rebalance the budget on what actually produces patients."
Yes. We use server-side tagging, HIPAA-compliant middleware, and minimum-necessary data flows, and no PHI is ever sent to ad platforms. We are BAA-ready and audit the data pipeline against the HIPAA Security Rule before launch, with 42 CFR Part 2 sensitivity for behavioral-health data.
Either. For larger systems we work alongside internal analytics, BI, and data-science teams, complementing them with the attribution modeling and healthcare-specific integrations they typically lack. For practices without an internal team we run the whole stack and deliver dashboards and commentary directly to leadership.
If your scheduling system exposes an API or an HL7/FHIR endpoint, we can pipe the confirmed-booking signal into the attribution graph as the ground-truth conversion event.
CRM dashboards show pipeline inside the CRM, which is only what the sales team touches. Our model reads paid, organic, social, and offline channels as one graph and reconciles CRM pipeline against the full funnel.
Yes. Our standard intake includes a discovery audit of current tagging, pixels, CRM setup, and reporting. You receive a written assessment with findings and priorities regardless of whether you continue with 210.
Measure against booked appointments and rebalance budget on what produces patients.
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