Using AI for dementia diagnostics is a massive opportunity, so we ran a campaign to get a new tool in front of doctors. This teardown breaks down our push to drive awareness and early sign-ups, built on marketing the client’s own AI research. Our goal was simple: get healthcare providers to see this tool as the top choice for its accuracy and speed, in the end cutting down the long, painful diagnostic journey for patients. The question was, could a data-driven marketing plan actually get busy, skeptical doctors to change how they work?
Key Takeaways
- Targeted LinkedIn InMail sequences hit a 22% conversion rate for demo sign-ups with neurologists and geriatricians.
- Our $750,000 budget over six months delivered a $125 cost per lead (CPL) for qualified HCP prospects.
- Creative with patient stories and clinical data got a 3.5% higher click-through rate (CTR) than creative that just talked about tech features.
- Our initial focus on large hospitals blew up the cost per conversion by 15% in the first two months.
- Shifting 40% of the budget to smaller, independent clinics cut the cost per conversion by 20% later in the campaign.
Our firm was brought on to build and run the entire marketing strategy for a new AI platform for early dementia detection. This meant we were trying to trigger a real shift in how doctors diagnose these conditions, not just move a product. The main hurdle was convincing a skeptical and overworked audience of specialists about AI’s real-world benefits in a field where trust is everything. Our messaging had to boil down to three things: precision, efficiency, and real impact on patients’ lives.
Campaign Strategy: Building Trust Through Evidence
Our whole strategy was built on earning trust. For doctors, that means data, so we led with hard evidence and peer-reviewed AI research to prove the tool’s effectiveness. HCPs live and die by evidence-based medicine, so there was no other way in. We combined digital ads with deep-dive content, aiming squarely at neurologists, geriatricians, and memory care clinics in major hubs like Atlanta, Boston, and San Francisco. The hook was always that early detection changes everything for treatment and patient outcomes, which is the exact conversation these specialists are already having.
Our content strategy hit the main pain points of dementia diagnosis head-on: the endless waiting, the subjective nature of old methods, and the stress on families. Every single asset, whether it was a dense whitepaper or a quick video ad, showed exactly how the AI tool solved one of those problems. We kept hammering on the clinical validation of the AI to back up every claim we made. This wasn’t just a hunch. A recent IAB report showed that evidence-based marketing can bump HCP engagement by up to 30%, and we took that finding as our guide for all content creation.
Creative Approach: Humanizing AI with Clinical Precision
For creative, our job was to make the AI feel human and clinically relevant. We dropped the tech jargon and just showed the tool working, what the UI looks like and how clear the results are. Our main assets were animated explainers on how the AI worked, case studies of actual early diagnoses, and video testimonials from doctors already using the platform. One split-screen ad was a huge winner: on the left, you saw the slow, frustrating, multi-appointment slog of a traditional diagnosis, while the right showed the clean, fast, AI-driven process. That side-by-side comparison did more to sell the tool than any block of text ever could.
We got a huge lift from a series of unscripted interviews with a neurologist who was an early adopter. We just let them talk about their actual experience using the tool and how it changed their patient management. No scripts, no corporate talking points. We pushed these videos out on LinkedIn and into closed medical forums where peer opinion is king. The data backed this up completely: creative that used a direct physician testimonial got a 3.5% higher click-through rate (CTR) than our ads that just focused on the product’s features. Doctors trust other doctors, simple as that.
Targeting and Channel Selection: Reaching the Right Specialists
Our targeting had to be surgical. We leaned heavily on LinkedIn’s professional data to build audiences of neurologists, geriatricians, and even internal medicine docs with certain certifications. It wasn’t just job titles. We layered on targeting for members of specific medical associations and readers of niche journals. Going broad would have just lit money on fire with useless impressions. This precision was the only way to make the budget work. To supplement this, we ran programmatic display ads on sites like Medscape and used IP targeting to hit specific hospitals and clinics.
The channel mix was straightforward: LinkedIn InMail and sponsored posts were our workhorses, supported by Google Search ads for people actively looking for keywords like “AI dementia diagnosis” or “early Alzheimer’s detection tools.” We also used display ads on HCP-specific platforms like Medscape and Doximity. Most of the budget went to LinkedIn because you just can’t beat its targeting for reaching doctors in a professional context. Our LinkedIn InMail sequences are a perfect example, we sent a personal note with a link to a whitepaper and got a 45% open rate and an 18% response rate, which is frankly unheard of for cold outreach in this field.
Budget, Duration, and Metrics: A Six-Month Deep Dive
We ran this campaign for six months (Jan-June 2026) on a $750,000 budget that covered everything from creative to media buys. Our main KPIs were pretty standard: qualified demo requests, traffic from our target HCPs, content engagement, and in the end, trial sign-ups.
Here’s where the numbers landed:
- Total Impressions: 12 million
- Overall CTR: 1.8%
- Total Leads (Demo Requests): 6,000
- Qualified Leads: 3,000
- Conversion Rate (Qualified Leads to Demo Sign-ups): 22% (among neurologists and geriatricians)
- Cost Per Lead (CPL): $125 (for qualified healthcare provider prospects)
- Cost Per Conversion (Trial/Subscription): $1,136
- Return on Ad Spend (ROAS): 1.8x (calculated based on initial subscription values)
That 22% conversion rate for demo sign-ups among neurologists and geriatricians is the number that really matters, because it shows they were genuinely curious enough to take the next step. A ROAS of 1.8x is decent out of the gate, but it also tells us we have work to do on efficiency as we try to land bigger, longer-term contracts.
What Worked: Precision Targeting and Educational Content
Without a doubt, the hyper-specific targeting on LinkedIn made this campaign work. Getting relevant content in front of the right doctors meant we weren’t wasting money and were actually getting their attention. The educational approach paid off, especially the whitepapers that walked through the clinical validation data. Content that tackled specific, tricky diagnostic problems (like telling different dementias apart) did the best. Having solid AI research to point to was our constant ace in the hole.
Physician testimonials were worth their weight in gold. Having a fellow doctor vouch for the tool gave us a level of credibility that our own marketing copy never could, confirming our belief that doctors listen to other doctors when it comes to adopting new tech. Our retargeting flow was also effective: once a doctor engaged with our top-of-funnel content, we’d start serving them detailed case studies. This kept the conversation going and made sure we were giving them progressively deeper information as they moved toward a decision.
What Didn’t Work: Initial Over-Reliance on Large Institutions
Our first big mistake was putting too many eggs in the large hospital basket. We assumed big institutions would have the money and structure to adopt the tool quickly, but that was wrong. They were interested, sure, but their purchasing process is a nightmare of red tape. This mistake cost us, leading directly to a 15% higher cost per conversion in the first two months of the campaign and dragging down our initial ROAS.
We also got the creative wrong at the start. Our first batch of ads was way too technical, going on about algorithms and machine learning. It probably impressed some data scientists, but it turned off the busy clinicians who just wanted to know how it would help their patients. The feedback from the field was loud and clear: talk about patient outcomes, not the code.
Optimization Steps: Shifting Focus and Refining Messaging
When we saw how slowly the large hospitals were moving, we made a fast pivot. We pulled 40% of our media budget out of that segment and pushed it toward independent neurology clinics and smaller private practices, especially in the suburbs around Atlanta, Boston, and San Francisco. These smaller practices could make decisions in days, not months, and were eager to try anything that gave them an edge in patient care. The move worked almost overnight, dropping our cost per conversion by 20% for the rest of the campaign.
At the same time, we overhauled our messaging to focus on patients and outcomes. We killed headlines like “Advanced AI Algorithms for Dementia Detection” and replaced them with direct, benefit-driven ones like “Faster, More Accurate Dementia Diagnosis for Your Patients.” It sounds like a small change, but it had a huge impact on engagement. We were A/B testing everything, and this iterative process gave us great insights. For example, we found that the CTA “Request a Clinical Overview” beat “Schedule a Demo” by 10% on clicks, telling us that doctors wanted more education before they’d commit to a sales call.
This campaign was a good reminder that even when you’re marketing a sophisticated AI tool, the fundamentals still apply. Success in healthcare marketing comes down to knowing your audience’s needs inside and out and then proving your value with clear, hard evidence. Relying on continuous optimization based on live data isn’t just an option. It’s the only way to navigate the messy, complex world of selling to doctors.
What was the main point of this whole campaign?
The main goal was to introduce a new AI diagnostic tool for dementia to doctors. We wanted to position it as the best option because of its speed and accuracy, with the ultimate aim of shortening how long it takes for patients to get a diagnosis.
How much did this cost and how long did it run?
The total budget was $750,000. It ran for six months, from January to June 2026, and that price tag included everything from making the ads to the media spend and analytics.
What was the best way to actually reach these doctors?
LinkedIn was the clear winner. Its targeting options let us get personalized, data-heavy content like sponsored posts and InMail directly to the right neurologists and geriatricians.
What was the biggest screw-up and how did you fix it?
Our biggest mistake was focusing too much on big hospitals at first. Their buying process was incredibly slow and expensive. We fixed it by shifting 40% of our ad spend over to smaller, independent neurology clinics that could make decisions much faster.
Which ads actually worked the best?
The ads that showed patient stories and hard clinical data got a 3.5% higher click-through rate. The most effective thing we did was run unscripted interviews with doctors who were already using the tool, that peer-to-peer credibility was huge.
