Digital advertising is a powerful tool—if wielded correctly. For healthcare brands in particular, success depends not just on clever creatives or big budgets but on accurate targeting. A recent audit we conducted for a major U.S.-based healthcare company revealed a textbook example of how flawed interest-based targeting on Meta (Facebook and Instagram) can lead to astronomical costs, low-quality leads, and ultimately, marketing failure.
In this blog, we dissect what went wrong, the structural flaws in Meta’s targeting for healthcare, and how we rebuilt the campaign from the ground up to recover performance. This is not just a case study—it’s a cautionary tale for any healthcare marketer running Meta campaigns in 2025.
The client—a well-established healthcare brand in the U.S.—had been running Meta ads for months with little to show for it. Despite a sizable budget and consistent ad spend, the return on investment (ROI) was negligible. The campaign was generating leads, yes—but they were unqualified, irrelevant, and, more importantly, expensive.
Their internal team suspected issues in copywriting or creative design. However, when we performed a full audit of the campaign structure, one glaring problem emerged:
The entire campaign relied heavily on poorly configured interest-based targeting.
Healthcare is one of the most sensitive industries when it comes to advertising. Unlike eCommerce or entertainment sectors, healthcare deals with:
These complexities make generic advertising tactics ineffective. You cannot treat healthcare like selling a skincare brand.
Despite regulatory complexities, many healthcare companies turn to Meta for advertising because of:
But these advantages come with a caveat: if the targeting is wrong, the entire funnel collapses.
The client suspected poor creative and ad fatigue. They believed that new banners, better CTAs, or video content might improve performance.
But once we accessed their ad manager, we saw a different issue entirely: interest-based targeting was fundamentally flawed.
Interest-based targeting can be powerful for consumer products, lifestyle brands, or entertainment, where people’s digital behavior aligns well with purchasing intent. But for high-consideration, high-compliance sectors like healthcare, it’s not enough.
Here’s why:
3: How Interest-Based Targeting Failed the Campaign
The campaign was targeting interests such as:
These may seem logical at first, but in practice, they are too broad. They pool together:
None of these indicate intent to book a consultation or get a diagnosis.
Example:
A person who liked “WebMD” five years ago for a college project is not a relevant target for a high-cost cardiac consultation today.
Interest-based targeting ignores what people are doing in the present. Meta’s interest pools are built from:
These don’t indicate that someone is currently experiencing symptoms, seeking treatment, or is even in-market.
Meta doesn’t allow you to target based on “recent healthcare need” like Google Ads does through keyword intent. This is where the targeting broke down.
Meta allows targeting by location, but the campaign was set to “United States – All,” ignoring:
In healthcare, hyper-local targeting is mandatory. Someone in Ohio seeing an ad for a New Jersey clinic is wasted spend.
The account did not use exclusions. That means:
… were seeing the ads repeatedly. They weren’t leads—they were spammed users.
Their lookalike audience was built from website traffic—including bounce traffic and blog readers. This polluted the 1% lookalike pool with non-buyers, destroying the efficiency of the reach.
The average CPL was $175–$230 for a healthcare category that should have been around $40–$60. In some ad sets, leads cost over $300.
The leads they did receive were:
Call center follow-ups had a 95% rejection rate.
Ads were being flagged as “irrelevant” and “spammy” by viewers who had no need for healthcare. This hurt their relevance score and ad quality, increasing delivery cost further.
Nearly 65% of their monthly ad spend was being wasted on impressions that had zero chance of converting.
To recover and rebuild a sustainable campaign strategy, we implemented a more strategic audience framework. Here’s how we approached the fix:
We shifted the focus from broad interest groups to Custom Audiences built from:
Instead of relying on Meta’s broad interest data, we built 1% and 2% lookalike audiences from:
This narrowed the audience to people who behaved similarly to real patients.
We layered geo-targeting to reach specific ZIP codes or cities with known demand or where the client had clinics and specialists available. This localized approach eliminated waste from irrelevant regions.
Instead of static interests, we leveraged video views, landing page visits, and event-specific engagement to trigger retargeting ads with relevant messaging (e.g., appointment reminders, insurance support, symptom-specific info).
We split the campaign into awareness, consideration, and conversion stages:
We restructured their funnel into:
This ensured users moved from passive to active stages, reducing friction.
We eliminated all generic interest targeting and instead used:
We geo-fenced campaigns around:
We excluded:
This made ads more relevant and reduced false leads.
We used behavior triggers to fuel retargeting:
This reduced budget burn and improved conversion by targeting warm leads.
We mapped each campaign goal to user intent:
No campaign was left with a “one-size-fits-all” objective like before.
Metric | Before Audit | After Optimization |
Avg. CPL | $185 | $52 |
Qualified Leads | 8% | 61% |
Conversion Rate | 0.7% | 9.2% |
Relevance Score | 4/10 | 8/10 |
Budget Wastage | 65% | <20% |
In just 60 days post-implementation, the brand saw a 300% increase in booked consultations, reduced no-show rates, and a positive ROI for the first time in over a year.
Healthcare decisions are not impulse purchases. Interest data does not reflect urgency or medical necessity.
Meta restricts detailed targeting on medical conditions, which means brands can’t use precise interest labels like:
This forces marketers to guess, which is unreliable.
You can’t serve everyone. Interest-based targeting does not allow for real-world limitations like service zones, insurance coverage, or hospital affiliations.
iOS14 and GDPR have reduced Meta’s ability to track user behavior accurately. Interests are now less accurate and more outdated than ever before.
Base lookalikes only on:
Don’t use “all web traffic” or “blog readers” as sources.
If you still want to test interests, combine them with layered filters like:
And always A/B test with a control group.
Track metrics like:
These provide better insight than just CPL.
Final Thoughts: Don’t Let Meta’s Tools Mislead Your Strategy
Meta Ads are incredibly powerful—but only if used with a deep understanding of your audience’s journey, intent, and constraints. For healthcare brands, the stakes are high. Using outdated, overly broad interest categories can wreck even the most creative campaigns.
The healthcare client we audited learned this the hard way. But with the right targeting, funnel design, and first-party data integration, their campaign turned around—and yours can too.
In digital advertising, especially on platforms like Meta, wrong targeting is worse than no targeting. For this healthcare brand, relying solely on interest-based targeting led to false leads, bloated costs, and campaign failure. After fixing the audience strategy, we saw a dramatic improvement in CPL, lead quality, and conversion rates—proving that relevant, data-driven targeting is non-negotiable in healthcare marketing.
If you’re running Meta ads and aren’t seeing the results you expect, it might be time to audit your targeting strategy. Just like this healthcare brand, your next big performance breakthrough might come from understanding whom you’re speaking to—and why.
Need Help Auditing Your Meta Campaign?
If you’re a healthcare brand struggling with Meta Ads, don’t guess. Let our team audit your campaigns and help restructure your strategy for real results. Contact us today to get started.
Akshat’s passion for marketing and dedication to helping others has been the driving force behind AkshatSinghBisht.com. Known for his insightful perspectives, practical advice, and unwavering commitment to his audience, Akshat is a trusted voice in the marketing community.
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