Pharma Marketing Analytics in a Privacy-First Era: What a Recent Lawsuit Reveals
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Last month, Novartis was sued over allegations that patient data from its breast cancer drug websites was shared with third-party tracking tools.
The lawsuit brought renewed attention to something many pharma teams have been navigating for years: the complexity of using modern marketing infrastructure in a highly regulated healthcare environment.
“The Novartis complaint isn’t an outlier,” says Mason Fitch, special counsel at law firm Kelley Drye & Warren LLP. “It’s the continuation of a years-long regulatory enforcement trend that is only gaining momentum.”
Pixels, cookies, analytics scripts, and ad platforms have long been embedded in branded and unbranded pharma experiences. Meanwhile, regulatory expectations, from HIPAA and FTC enforcement to evolving state privacy laws, have steadily expanded to cover more of the digital patient journey.
According to DigiPharma Insights/Freshpaint’s 2026 DTC and DTP Pharma Benchmark Survey, every pharma marketer of the 100 surveyed reports that privacy constraints are already impacting performance, and 62% of privacy leaders say they lack full visibility into how data flows through analytics and advertising tools.
The same report also highlights a shift: some pharma marketing teams are making progress by rethinking their approach. Instead of layering compliance onto existing systems, they’re addressing the underlying infrastructure — how data is collected, governed, and activated across the patient journey — with systems designed to support both compliance and measurable performance.
This blog post explores how enforcement actions like the Novartis lawsuit are exposing long-standing gaps in pharma marketing infrastructure — and the precise actions that leading organizations are taking to support both compliance and performance.
The Novartis lawsuit highlights how easily patient data can move beyond a pharma company’s control.
At the center of the case is a familiar setup: branded drug websites using commonplace marketing technologies like pixels and third-party analytics tools that aren’t built for pharma contexts.
These tools are designed to track user behavior, optimize campaigns, and improve performance, but in a pharmaceutical context, the interactions they capture — visiting a condition-specific page, checking eligibility for a drug savings program, filling out an interest form for an upcoming clinical trial, or engaging with branded platforms — can become sensitive health information.
When tied to specific conditions or treatments, these interactions can be passed to third-party platforms through embedded tracking technologies, often automatically and with limited visibility into what’s being shared or how it’s used downstream.
At scale, this creates a familiar challenge: data moving across multiple tools and partners without a clear, consistent view of where it’s going or how it’s governed. Regulators are increasingly focused on this exact issue, as enforcement shifts from PHI and covered entities into how consumer health data is inferred, transmitted, and used across digital experiences.
“Advertising in sensitive industries is not impossible, but it requires intentionality,” Fitch explains. “As we see state after state enact more laws governing health data specifically and sensitive data more broadly, the risk will continue to grow.”
For pharma teams, the move isn’t to abandon digital marketing — it’s to recognize that visibility and control over data flows are now foundational, and that marketing teams play a critical role in owning, cataloging, and helping govern those flows.
In many cases, though, a clear understanding of how that data flows from one system to another is still missing.
Across pharma marketing analytics, three key breakdowns show up consistently.
The Novartis lawsuit reflects a broader reality: the challenge lies in how pharma marketing systems operate as a whole, not in a single tool or tactic.
1. Measurement breaks at the moments that matter most
Pharma marketers can track top-of-funnel engagement — impressions, clicks, site visits — but measurement often stops at the handoffs that matter most: telehealth consults, prescription decisions, pharmacy fulfillment, and adherence.
According to the DigiPharma Insights/Freshpaint 2026 benchmark survey, 83% of marketers struggle to connect website activity to prescription fills, and many lose visibility entirely once patients move beyond brand-controlled environments.
Across pharma marketing analytics platforms, this disconnect between data collection and real-world outcomes is increasingly common. Teams are left optimizing toward surface-level insights instead of understanding the tactics that influence starts, fills, and adherence.
2. “Playing it safe” comes at a performance cost.
In response to increasing regulatory pressure, many teams have taken a cautious approach to data collection and activation. Per the 2026 benchmark survey:
- Two-thirds (67%) avoid certain ad platforms altogether
- 63% rely on internal or server-side tagging workarounds
- More than half (54%) depend heavily on anonymized or limited data
While these approaches reduce exposure, they also strip away the signals needed to measure and optimize performance. It’s unsurprising, then, that 59% of pharma marketers say compliance concerns delay or change their initiatives, most often affecting audience targeting (32%), speed to launch (30%), and channel selection (19%).
Over time, this creates a compounding effect: slower campaigns, less precise targeting, and reduced ability to prove ROI.
3. Fragmentation further exacerbates both problems.
Underneath both of these challenges is a more fundamental issue: data fragmentation.
Marketing, analytics, compliance, and data systems are often built and managed separately. Each tool collects data, applies rules, and operates under different levels of oversight. As a result, data is often siloed across systems, governance is inconsistent, and it’s rare that a single team has a complete view of how data flows end-to-end.
No wonder 62% of privacy leaders report only partial visibility into how data moves through analytics and advertising tools. Individually, these issues are manageable. Together, they create a system where teams can’t fully measure performance, can’t confidently manage risk, and can’t clearly tie marketing investment to patient outcomes.
The organizations making progress aren’t solving these problems one by one; they’re addressing the underlying infrastructure that connects them.
How Modern, Compliant Pharma Marketing Analytics Platforms Are Built
The shift often starts with a simple realization: most pharma marketing systems weren’t built for regulated data.
Over time, teams have layered in pixels, analytics tools, tag managers, and ad platform integrations — each solving for a specific need, but without a consistent model for how data should be handled. The result is a system that works for campaign execution, but struggles under the weight of compliance and measurement requirements.
High-performing teams are rethinking that foundation. Instead of managing dozens of independent trackers and downstream fixes, they’re centralizing how data is collected and routed through a single, governed layer.
This creates a point of control at the source, where rules can be applied before data is shared externally. In practice, that means greater consistency across branded sites, patient support programs, and partner handoffs, along with a clearer understanding of what data is moving and why.
This shift also changes how teams approach performance. Leading organizations design systems where privacy-safe data directly powers performance. Sensitive data is filtered or transformed automatically, and only approved signals are passed to downstream platforms. That preserves the feedback loops needed for campaign performance, without introducing unnecessary risk.
As a result, teams are able to move beyond proxy metrics and reconnect marketing activity to bottom-funnel outcomes, like patient starts, prescription fills, and adherence over time.
High-performing teams are also creating shared visibility into data flows and embedding governance directly into their systems. They know which trackers are active, where data is being sent, and how it’s being handled, and formalize data handling standards across their organizations.
Getting to this point starts with a clear understanding of where your current infrastructure creates risk or limits visibility.
Evaluating Your Pharma Marketing Analytics Platform: A Practical Checklist
For most organizations, the gaps are typically known — they’re just not consistently mapped, measured, or governed. The fastest way to make progress is to start with a clear, structured view of how data is actually flowing through your current systems.
“Mitigating risk while enabling marketing can be an intimidating task, but there are relatively simple measures that, when implemented, can materially lower the risk profile in advertising,” Fitch says. “Compliance starts with understanding what tracking technology is on your website and what personal information is being disclosed to whom. From there, it’s an exercise of reducing the amount and quality of information disclosed.”
The checklist below is where many teams begin.
1. Audit what’s running across your branded properties.
Start with a full inventory of tracking technologies across:
- Branded drug sites
- Unbranded condition sites
- Savings and support program flows
- Clinical trial and patient recruitment pages
Document:
- Which pixels, cookies, and scripts are active
- Where they fire
- Which vendors receive data
Even mature organizations are often surprised by what’s still running, especially across legacy pages or third-party-managed properties.
2. Map where interactions may become regulated data.
Using your tracker inventory, map each script or pixel to the user interaction it captures. Identify which of those interactions may qualify as regulated data, including:
- Condition-specific page visits
- Savings card or co-pay enrollment flows
- Dosing tools or symptom checkers
- HCP finders or appointment scheduling
You now have a prioritized view of risk. Focus first on high-sensitivity intersections tied to condition, treatment, or identifiable patient intent – these are the areas that require the most immediate control.
3. Evaluate whether consent controls are actually enforced.
With high-risk interactions identified, assess how consent is handled in those specific flows. Take a closer look at:
- Whether tracking is truly blocked before consent is given
- How consent signals are passed to downstream tools
- Whether enforcement is consistent across all properties
Flag any gaps between user consent and actual data behavior. These gaps indicate where enforcement needs to be strengthened, either through configuration changes or infrastructure updates.
4. Understand your third-party data exposure.
Next, leading organizations shift from measuring what’s collected to understanding where it goes. This is where visibility often breaks down, especially across ad tech and partner ecosystems.
Map:
- Which platforms receive data (analytics, ad platforms, CDPs, etc.)
- What type of data is shared from high-risk interactions
- Whether appropriate agreements (BAAs, DPAs) are in place
Identify which third parties are receiving sensitive or potentially regulated data. These relationships should be reviewed first, both from a contractual standpoint and from a data minimization perspective.
5. Replace fragmented tracking with a controlled data layer
At this point, you’ve identified:
- What’s running
- What data is sensitive
- Where consent may be failing
- Which partners are receiving data
The next step is to address the root cause of how data is handled before it leaves your environment. Leading teams are moving toward:
- A centralized layer that governs data before it’s shared
- Systems that automatically filter or transform sensitive data
- Controlled activation of compliant signals across platforms
Use your findings from the previous steps to define requirements for this layer, including what data needs to be blocked, transformed, or allowed. This becomes the foundation for a scalable, compliant architecture.
6. Establish ongoing governance.
As your marketing tech stack continues to evolve, without ongoing governance, your risk will, too. With that, we recommend you turn your audit into an ongoing system that prevents new issues from being introduced as campaigns, tools, and partners change.
Put in place:
- A review process for new pixels, tags, and interactions
- Clear ownership across marketing, privacy, and compliance teams
- A regular meeting between stakeholders to review the latest regulatory changes
- Continuous monitoring of what’s deployed and how data flows
Teams that approach this systematically are able to move beyond reactive fixes and toward a more stable, scalable foundation for compliant growth.
From there, the advantage becomes clear: better visibility, faster execution, and stronger alignment between performance and privacy.
The Novartis case shows how standard marketing infrastructure, when applied to pharma, can create exposure.
As regulatory expectations evolve and traditional tracking becomes less reliable, life sciences marketing teams need a new foundation for measurement.
Freshpaint brings together privacy and performance in a single platform purpose-built for life sciences. The result is a compliant funnel that restores attribution and the optimization signals you need for growth.
By adopting a compliance-first approach to performance, teams gain:
- Clearer visibility into the marketing actions that drive patient outcomes
- Faster speed to market without compliance-driven delays
- Centralized, consented data with full control over how it’s shared and activated
- Greater confidence across marketing, compliance, and leadership
