Forget Personalization! Localization is the Real Future of Pharma Content

Summary of this session

harma is obsessed with personalization. But in reality, true personalization comes at a high cost: endless content variants, bloated approval processes, and a negative ROI for most brand teams. As David Douek put it, “Pharma doesn’t have chicken in the kitchen”—a playful metaphor pointing out that while we talk about personalized content, we rarely have the content modules or infrastructure to support it.

Meanwhile, localization, a core necessity to make content usable in real markets, continues to be neglected—even though it’s where AI can create the most immediate commercial value.

Key Takeaways

• Personalization causes content explosion
  Adapting messaging across channels, formats, personas, and markets leads to thousands of content variants—most of which will never be used.
  → Personalization without scalable localization = waste.
• Only 9% of global content is reused by local markets
  (Veeva statistic) That means 9 out of 10 assets sit idle—despite the time, effort, and budget behind them.
• Localization isn’t just translation
  It requires adapting to:
  • Local regulations and compliance
  • Cultural tone of voice
  • Preferred content formats
  • Real-world objections and insights from local sales and med teams

What AI Really Brings to Localization

AI helps pharma go beyond speed and cost reduction to deliver:

• Higher quality output that includes local nuances
• Modular content reuse to support segmentation and personalization
• Faster launches even under compressed timelines
• Scalability across formats and touchpoints

Real Examples from the Field

📩 Case Study – Unused Email Journeys (with Ariya)
A global brand manager created high-quality emails for a launch, but no countries used them—until Ariya was used to localize and adapt them in collaboration with Germany.
➡ Result: one email every two weeks, across three brands and two channels = €2M/year savings.

🌐 Case Study – Accelerated Launch
A last-minute launch forced a German team to localize content in just 24 hours.
➡ Using AI (with public content + key messages), they created and approved a compliant localized webpage two days ahead of deadline.

🎥 Case Study – Webinar Summaries (with Ariya)
AI-generated summaries were benchmarked against agency-created ones.
➡ In three blind tests, local brand managers chose the AI version every time—for both speed and clarity.

And yes—we’ve done most of this with Ariya‘s content wizard, our AI platform purpose-built for pharma teams who want to transform content creation and reuse with speed, compliance, and real-world flexibility.

Introducing the PAELLA Framework

To succeed with AI-driven localization, David introduced the PAELLA model:

• Proof: Show results before scaling
• Adoption: Involve key teams early (brand, sales, med, MLR)
• Ease of Entry: Start with simple tools like ChatGPT before scaling
• Launch Small: Pick one market, one channel
• Look Beyond Price: Focus on quality and output impact
• Alignment: Get everyone on the same strategic page

Conclusion: Scale Value, Not Volume

Pharma doesn’t need more content. It needs better systems to reuse, adapt, and deliver what already works—at scale and with precision.

AI-powered localization is faster, cheaper, and more strategic than bloated personalization efforts—and it’s the next must-have capability for any serious omnichannel pharma team.

Want to know more about Ariya’s content wizard and how it can help you with content reuse (modularisation & localisation)? Just contact us!