Lately, pharma talks are a lot about 1:1 personalization. Aside of this being a distant dream, it often overshadows a more urgent problem: localization. While teams struggle to create ultra-personalized journeys, they’re still battling slow, expensive, and inefficient localization processes that delay launches and limit engagement. But are we even focusing on the right challenge? Should pharma be aiming for full personalization and refining segmentation, or is broad-scale content still the reality in many markets? This session explores how AI can help strike the right balance between personalization, localization, and content modularization -ensuring efficiency, scalability, and relevance without overwhelming teams or budgets. Learn how AI-powered localization can cut timelines, reduce costs, and ensure omnichannel content is actually relevant to HCPs globally.
Bullet Points:
- Personalization vs. Segmentation vs. One-Size-Fits-All. What actually works?
- The omnichannel dilemma: More channels, more formats, more complexity
- AI-driven localization: Where does the opportunity lie?
- Case studies: What’s working (and what’s not). Real examples of AI-driven localization in action: successes, challenges, and key takeaways.
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