Digital Experience Design & Strategy
Designing a global UX framework that scales across markets, respecting cultural, regulatory, and health literacy differences while maintaining experience design consistency.

The stigma-reduction sequence in its designed form, inside the global/flex framework. Click to see the full pages. The tabs below show how it deployed across four markets without a rebuild.
The brief centered a named persona, Andrea: frustrated, stuck in a cycle of failed attempts, carrying stigma and worried about her health. Her emotional profile was the design constraint, and everything from the homepage sequence to the quiz prompts was calibrated to resolve her barriers before any clinical ask.
A global platform request concealed two distinct structural problems that needed to be solved sequentially.
"Design a global obesity platform that can be adapted for each market — KSA, UAE, Germany, Japan — while maintaining brand and regulatory consistency."
The brief frames this as adaptation. It is actually two problems. First, nobody had separated the elements that are non-negotiable globally from the genuine flex zones. Second, obesity is one of the most stigma-loaded conditions, so a patient with years of failed attempts and self-blame has to be met emotionally before any clinical ask. The challenge was global architecture plus stigma-aware sequencing, not localizing a standard pharma template.
The reframe produced the global/flex zone architecture and the stigma-reduction sequencing that opens the homepage.
Global wellness platforms & stigma-adjacent health conditions. Global constants with local flex zones suit any platform scaling across markets where a condition carries stigma. The stigma-reduction sequencing carries over to weight management, mental health, addiction support and other conditions where self-blame blocks engagement.
Neither Novo Nordisk property addressed all five content pillars — and their approaches were mutually exclusive. ItsBiggerThan.com (emotional, community) missed biological causation and the HCP pathway. TruthAboutWeight.global (scientific) was weak on emotional validation and HCP conversion. Wegovy.com had an 84% bounce rate despite 970K monthly visits. Stigma was universal but showed up differently: social shame in Japan, religious self-judgment in KSA and UAE, personal-discipline failure in Germany.
I treated this as a global architecture problem with local sensitivity built in: non-negotiable IA and UX principles locked centrally, explicit flex zones for regional adaptation. AI-assisted research surfaced patterns and content gaps across all four markets. The five-screen Quiz Module, which generates a personalized discussion guide, was the most complex flex zone.
The site map sets the page hierarchy and content groupings that had to stay consistent across all markets. The homepage opens with four stigma-reduction modules before routing patients into four pathways.
It fixed which elements were non-negotiable globally, giving regional teams a clear brief instead of an open one and reducing late-stage drift.
Four homepage modules form the global constant zone, sequenced to resolve shame, attribution, stakes and agency before any clinical content. Select a module to expand.
Creates an opening without assigning blame. The patient must feel addressed, not judged, before any information has value.
The emotional barrier it resolves — shame-avoidance — is culturally invariant. Localising this module risks softening the activation signal.
Patient has accepted the premise that change is possible. Attribution of cause is still unresolved — must be addressed next.
Sequence constraint: modules appear in this order in every market build, because reordering collapses the behavioral arc. Flex zones begin at section two of the site IA.
Five-section readiness ladder. Each section has a gate condition that must be met before the next has behavioral value. Select a section to expand.
Homepage — emotional foundation
Permission to engage at all. Shame and self-blame are resolved before any clinical information.
Four stigma-reduction modules in fixed sequence, a soft CTA, and no clinical content until the arc completes.
Understanding obesity — condition education
Acceptance of the medical framing, so treatment options carry credibility.
Core: biology, comorbidities, systemic impact. Flex: comorbidity emphasis by market.
Weight management options — treatment landscape
Treatment seen as a legitimate, multi-modal space, with HCP guidance as context, not gatekeeping.
Core: treatment categories and the role of medical management. Heavy flex: options, regulatory references and reimbursement.
Weight loss journeys — social proof layer
Confidence that people like them have navigated this, lowering the barrier to an HCP conversation.
High flex. Stories reflect market demographics and local emotional barriers; voice and tone may flex.
Talk to your doctor — action conversion
Concrete action: the CTA is now a low-friction next step, not a leap.
Core: HCP conversation framing and preparation tools. Flex: HCP-finding tools, entry points and CTA phrasing by market access model.
Mobile wireframes R10: a six-artboard, mid-fidelity spread of the five-section patient journey at 375px, including the Quiz Module. Its nine questions carry embedded learning prompts. Selecting an answer such as “I continued to be hungry” reframes it as biological resistance mid-flow, and the result downloads as a PDF discussion guide for HCP conversations. Copy is lorem placeholder; the deliverable is the structure, interaction design and sequencing. Pre-MLR working copy.
Seven validated mobile layouts gave regional teams reference implementations to adapt, not blank canvases — cutting per-market design time without sacrificing local precision.
The architecture scaled well across four markets. Local teams still needed a clearer signal, such as a governance decision tree telling them whether they were in a flex zone or a global constant, rather than catching drift in late-stage review. I’d also point the AI research layer at regional patient-voice content earlier. We used it mainly for competitive pattern analysis, and applying it to cultural sensitivity would have sharpened the flex zones.