Prada — First global eCommerce (multi-market localisation)
Focus: global commerce foundation + localisation framework + brand craft at scale
Designed Prada’s first global eCommerce experience, creating a scalable commerce model and a localisation approach for market-specific needs (Japan, China, Gulf States, Russia) without fragmenting patterns, quality and brand expression.
- Problem
- Launch an end-to-end commerce experience for a global luxury brand, balancing premium craft with operational reality.
- Enable multiple markets with different customer expectations and local requirements while keeping the experience coherent and recognisably ‘Prada’.
- Constraints
- Localisation complexity: languages, content, merchandising rules and market-specific patterns.
- Regional differences across payments, shipping, returns, duties/taxes and service expectations.
- Luxury brand bar: typography, layout rhythm, imagery hierarchy and editorial tone must stay consistent and premium.
- Performance and reliability expectations for high-traffic moments and global access.
- Contribution
- Defined the end-to-end commerce journey model (browse → PDP → cart → checkout → post-purchase support patterns).
- Built a localisation framework: what stays consistent (common core) vs what adapts per market (explicit local layers).
- Designed high-stakes commerce patterns: stock states, shipping options, error/recovery, and trust cues.
- Aligned brand, product and technical stakeholders through prototypes, system rules and delivery-ready specifications.
- Artefacts
- Localisation matrix (common core vs market-specific variations).
- Commerce pattern set: PDP states, cart/checkout steps, validation, errors and recovery.
- Content hierarchy guidelines for luxury merchandising and editorial consistency.
- Outcomes
- Delivered Prada’s first scalable global commerce experience with a clear localisation model enabling multi-market rollout.
- Created reusable patterns that prevented market-by-market drift and protected premium quality across channels.
- Improved delivery alignment by making market differences explicit and designed, not discovered late in implementation.
- Reflections
- In luxury, trust is a design output: clarity of delivery/returns and predictable states matter as much as aesthetics.
- Localisation is not translation — it’s product strategy and system design.
Ferragamo — Clientelling experience (store ↔ customer relationship)
Focus: omnichannel relationship UX + privacy/consent + tooling that sales teams actually adopt
Designed a clientelling experience to support personalised, high-touch luxury retail relationships—connecting store teams to customer context and actions while respecting privacy/consent expectations and operational realities.
- Problem
- Enable store teams to build stronger customer relationships with better context, follow-ups and service continuity across channels.
- Reduce fragmentation between in-store interactions, customer history, and next-best actions.
- Constraints
- Privacy and consent expectations for customer data use and outreach (trust-sensitive domain).
- Usability in the store context: time pressure, interruptions, and varying digital confidence among staff.
- Integration constraints with CRM, stock/catalogue and operational processes.
- Need for clarity and traceability in customer interactions and notes.
- Contribution
- Mapped clientelling workflows (before/after appointment, outreach, follow-up) and designed role-based views.
- Defined trust patterns: consent visibility, data minimisation cues, and safe defaults for customer engagement actions.
- Designed interaction patterns that balance speed (quick actions) with depth (drill-down, notes, history).
- Aligned stakeholders through prototypes and clear requirements for integration touchpoints.
- Artefacts
- Workflow map + role/permissions matrix.
- Prototype slices: customer overview, outreach actions, appointment flow, follow-up tasks, notes/history.
- Consent/controls patterns and exception states (missing data, opt-outs, errors).
- Outcomes
- Delivered a clientelling interaction model designed for real store usage (fast, interruptible, and role-aware).
- Improved clarity and trust around customer data usage through explicit consent/controls patterns.
- Created a shared blueprint for CRM and operational integration points, supporting more consistent omnichannel service.
- Reflections
- In clientelling, adoption is the KPI: the best design is the one that fits the store’s pace and constraints.
- Privacy is not just compliance; it’s part of the luxury relationship and brand trust.
Brunello Cucinelli — Checkout experience fine-tuning
Focus: friction reduction in conversion-critical flows + clarity in forms/states + premium trust cues
Fine-tuned the checkout experience to reduce friction and ambiguity in the most conversion-sensitive journey—improving clarity of forms, validation, errors and confirmations while maintaining a premium brand tone.
- Problem
- Checkout is where uncertainty converts into drop-off: unclear forms, errors and what happens next moments damage trust.
- Luxury customers expect calm, predictable flows—especially around payment, delivery and returns.
- Constraints
- Payment/security steps (e.g., verification states) requiring clear handoffs and recovery.
- Shipping/returns constraints and edge cases that must be communicated without clutter.
- Maintain premium typography rhythm and layout clarity under dense form requirements.
- Accessibility-aware readability and error messaging in form-heavy screens.
- Contribution
- Reviewed checkout flow as a state machine (valid/invalid, pending, failed, retry, confirmation) and redesigned critical states.
- Improved form hierarchy, validation timing and error messages to reduce ambiguity and support recovery.
- Refined confirmation and next step messaging to increase predictability and trust.
- Aligned improvements with brand expression so usability upgrades didn’t compromise the luxury feel.
- Artefacts
- Checkout state model + edge cases and recovery paths.
- Updated form patterns: hierarchy, validation and error messaging guidelines.
- Prototype slices for the most failure-prone steps (payment, address, delivery options).
- Outcomes
- Delivered clearer, more predictable checkout patterns focused on reducing ambiguity in high-risk moments.
- Improved recoverability through explicit error states and retry paths, protecting trust when things go wrong.
- Created reusable checkout guidance that can be applied consistently as payment/shipping rules evolve.
- Reflections
- Checkout excellence is mostly state design: predictability beats novelty when money is involved.
- Luxury UX is calm UX — rhythm, clarity and trust cues are part of brand value.