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La Mer Virtual Skin Analysis
La Mer Virtual Skin Analysis
Personalized, ML-assisted skincare consultation that standardizes recommendations and boosts attachment rate/AOV in prestige retail.
Personalized, ML-assisted skincare consultation that standardizes recommendations and boosts attachment rate/AOV in prestige retail.
+15%
Average order value
-30%
Time to recommendation
+31%
Attachment rate.
+15%
Average order value
-30%
Time to recommendation
+31%
Attachment rate
At a glance.
At a glance.
My Role — Senior Product Designer (end-to-end: research synthesis, IA, flows, interaction patterns, content/governance, pilot planning, tokenized design system)
Team — Retail Ops, iOS Engineering, Data/ML, Brand, Research
Duration — Multi-release program, 2019–2022
Key Outcomee:
+15% AOV from clearer bundled routines.
-18% Time to plan
-30% time to recommendation
+31% attachment
+41% Save/Share opt-in
Contribute to the solution being adopted by more than 7 other ELC brands (Tom Ford, Bobbi Brown, Clinique, etc).
My Role — Senior Product Designer (end-to-end: research synthesis, IA, flows, interaction patterns, content/governance, pilot planning, tokenized design system)
Team — Retail Ops, iOS Engineering, Data/ML, Brand, Research
Duration — Multi-release program, 2019–2022
Key Outcomee:
+15% AOV from clearer bundled routines.
-18% Time to plan
-30% time to recommendation
+31% attachment
+41% Save/Share opt-in
Contribute to the solution being adopted by more than 7 other ELC brands (Tom Ford, Bobbi Brown, Clinique, etc).
The Strategic Challenge: Why This Mattered
The Strategic Challenge: Why This Mattered
The Business Context
La Mer and the broader ELC org set a strategic goal to raise the quality and consistency of in-store consultations while respecting strict time boxes at the counter—grow attachment through trust and clarity, not pressure. This translates to healthier baskets now and better long-term retention as clients actually follow routines at home. (Structuring your case around story beats → context → outcome improves comprehension for reviewers.
The Problem
Consultations varied widely. Associates relied on personal heuristics; the rationale often lived in their heads, not in the interface. The result: time slippage (consults clustering at ~8–12 minutes), inconsistent explanations, and attachment that depended on who was on shift rather than what the client needed. Baseline from pilot stores: time to plan ~9m20s, attachment ~44%, and clients frequently leaving without a portable plan.
My Role & Responsibilities
I owned the end-to-end redesign: shaped the IA, designed flows & interaction patterns, defined the “Why this” explainability model, and built the content/governance system Brand & Clinical can operate safely. I partnered with Research (fieldwork & synthesis), iOS (performance at the counter), and Data/ML (auditable, human explanations).
The Business Context
La Mer and the broader ELC org set a strategic goal to raise the quality and consistency of in-store consultations while respecting strict time boxes at the counter—grow attachment through trust and clarity, not pressure. This translates to healthier baskets now and better long-term retention as clients actually follow routines at home. (Structuring your case around story beats → context → outcome improves comprehension for reviewers.
The Problem
Consultations varied widely. Associates relied on personal heuristics; the rationale often lived in their heads, not in the interface. The result: time slippage (consults clustering at ~8–12 minutes), inconsistent explanations, and attachment that depended on who was on shift rather than what the client needed. Baseline from pilot stores: time to plan ~9m20s, attachment ~44%, and clients frequently leaving without a portable plan.
My Role & Responsibilities
I owned the end-to-end redesign: shaped the IA, designed flows & interaction patterns, defined the “Why this” explainability model, and built the content/governance system Brand & Clinical can operate safely. I partnered with Research (fieldwork & synthesis), iOS (performance at the counter), and Data/ML (auditable, human explanations).
The Journey: From Ambiguity to Clarity
The Journey: From Ambiguity to Clarity
The Approach
We returned to the counter: shadowed high-throughput stores, interviewed associates & clients, and captured the true rhythm of the conversation. We converted findings into a journey model and decision taxonomy mapping where confidence dropped and hesitation crept in. In parallel, I audited legacy screens to remove jargon and detours.
Key Insight / Turning Point
Three insights reframed the work: Explainability → trust (a single, short rationale boosts commitment); time boxes are real (~60s without progress feels long); attachment happens when the plan appears (AM/PM with roles reduces cognitive load; add-ons feel like upgrades, not surprises). These became the backbone: concern-first, a self-explanatory plan, and explainability under every product.
Collaboration in Action
I ran workshops with PM, Retail Ops, Engineering, and Brand, walking the ideal journey backwards—from a client holding a saved routine to the first counter question. Engineering flagged flaky networks; we pivoted to local-first interactions with graceful sync so momentum survives connectivity dips. We aligned on the final sequence and a copy system Brand could extend.
The Approach
We returned to the counter: shadowed high-throughput stores, interviewed associates & clients, and captured the true rhythm of the conversation. We converted findings into a journey model and decision taxonomy mapping where confidence dropped and hesitation crept in. In parallel, I audited legacy screens to remove jargon and detours.
Key Insight / Turning Point
Three insights reframed the work: Explainability → trust (a single, short rationale boosts commitment); time boxes are real (~60s without progress feels long); attachment happens when the plan appears (AM/PM with roles reduces cognitive load; add-ons feel like upgrades, not surprises). These became the backbone: concern-first, a self-explanatory plan, and explainability under every product.
Collaboration in Action
I ran workshops with PM, Retail Ops, Engineering, and Brand, walking the ideal journey backwards—from a client holding a saved routine to the first counter question. Engineering flagged flaky networks; we pivoted to local-first interactions with graceful sync so momentum survives connectivity dips. We aligned on the final sequence and a copy system Brand could extend.
The Solution: A Deliberate and Crafted Experience
The Solution: A Deliberate and Crafted Experience
Introducing the Design
The consultation that moves at retail pace and explains itself. The flow is intentionally simple: Greet → Diagnose → Plan → Share → Checkout. Simplicity is the arrangement of detail, not the absence of it.
Principle 1 — Concern-First Diagnosis (Clarity from the Start)
We pulled diagnosis to the beginning. A lightweight concern picker (and when available, a quick surface scan) captures intent in seconds. With a reliable signal, the plan is a response, not a guess—reducing back-and-forth and unlocking specific explanations.
Introducing the Design
The consultation that moves at retail pace and explains itself. The flow is intentionally simple: Greet → Diagnose → Plan → Share → Checkout. Simplicity is the arrangement of detail, not the absence of it.
Principle 1 — Concern-First Diagnosis (Clarity from the Start)
We pulled diagnosis to the beginning. A lightweight concern picker (and when available, a quick surface scan) captures intent in seconds. With a reliable signal, the plan is a response, not a guess—reducing back-and-forth and unlocking specific explanations.
Principle 2 — AM/PM Plan that Reads Itself
The routine renders as AM/PM lanes with role names people already use: Cleanse, Treat, Moisturize. All the heavy lifting (selection, sequencing, regulatory constraints) stays behind the scenes. The surface stays human; associates don’t need to explain how to read the UI—it reads itself.
Principle 2 — AM/PM Plan that Reads Itself
The routine renders as AM/PM lanes with role names people already use: Cleanse, Treat, Moisturize. All the heavy lifting (selection, sequencing, regulatory constraints) stays behind the scenes. The surface stays human; associates don’t need to explain how to read the UI—it reads itself.
Principle 3 — “Why this” (Explainability in One Line)
Under every product lives “Why this”—benefit, evidence, instruction. Short enough to remember, specific enough to trust. It’s the line clients can repeat at home and the anchor associates rely on under pressure.
Principle 3 — “Why this” (Explainability in One Line)
Under every product lives “Why this”—benefit, evidence, instruction. Short enough to remember, specific enough to trust. It’s the line clients can repeat at home and the anchor associates rely on under pressure.
Principle 4 — Pace without Pressure
Soft micro-timers (“about 45s”) act like tempo cues—not countdowns—so the consult keeps moving without feeling scripted.
Principle 4 — Pace without Pressure
Soft micro-timers (“about 45s”) act like tempo cues—not countdowns—so the consult keeps moving without feeling scripted.
Principle 5 — Choice that Earns Trust
The plan separates primary, secondary, optional items; toggling an optional shows transparent pricing and updated context. Optional really is optional—and paradoxically is chosen more because it’s honest and contextualized. (Transparency and clear add-on logic are also consistent with e-commerce evidence on product-page clarity driving conversions.
Principle 5 — Choice that Earns Trust
The plan separates primary, secondary, optional items; toggling an optional shows transparent pricing and updated context. Optional really is optional—and paradoxically is chosen more because it’s honest and contextualized. (Transparency and clear add-on logic are also consistent with e-commerce evidence on product-page clarity driving conversions.
Principle 6 — Save/Share: Closing the Loop
The consult isn’t complete until the plan goes home. Save/Share sends the routine—written in the same language used at the counter—to the client’s device. This is how the in-store moment becomes a habit at home.
Principle 6 — Save/Share: Closing the Loop
The consult isn’t complete until the plan goes home. Save/Share sends the routine—written in the same language used at the counter—to the client’s device. This is how the in-store moment becomes a habit at home.
The Impact: Measuring Our Success
The Impact: Measuring Our Success
Pilot (2 stores, 1 week)
Time to plan: 9m20s → 7m40s (−18%)
Attachment rate (≥1 add-on): 44% → 56% (+12pp)
Save/Share opt-in: 41%
Associate confidence: +0.6 on a 5-point scale
Plan completion: 82% → 91% (+9pp)
Voices
“I didn’t have to sell the second product—she understood why it belonged in the routine.” — Beauty expert, pilot store
“I know what to do tonight and tomorrow morning. It’s clear—and short.” — Client, moderated session
Operational
Fewer “reset” moments and ~20% fewer how-to questions in month one post-rollout. The content/governance model let Brand & Clinical update copy without breaking flows, reducing ad-hoc design requests and enabling faster iteration. (Clear storytelling + outcome framing is a recommended pattern for case-study readability.
Business Signal
Projected against matched historical days, the model suggested +15% AOV, driven by clearer bundled routines, not pressure. (Projection based on pilot basket mix vs. matched baselines; same-store, matched days; not seasonally adjusted.)
Pilot (2 stores, 1 week)
Time to plan: 9m20s → 7m40s (−18%)
Attachment rate (≥1 add-on): 44% → 56% (+12pp)
Save/Share opt-in: 41%
Associate confidence: +0.6 on a 5-point scale
Plan completion: 82% → 91% (+9pp)
Voices
“I didn’t have to sell the second product—she understood why it belonged in the routine.” — Beauty expert, pilot store
“I know what to do tonight and tomorrow morning. It’s clear—and short.” — Client, moderated session
Operational
Fewer “reset” moments and ~20% fewer how-to questions in month one post-rollout. The content/governance model let Brand & Clinical update copy without breaking flows, reducing ad-hoc design requests and enabling faster iteration. (Clear storytelling + outcome framing is a recommended pattern for case-study readability.
Business Signal
Projected against matched historical days, the model suggested +15% AOV, driven by clearer bundled routines, not pressure. (Projection based on pilot basket mix vs. matched baselines; same-store, matched days; not seasonally adjusted.)
Prototyping for A/B testing
Prototyping for A/B testing
A/B testing
A/B testing
A/B testing
A/B testing
Reflections & Learnings
Reflections & Learnings
What I Learned
In retail time, clarity is a force multiplier. When intent is captured early and the plan explains itself, everything downstream improves: associates move with confidence, clients commit with understanding, and the experience feels premium without theatrics. The shortest honest justification (“Why this”) outperforms long-form marketing copy because it respects the moment’s tempo.
What I’d Do Differently
Bring localization into copy testing earlier—“evidence-first” works globally, but tone & register vary by market.
I’d also expand instrumentation for at-home adherence (the first week is the habit window) and pair Save/Share with gentle, opt-in reminders and micro-explanations.
What I Learned
In retail time, clarity is a force multiplier. When intent is captured early and the plan explains itself, everything downstream improves: associates move with confidence, clients commit with understanding, and the experience feels premium without theatrics. The shortest honest justification (“Why this”) outperforms long-form marketing copy because it respects the moment’s tempo.
What I’d Do Differently
Bring localization into copy testing earlier—“evidence-first” works globally, but tone & register vary by market.
I’d also expand instrumentation for at-home adherence (the first week is the habit window) and pair Save/Share with gentle, opt-in reminders and micro-explanations.