A.S. Watson (Superdrug, ICI Paris XL, Watsons)
Selfie-based skin diagnosis and product routine recommendation
At Superdrug, an A.S. Watson banner, users of Revieve's AI Skin Advisor, which analyzes a selfie on more than 120 skin indicators to recommend a routine from the catalog, convert more than 100% better, with average order value up more than 20% (figures published in December 2021).
Key points
- A.S. Watson deploys a selfie-based skin advisor at Superdrug (United Kingdom) and ICI PARIS XL (Netherlands).
- The tool comes from Revieve: computer vision, more than 120 skin indicators, recommendations from the catalog.
- At Superdrug, users of the tool convert more than 100% better, average order value +20%.
- The group extended the pattern to Asia with ModiFace (Skinfie Lab), still offered in the Watsons app in 2026.
Objective
Replace online the advice of a skincare counter sales assistant. The online customer does not know which product suits their skin among thousands of references; A.S. Watson gives them a diagnosis and a routine drawn from the site's catalog, to remove that hesitation and sell more products per order.
The deployment
A.S. Watson, the largest international health and beauty retailer (Superdrug, ICI PARIS XL, Kruidvat, Watsons), installed an AI skin advisor on the websites of two of its European banners. The tool is supplied by Revieve, one of the group's Tech Partners, and deployed by A.S. Watson's eLab team. It is called AI Skin Advisor at Superdrug in the United Kingdom and Skin Analyser at ICI PARIS XL in the Netherlands. The customer takes a selfie on their phone and answers a few questions about their skin type and concerns. Revieve's engine analyzes more than 120 skin indicators on the face, flags in real time insufficient lighting, glasses or a poorly framed face, then returns a detailed analysis and a list of suitable products from the site. A.S. Watson and Revieve published the results in December 2021: at Superdrug, users of the tool convert more than 100% better and average order value rises by more than 20%; at ICI PARIS XL, users spend twice as much time on the site. The sources do not specify the comparison base and describe no A/B test: these are engaged users, so part of the gap may come from self-selection. In Asia, the group replicated the pattern with another supplier: Skinfie Lab, co-developed with ModiFace (L'Oreal), launched in October 2022 at Watsons Hong Kong and announced for six other markets. It recommends a routine from the products of the Watsons eStore, from cleanser to sunscreen.
Results Proof B
The figures come from a joint vendor press release (Revieve) consistent with A.S. Watson's official press release, which repeats the same Superdrug results; no mention in financial results and no published measurement protocol, hence level B.
How it works
Inferred typical approachThe internal detail is not public. Here is a proven approach that leads to the same result, to adapt to your stack.
The stack in detail
- plateforme Revieve AI Skin Advisor Mobile skin diagnosis, more than 120 indicators, deployed at Superdrug and ICI PARIS XL
- plateforme ModiFace Co-development of Skinfie Lab with A.S. Watson for Watsons in Asia
How it runs, concretely
For ops teams-
1Take the selfie and answer the questionnaire customer
The customer photographs their face on mobile and states their skin type and concerns.
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2Check the photo in real time AI (computer vision)
The module flags insufficient lighting, glasses or a poorly positioned face before the analysis.
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3Analyze the skin AI (Revieve)
The engine measures more than 120 skin indicators on the face and produces a detailed analysis.
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4Recommend a routine from the catalog AI / e-commerce
The tool returns a list of site products suited to the profile, which the customer can add to the cart.
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5Track the commercial effect digital team (eLab)
The digital team tracks conversion, average order value and time spent for users of the tool.
The quality of the selfie and the customer's answers about their skin type, cross-referenced with the catalog available on the site. If the catalog connected to the tool is not up to date (discontinued references, stockouts), the routine pushes products the customer cannot buy.
How your customers perceive this type of use
Sourced studiesLe paradoxe est documente des deux cotes : 71% des consommateurs attendent des interactions personnalisees et 76% sont frustres quand elles manquent (McKinsey, 2021), mais 75% declarent ne pas acheter aupres d'organisations auxquelles ils ne confient pas leurs donnees (Cisco, 2024). La « creepy line » est localisee : messages recus quelques secondes apres une recherche et suivi de localisation sont les pratiques qui mettent le plus mal a l'aise (Periscope by McKinsey, 2019).
Acceptance conditions
- La confiance dans le traitement des donnees precede l'achat : 75% ne achetent pas sans elle (Cisco 2024)
- Un cadre legal protecteur rassure : 59% des consommateurs disent que des lois fortes sur la vie privee les rendent plus a l'aise pour partager des informations dans des applications IA (Cisco 2024)
- La personnalisation elle-meme est attendue quand elle est consentie : environ la moitie des consommateurs (US 55%, UK 52%) disent s'inscrire souvent ou parfois a des services personnalises (Periscope by McKinsey 2019)
Red lines
- Le message declenche quelques secondes apres une recherche ou un achat : deuxieme ou troisieme cause de malaise selon les pays (Periscope by McKinsey 2019)
- Le suivi de localisation percu comme de la surveillance : 40% de malaise en Allemagne et au Royaume-Uni (Periscope by McKinsey 2019)
- Le mesusage des donnees personnelles par l'IA, devenu la premiere inquietude des consommateurs, a 53% et en hausse (Qualtrics 2025)
Sources: McKinsey & Company 2021 · Periscope by McKinsey 2019 · Cisco 2024 · Qualtrics 2025
How to replicate
Inference, not sourcedData prerequisites
- Skincare catalog structured by skin type, concern and routine step
- Product availability synchronized with the tool so that only sellable items are recommended
- Tracking that distinguishes sessions that used the tool from the others
Org prerequisites
- A GDPR framework for processing selfies: consent, minimization, retention
- An e-commerce lead who owns the tool and its placement in the journey
- Validation of the advice wording by a skincare expert or dermatologist
Possible stack
- White-label skin diagnosis module (Revieve, ModiFace or equivalent)
- Catalog feed to the recommendation module
- Experimentation tool to measure the effect through an A/B test rather than a comparison of users
The plan, step by step
- Step 1Frame selfie processing with the DPO before any developmentDeliverable: Validated legal basis, notices and retention policy
- Step 2Map the skincare catalog to detectable concerns (acne, wrinkles, pores, spots)Deliverable: Profile-to-product matching rules
- Step 3Integrate a supplier diagnosis module on a dedicated page and on skincare product pagesDeliverable: Selfie, analysis, routine, add-to-cart journey in production
- Step 4Measure the effect through an A/B test on exposure to the tool, not only among its usersDeliverable: Incremental reading of conversion and average order value
First step: Check that the skincare catalog is tagged by skin concern: without this mapping, even the most precise diagnosis does not know which product to suggest.
The same pattern, proven in other industries
Clinique
AI face scan shade diagnosis + AR virtual try-on + complementary product recommendation
Coffret d'Or
vision-AI skin analysis routing to a personalized product recommendation
Function of Beauty
personalized product formulation by algorithm from a quiz
Sources
- S1 AS Watson O+O AI-Powered Skincare Solutions Double Conversion Rate Primary archive pending
- S2 A.S. Watson O+O AI-Powered Skin Advisor Doubles Conversion Rate Enabled by Revieve Interested party archive pending
- S3 AS Watson Innovates AI-Powered Skincare Solutions with L'Oreal's ModiFace in Asia Primary archive pending
- S4 Watsons SG: Your Official App - Google Play Primary archive pending
- S5 Skin Analysis | Skin & Age Analyser | Skincare | Superdrug Primary archive pending
An error, newer info, a source?
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