How it works Brands About us Blog Ingredients FAQ

Lab notes / Industry / AI Skincare Platform Buyer’s Guide 2025

AI Skincare Platform Buyer’s Guide 2025

How beauty retailers and brands should evaluate, select, and implement AI skin advisors this year

Start your 2 minute skin quiz today and one of our aestheticians will create a personalised skincare routine for you!Take the skin quiz

Written byPippa HarmanCo-Founder Renude

Start your 2 minute skin quiz today and one of our aestheticians will create a personalised skincare routine for you!Take the skin quiz

Who is this Buyer’s Guide designed for: Heads of Digital, Ecommerce Managers, CX leads and CMOs at beauty retailers and DTC skincare brands evaluating AI advisors to grow conversion, AOV and loyalty. Funnel: Top–Mid.

Executive summary

UK ecommerce conversion is still low single digit, averaging ~3.7% across categories in 2024, with Health & Beauty verticals typically around 3–4%. (eCommerce DB, Doofinder)

Interest in AI shopping tools is mainstream among skincare buyers: 62% of recent purchasers say they’re interested in AI powered recommendations. (Provoke Insights)

Case studies show meaningful uplifts when AI skincare advisors are deployed: SVR saw a 150% uplift in AOV whilst Ellla & Jo saw a 63% uplift in conversion (+214% after receiving a recommendation) and +79% uplift in AOV) both with Renude. With Reveive, SuperPharm reported a significant onsite conversion uplift; JCPenney reported +108% conversion (mass brands) and +23% AOV among skincare users. (Glossy, revieve.com, Business Wire)

Despite Google’s pivot on third-party cookie deprecation in 2025, regulators (CMA) continue oversight of the Privacy Sandbox changes. First party, opt-in data strategies remain essential and must follow UK GDPR and PECR rules. (GOV.UK, Privacy Sandbox, ICO)

The AI beauty market continues to grow: one forecast expects the AI in beauty market to more than double from ~$3.27B (2023) to ~$8.1B by 2028. (Reuters)

Why this guide matters in 2025

Beauty ecommerce remains relatively conversion constrained vs. instore retail. UK ecommerce conversion averaged ~3.7% in 2024, with Beauty/Skincare often reported near ~3.3% and even high performing stores rarely exceed around 5% without significant personalisation. It should be noted however that beauty is one of the higher performing verticals, bested only by Food & Drink at ~4.6%

(eCommerce DB, Doofinder)

At the same time, consumer openness to AI-supported shopping has moved from novelty to norm: nearly two thirds of recent skincare purchasers say they’re interested in AI-powered shopping tools. Trust is strengthening too, with The Future Laboratory reporting that 73% of consumers globally say they trust content created by generative AI. Execution quality still matters, but adoption through platforms like OpenAI, Meta and Google is helping to normalise use.

Privacy shifts are ongoing. Google pushed back its timeline for phasing out third-party cookies again in 2025, while the UK CMA continues to review its Privacy Sandbox framework. For marketers, the practical takeaway is that relying on browser-based tracking is increasingly uncertain. The momentum is toward building first-party, consented data through value-adding touchpoints (like consultations or quizzes), collected in ways that stay compliant with UK GDPR and PECR

(GOV.UK, Privacy Sandbox, ICO)

So, if cookies and browser tracking are becoming unreliable, you’re left with a thinner picture of your shopper, and you can’t just plug the hole with more dubious workarounds. First-party, opt-in data becomes a competitive asset: whoever can capture it, wins and there is no better generator of fresh, first-party user data than how they interact with AI chat and beauty tools.

What an “AI skincare platform” is (and isn’t)

An AI skincare platform is software designed to analyse a shopper’s selfie and text inputs, then generate a personalised skincare regimen with clear explanations in plain English. Modern solutions bring together three key capabilities:

Computer vision to detect skin concerns from images.

Recommendation engines to build tailored routines linked to live inventory.

Conversational interfaces that act like an always-on skin advisor, available anytime.

Unlike traditional online quizzes, which rely on static decision trees and return canned results, true AI platforms adapt dynamically to each visitor. They learn over time, integrate with a your CRM and marketing tools, and evolve alongside customer behaviour.

Clinical disclaimer

AI skincare advisors are intended for cosmetic guidance only. They do not provide diagnosis or treatment and must not make medical claims.

What good looks like: capabilities & evaluation criteria

Use this checklist to compare vendors on outcomes, not buzzwords.

Area	What to look for	Why it matters
Analysis accuracy	Documented performance on common concerns; bias mitigation across skin tones; transparent model updates	Accuracy and inclusivity drive trust. Studies repeatedly flag bias risks in dermatology/computer vision datasets; ask how the vendor mitigates this. (ScienceDirect, ai.sony)
Explainability	Plain language reasons; ingredient-level rationale	Improves buyer confidence, maximises conversion and reduces returns disputes.
Routine building	Multi-product routines aligned to real-time inventory updates	Drives basket size and average order value (AOV)
Conversational UX	Multimodal chat (text and image), brand tone	Increases breadth of use cases for customer support, maximising value
Compliance	UK GDPR + PECR aligned consent capture; cookie usage controls; simple data subject flows	Legal safety and deliverability of marketing comms. (ICO)
Data & activation	Clean first party attributes (concerns, skin type, regimen) to CRM/CDP; opt-in rates	Fuels lifecycle optimisation and provides insights to broader business functions (buying, product development.) BCG has shown retailers underleverage first party data. (Boston Consulting Group)
Integrations	Ecommerce (Shopify, Magento, WooCommerce), ESP/CRM (Klaviyo, Ometria), analytics	Reduces time to value; check native vs custom. (Klaviyo Help Center)
Time to launch	Weeks not months; “widget” or no code options	Faster learning and ROI.
Measurement	Conversion funnel, AOV, opt-in, top performing SKUs, text data insights	Confident commercial attribution.
Support	Playbooks, QA tooling, moderation, change management	Sustained performance beyond launch.

Proof points: what the data says

Ella&Jo (Renude): +63% uplift in conversion and +79% uplift in Average Order Value (AOV) for customers engaging with Renude Skin Routine AI, compared to all site traffic data.

Laboratoire SVR: +150% uplift in AOV, including a 100% increase in basket size and a 40% increase in Average Unit Price. 91% e-mail opt in rate with key skin profile data collected via Klaviyo for future targeting and segmentation.

SuperPharm: +232% uplift in onsite conversion after launching Revieve’s Makeup Advisor; +275% conversion with VTO on PDP. (Business Wire, Silicon Canals)

These are vendor reported case studies; they’re useful directional indicators but you should replicate with your own A/B tests before scaling.

5) Vendor landscape (snapshot)

Vendor	Core approach	Notable features	Example integrations	Selected evidence
Renude	Dermatologist trained Skin Routine AI + AI Skin Chat for live advice; ingredient aware recommendations based on selfies and text input.	Multimodal chat; ingredient level intelligence; plug and play deployment in under 4 weeks (Enterprise APIs available)	Shopify, WooCommerce, Magento; Klaviyo, Ometria	Internal benchmarks: +3.5× conversion, 2× basket, 91% opt-in (update with client case data pre-publish).
Haut.AI	Selfie based analysis + self-serve recommendation widgets	No code app; automatic product inventory sync for Shopify/WooCommerce	Web embed; ecommerce platforms	Vendor states “plug and play” embeds and auto inventory transfer for Shopify/WooCommerce. (Haut.AI, docs.saas.haut.ai)
Revieve	AI skin/hair advisors/VR makeup try-ons + VTO; broad enterprise deployments	Advisor suite; post purchase Skin Coach	Widely deployed with enterprise retailers	BABOR, SuperPharm, JCPenney results above. (Glossy. Business Wire, revieve.com)
Perfect Corp	AI skin analysis + AR virtual try-on	“AI Skin Analysis” Widget Mode (plug and play), HD analysis	Console based widget; VTO stack	Press and product pages detail plug and play widget and HD analysis. (PerfectCorp)

Selection is illustrative, not exhaustive; compare on accuracy, inclusivity, activation, and total cost to outcome.

Implementation blueprint (90 days)

Phase 0: Define success (Week 0)

Pick 1–2 priority metrics and a tight scope (e.g., Skin chat (Initiated via skincare PDP pages, PDP buttons, banners, standalone skin advisor page on brand website) + Routine Builder). Goals typically include conversion uplift, AOV, opt-in rate, and full routine adoption rate.

Phase 1: Pilot (Weeks 1–4)

Install widget or app; connect catalogue; configure brand guidelines and tone.

Instrument analytics (A/B split vs current flow).

Enable consent capture for first party data in line with UK GDPR + PECR. (ICO)

Phase 2: Prove value (Weeks 5–8)

Monitor test results (conversion, AOV, opt-in, engagement).

Triage false positives/negatives in recommendations; refine copy and UX.

Push attributes to CRM (e.g., skin concern, routine) and trigger lifecycle campaigns.

Phase 3: Scale (Weeks 9–12)

Expand coverage (PLPs, PDPs, quizzes redirect to AI, post purchase coaching).

Feed data to paid social and retail media for lookalikes.

Add “chat with a skin expert (AI)” to key drop off points.

Renude deployments typically goes live within 4 weeks via plug and play, then scale feature depth in sprints. During this time Renude deeply integrates with your entire product catalogue.

Risks and how to mitigate them

Analysis bias across skin tones. Ask vendors to evidence dataset diversity and fairness testing. Independent literature highlights underrepresentation of darker skin tones in dermatology datasets. Vendors should show bias testing and remediation. (ScienceDirect, ai.sony)

Overreach into diagnosis. Keep language cosmetic and educational; add clinical disclaimers where relevant.

Privacy & marketing law. Use explicit, granular consent for email/SMS opt-in and ensure cookie usage aligns with PECR and UK GDPR. (ICO)

Operational lift. Prefer vendors with no-code widgets and prebuilt integrations to reduce time to value. (PerfectCorp, Klaviyo Help Center)

KPIs that prove it’s working

Track and report weekly in the first 90 days:

Conversion uplift vs control (A/B): target statistically significant movement.

AOV: multiproduct routine attachment rates. Basket size, Average unit price.

Time on site and depth: advisor sessions vs non-advisor.

Opt-in rate to marketing (email/SMS) from advisor flows.

First party attributes captured (skin concern, routine, skin type).

Return/CS tickets referencing poor product fit.

Attribution: ensure the advisor is a distinct touchpoint in analytics.

Renude internal benchmarks cite +3.5× conversion (post-recommendation), 2× basket size, and 91% optin; replace with live client data prepublication.

AI Skincare Platform Buyer’s Checklist (RFP Matrix)

Category	Renude	Revieve	Haut.AI	Perfect Corp
Commercial outcomes	✅ 3.5x conversion uplift, 2x AOV (case data)	⚠️ Case studies, but often PR-driven	✅ Multiple published case studies	⚠️ ROI claims, fewer transparent studies
A/B rollout plan	✅ Phased deployment, success thresholds	❌ Not publicly documented	⚠️ Limited rollout detail	⚠️ Varies by client
Accuracy & inclusivity	✅ Dermatologist-trained, 100k+ diverse users	⚠️ Mentions inclusivity, limited published data	✅ Publishes validation studies	⚠️ Bias mitigation unclear
By concern & skin tone	✅ Proven across concerns & Fitzpatrick types	❌ No breakdown published	✅ Research papers available	❌ Not specified
Compliance & data	✅ PECR/UK GDPR consent flows; retailer remains data controller	⚠️ GDPR mention only	⚠️ GDPR mention only	⚠️ GDPR mention only
Data schema → CRM/CDP	✅ Klaviyo, Ometria, Salesforce mapping	⚠️ Limited detail	✅ API-first integrations	⚠️ Case-by-case
Integration & time to value	✅ Plug-and-play, live in <4 weeks	⚠️ Custom deployments	⚠️ 6–12 weeks typical	⚠️ 6–12 weeks typical
Supported platforms	✅ Shopify, Magento, WooCommerce, Klaviyo, Ometria	⚠️ Custom integrations	✅ Shopify, WooCommerce, APIs	✅ Shopify, WooCommerce
Support & roadmap	✅ Named CSM, sandbox, release cadence	⚠️ Regional support teams	⚠️ Limited transparency	⚠️ Standard enterprise support
Content moderation	✅ Escalation playbooks	❌ Not specified	❌ Not specified	❌ Not specified