Skinology case study: personalised, dermatologist-led skincare quiz

Skincare is a category where the questions a customer needs answered before buying are particularly hard to solve on a generic product page. Skinology, a Chilean brand founded in Santiago by Antonia Schlesinger, built a personalised quiz to bridge that gap: a dermatologist-designed assessment that feeds an in-house AI model and produces a bespoke formula for every customer. In this case study Antonia walks us through how the quiz, the AI, and the dermatologist sign-off work together.

The vision behind Skinology

Antonia, the founder, was tired of trial-and-error skincare and the overwhelming choice on the shelf. She joined forces with Lia, an experienced dermatologist, to build a skincare line that feels as personal as a clinic visit. Together they designed an interactive online quiz that mimics the questions Lia would ask her patients in person: pregnancy, hormonal conditions, lifestyle, skin reactions.

The quiz responses are reviewed by Lia and by Liam, an in-house AI model whose name combines Lia with the brand’s CTO’s initials. Liam acts as the brain behind each formulation: it synthesises the customer’s responses and proposes the ideal ingredients and concentrations. Lia then reviews the AI’s proposal for accuracy and safety, and once approved the formula is prepared in the lab for that individual.

It’s a high-tech approach to personalisation backed by hands-on dermatology expertise, and a useful pattern for any brand thinking about how to combine an AI layer with a human expert.

“We’re trying to simplify skincare, so you use fewer, more effective products. That’s why every question in the quiz matters: a different combination of answers can lead to vastly different formulations.”

“People find it difficult to understand what tailored skincare means. It’s not a one-size-fits-all; every ingredient has a purpose,” Antonia noted during our conversation.

A routine that evolves

What sets Skinology apart from traditional skincare brands is that the formulation itself evolves. Customers as young as four can begin a Skinology journey, receiving products that adapt as their skin develops. After the first set of products, the app prompts customers to retake a follow-up quiz when they reorder. The follow-up explores how earlier products performed, any changes in skin condition, and lifestyle factors. Every reorder means a reformulated product, matched to the customer’s current needs.

“For example, we had a customer experiencing menopause-related acne for the first time in her life,” Antonia recalled. “She had never struggled with acne before, but due to the hormonal changes, her skin reacted. Using Skinology, she was able to regain control of her skin, and the acne disappeared.”

Every product Skinology delivers is freshly formulated and designed to last just long enough until the next evolution: a new phase in skincare for a continually changing life.

Data-driven skincare, powered by the quiz and Liam

Skinology’s quiz runs on RevenueHunt: Recommender Quiz for Shopify. The quiz collects the data Liam needs to formulate, and the same data lets Skinology evolve products to match each customer’s changing needs.

The two systems work hand-in-hand: the quiz captures the inputs, Liam translates them into a draft formulation, Lia signs off. Each customer ends up with something the brand could not have produced from browsing behaviour alone.

“The quiz collects important data points like name, last name, and a national ID, which we need for our custom formulations. But each piece of information has a purpose: it’s all about crafting the best solution for that individual,” explained Jessica, Skinology’s head of marketing.

The quiz also drives marketing. Because each customer’s answers, recommendations, and follow-ups live on a unified customer record, Skinology can segment by skin profile, lifestyle, or stage of journey, and run retargeting and email flows that match where the customer actually is.

“We’re still learning and fine-tuning our approach, but as soon as we find our footing, we’re ready to scale up.”

Challenges and the future

Skinology has faced the marketing challenges that come with any new, highly personalised model. “It’s been difficult to explain our concept in the short attention spans you get online. When you’re explaining something complex like tailor-made skincare, it’s not easy to condense that into a few seconds for an ad,” Antonia admitted.

The brand currently relies on word-of-mouth, social ads, beauty-event appearances, and SEO focused on sensitive skin and allergic reactions. Around 50% of customers are repeat buyers, which Antonia treats as the strongest signal that the model works once shoppers understand it. Geographic expansion across Latin America is the next step.

“We’re still learning and fine-tuning our approach, but as soon as we find our footing, we’re ready to scale up.”

What other natural-skincare brands can borrow

Three transferable patterns from how Skinology built this:

• Mirror the in-clinic consultation. The quiz questions are the questions a dermatologist actually asks. That makes the quiz feel like care, not a marketing funnel, and it makes the data downstream genuinely useful for formulation.
• AI proposes, human approves. Liam drafts every formulation; Lia signs each one off. The pattern handles scale without removing the expert from the loop, and gives customers the dermatological reassurance the category needs.
• Re-quiz on every reorder. Skin changes; subscriptions don’t. A short follow-up before each reformulation captures lifecycle signals (menopause, pregnancy, climate change, lifestyle shifts) that a static subscription would miss entirely.

FAQ

How is Skinology’s quiz different from a typical product-finder quiz?

It’s designed as a dermatology consultation, not a product picker. The questions mirror what Lia would ask in clinic, and the answers feed an AI formulator (Liam) and a dermatologist sign-off rather than mapping directly to existing SKUs. The output is a bespoke formula made in the lab for that customer.

How does the evolving-formula model work on repurchase?

Before each reorder, the customer takes a short follow-up quiz: how did the last formula perform, did anything change in your skin or lifestyle, are there new concerns. The new answers feed Liam and Lia, who adjust the formulation. Every shipment is therefore freshly formulated and current.

What role does the AI model play, and where does the dermatologist sign off?

Liam ingests the quiz responses and proposes the ingredient mix and concentrations. Lia then reviews the proposal for safety and clinical fit before the lab produces it. The AI handles scale; the dermatologist owns the final call.

What data does the quiz collect, and why?

The quiz captures contact details (name, last name, national ID for the compounded prescription), lifestyle and hormonal context (pregnancy, menopause, contraception), skin history, and reaction patterns. Each field has a downstream purpose in either the formulation or the customer-care flow.

How does Skinology use quiz data outside the formula?

Quiz answers and recommendations attach to the customer record, which lets Skinology segment by skin profile and lifestyle for retargeting, email flows, and re-engagement campaigns timed to the natural reorder cadence.

Next steps

• For the underlying recommendation logic options Skinology and brands like it pick from, see product quiz recommendation systems.
• For the data layer behind segmented marketing, see customer tags in product quizzes and Klaviyo zero-party data.
• For consent collection at quiz time, see marketing consent in your quiz.
• For the broader playbook, see how to build a successful ecommerce quiz and quiz creation mistakes that hurt your ecommerce sales.

To learn more, visit Skinology on Facebook, Instagram, TikTok, YouTube or their website.