Ask a beauty marketer what their customers' skin needs and you will get a confident answer. Ask where that answer comes from and it is usually a survey, purchase data, social listening
or a focus group. All useful – but each one records what customers say or buy. None of them records what their skin actually shows.
The simple way is the selfie. When a shopper runs an AI skin analysis on a brand's website, in store or at an event, the analysis evaluates visible features such as wrinkles, dark spots, pores, blemishes, redness, dryness and loss of firmness. One analysis gives that shopper a personal routine. Thousands of analyses, added together, give the brand a picture of what
its whole audience's skin needs.
Why aren't more brands using skin analysis data?
Most brands that offer skin analysis treat it as a sales tool, not a research tool. The analysis recommends products, the shopper buys or leaves, and the data goes no further. Meanwhile, consumer research teams keep working with what people declare. The two rarely meet.
That is a missed opportunity, because skin is an area where what people say and what is there often differ. Shoppers can only report the concerns they notice and know how to name. One may shop for mattifying products while showing signs of dehydration; another may focus on fine lines and overlook uneven tone. A questionnaire captures their perception. An analysis captures their skin.
What does skin analysis data tell a marketing team?
Aggregated skin analysis data answers four questions that surveys and purchase data struggle with:
- Which needs are most common? The share of shoppers showing signs of dehydration, dark spots, blemishes or redness, and the features that tend to appear together.
- How do segments differ? Age ranges, markets, and online versus in-store shoppers, where there is enough data for each group.
- Where does the range fall short? Skin needs that come up often in the audience but are poorly covered by the current assortment.
- How are needs changing? Seasonal differences and shifts between campaigns or periods.
One caveat matters when presenting these figures internally: they describe the people who ran an analysis on the brand's touchpoints, not the whole beauty market. That makes them a precise picture of a brand's own audience – usually the picture marketing needs most.
How can a brand start? Three steps
- Put a skin analysis where customers already are. A widget on the e-commerce site, a Shopify app, a QR code or tablet in store, or an event activation.
- Choose what to measure. For example, the share of shoppers per skin concern, the top needs by age range or the differences between stores.
- Read the results and act. Overall patterns emerge first; comparisons by market, channel or period appear as data builds up, and each segment is shown only when it has enough analyses to support it.
This is how Consumer Insights by Dermaself works: it runs on the same AI skin analysis brands use to recommend products, and delivers the aggregated results in a dashboard built around the KPIs each brand agrees at the start.
What does it look like at a live event?
At Milan Beauty Week 2026, Shaka – the beauty concept of Italian retailer OVS – hosted the Shaka Beauty Hotel, a five-day activation at Garden Senato in Milan featuring 37 beauty brands. Dermaself ran the AI skin analysis experience: visitors took a selfie, saw their main skin concerns and received a routine built from products available at OVS.
Over five days, visitors completed 2,632 skin analyses, roughly one every 55 seconds, with a 75% completion rate. Each visitor left with a personal routine. The organisers also gained
an aggregated picture of the audience the event had actually engaged – useful input for planning their next initiatives. Read the full case study.
Four questions to bring to your next skincare brief
Skin analysis data is most useful when it challenges a specific decision. These are the four questions marketing teams ask most often:
- Does our campaign lead with our audience's most common need, or the one we assume? If dehydration shows up more often than fine lines, the hero message may be aimed at the wrong problem.
- Should the message change country by country? Skin needs can differ between markets, so one global claim may land in one country and miss in another.
- Are online and in-store shoppers the same customer? Comparing channels shows whether a store needs a different assortment, promotion or advisor training.
- Which need does our range cover poorly? A frequent need with few matching products is a brief for R&D, not only for marketing.
What about privacy?
Consumer insights from skin analysis work on aggregated results, so every finding describes a group of shoppers and never a single, identifiable person. Which data can be used, and for
which purposes, is set in the agreement with each brand and in line with the privacy information shown to shoppers before the analysis.
The question for brands already using skin analysis
If your brand already offers skin analysis, the question is simple: does that data feed your planning, or does it stop at the product recommendation? If you don't offer it yet, one touchpoint is enough to start. Either way, the next brief can start from what your customers' skin shows, not only from what they say about it.
Quick answers
How is skin analysis data different from CRM data and market research? Skin analysis data records skin features observed through AI analysis of a selfie, while CRM data records what customers bought and market research records what people declare. Dermaself Consumer Insights adds this observed layer to existing research, so brands can check which needs their audience actually shows rather than only those it reports.
Which teams use consumer insights from skin analysis? Marketing and brand teams use them to choose campaign messages; R&D uses them to prioritise formulations; retail and merchandising teams use them to adapt assortment, promotions and advisor schedules store by store; e-commerce teams use them to refine recommendations and site content.
Does a brand need its own skin analysis touchpoint to get these insights? Yes, the insights come from analyses collected on the brand's own touchpoints. Dermaself Consumer Insights needs at least one active Dermaself touchpoint, such as an e-commerce widget, the Shopify app, an in-store QR code or tablet, or an event activation.
How quickly do useful insights appear? The overall picture of an audience's most common skin needs emerges first, once a meaningful number of analyses has been collected. Comparisons between segments, markets or periods take longer, because each group needs enough analyses of its own to support a reliable comparison.
This article was written by Elena Setaro, CEO and co-founder, Dermaself
