Check out our other stories on Trending Thought. In today’s world where most of the things have gone digital, we are here to explain to you about the new generation AI transforming the face of beauty. Gone are the days when one would have to visit a parlour to look good in those wedding photos. Now anyone with a smartphone has the option to touch-up their face or hair using the in-built beauty mode or one of the innumerable beauty apps such as Makeup Plus or TheGlamApp and allow your smartphone’s AI transforming the face of beauty. Product companies like Lakmé even have apps that let users apply their products on selfies to see which one suits best to their skin tone.
Artificial intelligence (AI) has only added power to some of these platforms. Hyderabad-based SkinKraft Laboratories, for instance, is one of the few cosmetics companies in India that uses machine learning (ML) to provide more accurate product suggestions to customers keeping their specific skin and health requirements in mind.
Users are asked up to 30 questions pertaining to their skin type and lifestyle choices which might have a direct or indirect implication on their skin health. Based on their responses, the algorithm running in the background figures out the right product for a particular skin type.
“Data has shown us that every user has a a unique skin and it reacts very differently to different products. At SkinKraft, we ask users questions that will help us understand their skin. And based on all of those parameters, our algorithm figures out what is the right cleanser, or the right moisturizer for a particular skin,” notes Chaitanya Nallan, CEO of SkinKraft Laboratories. SkinKraft has generated over a million skin profile records since the platform is visited by at least 45 million users every month.
Some cosmetic companies also use connected wearables to capture data on skin health directly from users. L’Oréal’s skin tracker, My Skin Track UV is one such product that can take readings on the skin, while its companion app (available on Android and iOS) can measure the exposure to environmental aggressors such as ultraviolet radiation, pollution, and humidity to provide personalized product recommendations for better skin health.
Developed by L’Oréal’s dermatology lab La Roche-Posay, the sensor is priced at $59.95 (approx ₹4,266). The lab is also readying a wearable microfluidic sensor, which can measure skin pH levels in 15 minutes.
Using technology to improve the in-store experience is another area which is being explored at the global level by a few companies. So when customers walk in they won’t have to rely on assumptions of shop assistants but can take advantage of AI and face recognition to get better insights.
A case in point is Future X smart stores in Tokyo by Japanese company SK-II in collaboration with P&G. Equipped with 39 hidden cameras with facial recognition and 48 computers, the store does a facial scan to analyze the skin types. As customers walk into the smart beauty bar, a section of the store which has horizontal and vertical screens, they can see the analysis of the skin’s health, followed by a product suggestion that is most appropriate for their skin.
Then there are smart mirrors for home users like Europe-based CareOS’s Artemis which at first glance looks like a regular mirror, but it has cameras that can recognize faces. The mirror can be controlled with voice and uses augmented reality to let users virtually try on different hairstyles or makeup. It also offers tutorials on different ways to apply beauty products. The company is currently working on adding a detection system that will allow the smart mirror to spot and alert users of any anomaly in skin or body posture.
Nallan believes that a technology like ML will eventually have a huge impact on the skincare, haircare and the beauty industry but it will be 3-4 years before we can see any significant results.
Mahesh Makhija, partner, EY India, agrees that ML will play a significant role in this field and is going to be a part of every retail company’s repertoire of solutions. He also adds, “ML models need large data sets to train on.
Adoption of technology by beauty and personal care companies is still at a nascent stage not just in India but globally as well but is likely to increase. Makhija believes that over a period of time adoption of emerging technologies will rise as companies will want to scale up their offerings to customers and differentiate their products. And for that, they will have to start adopting technologies like AR, ML and, embedded solutions.
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