When hyper-personalisation is the name of the game, a clutch of startups as well as legacy players in the beauty and personal care (BPC) space are leveraging the advantages of artificial intelligence with a vengeance.
If consumers love the experience, it is because AI is helping them to look better. Users can capture their selfies from different angles and the AI model will process them to identify even the tiniest of problem areas. It will identify skin types, acne, dark spots, discolouration, dryness, uneven skin, wrinkles and pores, and offer real-time recommendations.
Purplle, for instance, uses an in-house tech tool called The Purplle Skin Analyser which leverages AI-powered image recognition to analyse users’ skin conditions in real time. Vivek Parihar, head of engineering, Purplle told FE.
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The firm’s Smart CRM – customer relationship management – tool then uses machine learning to offer hyper-personalised recommendations. “It also takes into account customer behaviour, supported by a dynamic GPT-powered content library and automated journey mapping to optimise customer interactions,” Parihar explained.
Similarly, L’Oreal products, which Nykaa retails, enable consumers to view products in an augmented reality (AR) experience through an advanced, Al-powered virtual try-on technology called ModiFace. The software can detect face shape, skin tone, hair colour and more, and has an average of 88% accuracy.
Vineeta Singh of SUGAR Cosmetics says that technology has helped the team create a more interactive, efficient and enjoyable shopping experience, blending convenience with advanced digital features.
Jasmin Gohil, chief technology officer of the company says, “We use an ML algorithm that suggests things like say, people who have bought SUGAR Ace of Face foundation are more likely to purchase mascara, based on their purchase history.”
The enormous amount of data collected from consumers in the last 2-3 years is one of the primary reasons that these startups are able to update their technology frequently. The data sets from thousands of individuals are first analysed, either in-house, or in some cases by third parties, and then labelled into different categories such as dry skin, pigmented skin, etc. AI technology is then deployed to look at new images and identify the already labelled characteristics.
The process has led to seamless analysis of not just skin products, but lip and hair care products as well. For instance, hair care startups like Traya and Ravel, take quick online surveys on the consumer’s hair type, curate ingredients using ML algorithms and offer products that would suit the user, all within minutes.
Besides virtual try-ons, technology is also being used across various stages such as customer queries, customer feedback, logistics and warehousing, among others. PEP Brands (parent company of mCaffeine and Hyphen) claims it uses advanced CRM systems by adopting Kapture, an AI-driven tool that helps the team categorise and analyse consumer queries more effectively.
Purplle’s search engine integrates features like spell correction and fuzzy logic, along with a self-learning beauty dictionary powered by GPT. Additionally, it offers vernacular search in regional languages, with localised beauty-related queries.
Many startups have also leveraged AI and ML tools to select the right warehouse and logistics partners to deliver orders to users in short span of time. “These technologies have helped us plan inventory and forecasting, which has resulted in huge cost savings and better turnaround time,” Deep Ganatra, CTO, The Good Glamm Group, said.