Premium Beauty News - Beauty Matching Engine (BME) is not your first beauty tech entrepreneurial adventure?
Nidhima Kohli - Five years ago, I have developed a tool called My Beauty Matches (MBM). It helps consumers find the best products for themselves following a diagnostic quiz. They will then receive personalised product recommendations based on the submitted answers. They can then shop them online through the connected retailers thanks to price comparison. To develop this tool, we had identified key ingredients and product claims to match to any beauty concerns. It’s not only for skincare but for every beauty category from makeup to fragrances and hair.
Premium Beauty News - Why develop this new concept?
Nidhima Kohli - We wanted to launch a B2B white label plug-in solution for beauty brands and retailers so they can also now offer their customers a digital beauty assistant, but also help them personalise their full customer journey, i.e. their complementary products, upsells, emails, product listing pages and more - using five years competitor data via MBM.
Created five years ago, My Beauty Matches served as the based of the new engine
Also currently in the market there are many 360 degree personalisation solutions which are great but they are not beauty specific, so they do not give the same 400% uplift in sales like using a beauty specific solution or they take 3-6 months to really show an uplift and are quite manual. Our solution provides effective results from day one.
The Beauty Matching Engine (BME) solution helps companies provide their customers a personalised shopping experience with or without a digital beauty assistant. When replying to the online quiz consumers receive a gradation in percentage, to see which products matches their needs the most and it continuously optimises, unlike a general beauty diagnostic. The AI technology also explains to the customer why the product is being recommended to them.
Premium Beauty News - How does this work?
Nidhima Kohli - By merging AI with beauty specific intelligence, the BME plug-in applies dynamic machine learning algorithms to identify nuanced patterns within consumer datasets. In other words, BME identifies preferred beauty products by age, skin concerns for instance. The more consumers visit the online shop, the more information and the more the tool learns (and we already have 5 years of data).
The engine then narrows down customer choice, predicting which product the customer is most likely to buy, increasing sales & loyalty. BME personalises product recommendations, complementary products, emails, landing pages. Eventually, it improves sales conversion rates by 30-600%.
Beauty websites offer plethora of products and the recommendations are not always accurate in terms of skin tone, lipstick colour or hair thickness for instance. It can result in lower sales conversion due to incorrect product recommendation or choice paralysis (too much choice). Also, without proper targeted data, consumers visits are less frequent or lead to less conversion.
Premium Beauty News - Can the solution be implemented on any platform/website. How does it work for the consumer?
Nidhima Kohli - It’s completely transparent for the consumer. They can click on “Digital Beauty Assistant” or any other nudge on the website to start the quiz and be recommended products. They need to answer a diagnostic quiz asking for their skin type, skin concerns, hair and body concerns and product or scent preference for instance.
The solution can be implemented directly onto a brand website or an online retailer. We just plug it on top of the current website (Javascript/API plugin) without altering the design or the shopping experience. It’s just an additional help to direct the consumer. We just need the product feed and it takes the brand / retailer just 1-2 hours to set up.
The diagnostic quiz can be personalised according the brand category.
We have implemented BME in the UK with the The French Pharmacy. They needed a beauty personalisation solution for the website and a digital beauty consultant to match the in-store recommendations as close as possible. The tailor-made technology was super quick and easy to implement, needing only a couple of hours from the founder. They have already seen a 50% increase in AoV (Average Order Value) a 400% increase in conversion rates to sales.
The tool also offers companies an analytics dashboard with granular beauty profile consumer insights & metrics so their clients can hyper personalise their social media advertising and e-mailings. It can be implemented online, through email or in-store for every beauty category.
Premium Beauty News - You’ve recently joined the L’Oréal beauty tech start-up accelerator at Station F in Paris. How is it helping you?
Nidhima Kohli - The program is aimed at innovative Beauty Tech start-ups, from small to big sizes businesses. BME joined the program in February, and it gives us access to resources from L’Oréal but also business mentoring and investor connections for instance. Station F and L’Oréal also host their own events to help us grow and learn more skills. It’s a real luck and advantage in our competitive world, which I’m really thankful for.
