Designed to help beauty brands and sellers customize their customers’ online shopping experience, through personalized promotional recommendations and operations, the Beauty Matching Engine software uses multiple layers of beauty-specific data and different machine learning and artificial intelligence technologies. The goal is to maximize revenue by increasing conversion rates and customer satisfaction. Explanations by its founder, Nidhima Kohli.
Premium Beauty News – Beauty Matching Engine (BME) is not your first entrepreneurial adventure in beauty tech?
Nidhima Kohli – Five years ago, I developed a tool called My Beauty Matches (MBM). It helps consumers find the best products for themselves through a questionnaire. They receive personalized product recommendations based on their responses and can then purchase them online through suggested retailers with price comparisons. To develop this tool,we had identified key ingredients and claims corresponding to each need. It is a tool suitable for treatments as for all categories of beauty,from make-up to hairs to perfumes.
Premium Beauty News – Why develop a new concept?
Nidhima Kohli – We wanted to launch a white-label B2B plug-in solution en for brands and beauty retailers, so that they could offer their customers a digital assistant, but also help them customize their customer journey, with complementary products to buy,promotions, emails, product listing pages, etc. All using the masses of data collected over five years via MBM
There are currently many 360 degree customization solutions on the market that are excellent, but are not specific to beauty and only allow the 400% increase in sales that we can achieve with a specific solution to beauty. Or it takes them 3 to 6 months of manual settings to achieve these results. Our solution delivers results from day one.
The Beauty Matching Engine (BME) solution helps businesses deliver a personalized shopping experience with or without the digital beauty assistant. When they answer the online questionnaire, consumers receive a percentage coefficient, to see which products best meet their needs, this coefficient is constantly optimized, unlike a conventional general diagnosis. AI technology also explains to the customer why the product is recommended to them.
Premium Beauty News – How does it work?
Nidhima Kohli – By merging artificial intelligence with beauty-specific data, BME plug-in applies dynamic machine learning algorithms to identify nuanced models within masses of consuming data. In other words BME can, for example, identify preferred products according to the age and needs/problems of each skin. The more consumers visit the online store, the more information we have, the more the tool learns (in addition to our 5-year database).
The engine thus reduces the options offered to customers, predicting which product it is most likely to buy, increasing sales and loyalty. BME customizes product recommendations, related products, email campaigns. In the end, it improves conversion rates by 30 to 600%.
Online beauty platforms have a plethora of products and recommendations are not always accurate in terms of complexion, lipstick color or hair thickness for example. This can degrade the conversion rate due to incorrect recommendations or because of too wide a choice. In addition, without appropriate targeted data, consumer visits are less frequent or lead to less conversion.
Premium Beauty News – Can this solution be implemented on any platform/website? How does it work for the consumer?
Nidhima Kohli – For the consumer, it’s completely transparent. They can click on the “Vitruel Assistant” or any other boost on the website to start the quiz and get recommendations. They must complete a diagnostic questionnaire asking them – for example – for their skin type, their skin and hair problems, their favourite products or perfumes.
The questionnaire can be customized according to the brand category.
We have implemented BME in the UK with The French Pharmacy. They needed a beauty customization solution for their site and a digital beauty consultant to keep online recommendations up to the level of in-store recommendations. The bespoke technology was super fast and easy to implement, requiring only a few hours from the founder. They have already seen a 50% increase in AoV (average value of orders), and a 400% increase in conversion rates in sales.
The tool also offers companies an analytical dashboard with a granular beauty profile and consumer statistics to personalize communications on social networks, emails, etc. It can be implemented online, by email or in-store for each beauty category.
Premium Beauty News – You recently joined the beauty Tech L’Oréal start-up accelerator at Station F in Paris. How does that help you?
Nidhima Kohli – The program is aimed at Beauty Tech start-ups in the start-up phase. BME joined the program in February, giving us access to L’Oréal’s resources as well as business mentoring and the investor network. Station F and L’Oréal also organize their own events to help us evolve and acquire more skills. It’s a real opportunity and an advantage in our competitive world, which I’m really grateful for.
See: www.beautymatchingengine.com online