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Beauty Matching Engine, The Personalization And Prediction Plug-in For Beauty Brands And Retailers


BeautyTech and RetailTech company Beauty Matching Engine™ aims at helping customers have a bespoke beauty shopping experience. The UK-based startup led by Luxembourgish founder Nidhima Kohli recently won the DatSci Awards for Best Use of Data Science and AI for Customer Experience. Get to know the startup.
by: Silicon Luxembourg
photo: Beauty Machine Engine
featured: Nidhima Kohli at DatSci Awards


What is BME about?

Beauty Matching Engine™ is a B2B SaaS solution which helps beauty brands and retailers personalize the shopping experience for customers by providing them with personalized Beauty Matches™ (product recommendations), landing pages, emails, upsells and more using beauty specific data layers and AI to help them increase their revenue.

How did you come up with the idea?

We started off with My Beauty Matches™, a beauty price and product comparison site, and realized that there was actually a big demand for personalization in beauty. We scanned the market to realize no one was personalizing the whole consumer journey using prediction technology. It is shocking to see how even some of the bigger retailers like Sephora, Douglas or Ulta are not doing it yet. And, that’s how the idea for Beauty Matching Engine™ came about.

“We disrupt the sectors by being the only personalization and prediction software in the world specific to the beauty industry.”

What is your product/service?

Our service is an Omni-channel JavaScript/API plugin solution, which can be implemented online, in store and emails. It is meant for beauty companies with almost no need for time or resources from their side.

How do you disrupt the RetailTech / BeautyTech sector?

We disrupt the sectors by being the only personalization and prediction software in the world specific to the beauty industry. Our solution takes beauty-related considerations such as ingredients, weather, location, and skin concerns into account etc, to offer the most precise personalized experience. We use dynamic machine learning algorithms to identify nuanced patterns in big data sets to predict what beauty shoppers are more likely to buy. We are also working on making our technology work across every beauty category, including hair, and body.

As a Luxembourgish entrepreneur living in the UK, how do you perceive the local (LUX) ecosystem?

Unlike UK, Luxembourg offers political stability especially given Brexit. It has an international workforce, which is great as we are in talks with clients in France, UK, and Germany. Furthermore, in the UK we are 1 in a million start-ups, whereas in Luxembourg it is much easier to connect with the right people. The UK system, however, seems to have lesser bureaucracy.

“Your entry and Beauty Matching Engine™ epitomize what it is to deploy AI to solve a real customer problem.”

You just won an incredible award. What does this mean for you?

This award is like the Oscars for AI. It has proven how devoted we are to deploying AI in order to enhance customer experience and provided us with credibility over other vendors.

We managed to beat billion dollar companies such as Zalando and Accenture. It definitely warrants recognizing my team’s effort. I am very proud of them. The Head of Data Science Gaming EMEA at Facebook said: “Your entry and Beauty Matching Engine™ epitomize what it is to deploy AI to solve a real customer problem.”

What’s next?

Now that our technology is ready, we are looking forward to launching with clients across Europe and picking up some more awards along the way. We are looking to dominate the BeautyTech space worldwide.

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