‘Customer data is the new oil’: Beauty Matching Engine uses AI and big data to create personalised retail models

By Kacey Culliney contact

- Last updated on GMT

Beauty Matching Engine's white-label software for personalised, optimised beauty retail is already used by Douglas, By Terry and The French Pharmacy
Beauty Matching Engine's white-label software for personalised, optimised beauty retail is already used by Douglas, By Terry and The French Pharmacy

Related tags: personalised beauty, ecommerce, digital, omnichannel, AI, big data

Tech start-up Beauty Matching Engine is using artificial intelligence and big data to offer beauty brands and retailers highly personalised white-label retail models to optimise business.

Launched in 2019 and used already by Douglas, By Terry and The French Pharmacy, Beauty Matching Engine​ – part of L’Oréal’s Open Innovation accelerator program – used artificial intelligence (AI) personalisation software to predict and optimise the entire consumer journey online, in-store and on apps. The software enabled brands and retailers to design sites and curate product offerings accordingly and track behavioural data to further personalise consumer engagement and optimise product recommendations.

‘Beauty has a lot of catching up to do’

Camille Kroely, global head of open innovation and digital services at L’Oréal, said Beauty Matching Engine had an “innovative approach”​ to personalising the entire consumer shopping experience.

Speaking to CosmeticsDesign-Europe, founder of Beauty Matching Engine Nidhima Kohli said the concept had come about after the success of launching her first business My Beauty Matches – a personalised and price comparison shopping tool for consumers.

“I was sitting on so much data and insights from My Beauty Matches and I saw so many companies trying to do personalisation, but there was a lot of talk about it – it’s great for PR – and most of them were not really doing it yet,” ​Kohli said.

Most efforts in personalised beauty retail were only starting points, she said, and efforts with tools like augmented reality (AR) often didn’t provide the best results.

“I would say beauty as an industry is quite behind fashion when it comes to innovation and e-commerce; beauty has a lot of catching up to do.”

The future of beauty retail – ‘customer data is the new oil’

Beauty consumers were typically “overwhelmed with choice”​ when shopping on brand, retailer or pharmacy websites, Kohli said, so the goal of Beauty Matching Engine was to help simplify this whole shopping experience. 

Nidhima Kohli, founder of Beauty Matching Engine
Nidhima Kohli, founder of Beauty Matching Engine

The machine-learning proprietary technology provided relevant content to each consumer based on five years of historical data (from My Beauty Matches), real-time data and AI predictions; this could be in the form of virtual assistant content, emails or complementary products with purchases, among other things, she said.

“Personalisation is something that’s really important – customer data is the new oil. And for a brand to grow, and the brand to stay there and have customer loyalty, they can’t just sit on this data and do nothing. They will fall behind,” ​Kohli said.

The issue across beauty was that utilising big data typically required hiring data scientists and tech experts – something not all companies had resources for – so, Beauty Matching Engine, which installed in two hours and optimised automatically, was the alternative. In terms of the General Data Protection Regulation (GDPR), she said the company worked with insights rather than personally identifiable information (PII) but importantly the data was broad – across all categories, from skin care and hair care through to make-up and fragrances.

Beauty agility vital, particularly during COVID-19

Using data to develop more personalised, relevant retail models, Kohli said, was even more important amid COVID-19.

“What’s important is that brands and retailers need to start being a bit more agile, like start-ups.” ​Particularly with the ongoing crisis, she said it was vital beauty brands and retailers worked to convert online consumer engagement to sales and returning custom “sooner rather than later”.

“…What we’ve seen is that companies who innovate and act quick get on top,”​ she said.

And beauty brands or retailers could “start small”,​ Kohli said, with just a simple plugin from Beauty Matching Engine, for example, that could later be integrated into the website in full.

Whilst Beauty Matching Engine worked across multiple retail channels – online, in-store and apps – Kohli said because of the current landscape with COVID-19, the focus was on e-commerce for the time being.

“It makes more sense for our clients, and it makes more sense for us. …Online was already a growing trend, that’s a no-brainer, but COVID has just accelerated that like crazy.”

Eyes on Asia – ‘that’s where innovation in beauty is really big’

Asked what the expansions plans were for the company, Kohli said the goal was to stretch presence in the EMEA region, but also beyond.

“In the long-run, it would be great to tackle Asia because that’s where innovation in beauty is really big,”​ she said.

Related topics: Brand Innovation

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