Founded in 2019, Beauty Matching Engine™ (BME) is the first AI based personalisation engine, designed specifically for the beauty retail industry. The solution has been recognised by leading industry experts at L’Oréal and it was recently implemented by the premium makeup brand By Terry Cosmetics and by the retailer Douglas.
“Beauty Matching Engine has an innovative approach to personalising the entire consumer shopping experience at every touch point to help customers find their “Beauty Matches™” in a post COVID world. We look forward to accelerating their development by bringing them our network and expertise in the beauty industry”, tells Camille Kroely, Global Head of Open Innovation & Digital Services at L’Oréal
By merging AI with beauty-specific consumer data, BME is able to accurately predict customer purchasing decisions. This information is then used to transform the customer experience by enabling unique, personalised engagement at each touch point on their online shopping journey, from up-sells to landing pages and product recommendations.
“What makes BME unique, is the fact that the tool is powered by 5 years’ worth of competitor data and beauty intelligence data from cosmetic scientists.”
For the customers, this means that they can benefit from a more streamlined and personalised experience when shopping for their beauty products online. It’s like having a one-on-one, in-store sales assistant guiding them towards the product they are looking for, but from the comfort of their own home.
For brands and retailers, it’s a win as well; the personalised customer experience has shown to significantly increase sales conversions and increase customer loyalty. Based on recent case studies, BME uplifts the average order value by an impressive 50% and it increases the sales conversion rate by up to 400%.
Beauty Matching Engine™ collects data actively by having consumers enter information about their product preferences and skin, hair and body concerns using the ‘Virtual Assistant’. This information allows for BME to pull through AI data in order to recommend the right products instantly. Beauty Matching Engine™ also works passively by observing the consumer’s purchasing and browsing behaviour over time. The more customer shops, the higher the level of personalisation and the more accurate the recommendations will be. This passive approach gives retailers artificial intelligence capabilities without having to build it themselves.
“The Beauty Matching Engine™ plugin can easily be integrated into existing online platforms and it can be installed within a few hours.”
Given the volatile climate initiated by COVID-19, it is now more important than ever for beauty retailers to implement the BME platform to ensure the survival and long-term success of their business. Optimising the online shopping experience of their customers is an important aspect of their digital transformation process. And as stores are now reopening, BME can also be implemented onto touch pads located in-store to create an effective omnichannel strategy.
Aside from being the first personalisation engine created specifically for the beauty industry, what makes BME unique, is the fact that the tool is powered by 5 years’ worth of competitor data and beauty intelligence data from cosmetic scientists. This makes BME’s trademarked “beauty matches™” more accurate, authentic and trustworthy. Furthermore, the large existing dataset means that BME’s personalisation tool starts matching the real needs of the customer from the minute they sign up, unlike other platforms that can take a few months to learn the consumers’ habits before showing an uplift in sales.
The Beauty Matching Engine™ plugin can easily be integrated into existing online platforms and it can be installed within a few hours. The cost of the solution is determined based on the number of users and SKUs.
Photo: Nidhima Kohli, CEO of Beauty Matching Engine™ © Beauty Matching Engine™