A report by Emarketer has recently informed that 45% of beauty shoppers are more inclined to carry out online research to search for the appropriate beauty products. Customers are relying heavily on two main sources of information: Artificial Intelligence-based information and information based on customer experiences.
Firstly, regarding the Artificial Intelligence-based information, customers are looking for a digital beauty assistant, a specific beauty AI application or solution which is able to identify their product matches, based on their beauty specific concerns and beauty attributes. Mass marketing is not a viable way anymore to make customers satisfied or convert one time customers into returning customers. Every shopping experience must be individualised and treated as unique.
Secondly, in terms of subjective and neutral reviews, the Millennial Generation and Generation Z, are increasingly looking for beauty feedback and the latest beauty trends and products in social media channels such as Instagram or Youtube videos. The advice of a shopping assistant in-store is no longer seen as reliable, but rather as biased and subjective. This is why Youtube channels or very interactive Instagram accounts seem to be their “beauty best friend”.
Beauty Matching Engine ™, the world’s 1st predictability and personalisation beauty specific solution driven by AI, manages to meet these customers demands by providing a bespoke and tailored shopping journey to its customers by personalising not only product recommendations, but also upsells, landing pages, emails and more. The state of the art beauty specific solution takes into account industry-specific factors such as ingredients, pollution levels, seasons, and skin concerns, to provide the most accurate recommendations and personalised beauty shopping experience. This is achieved using beauty intelligence and beauty metadata layers.