Increase in average
BY TERRY is an award-winning French luxury beauty brand recognised and sold international encompassing makeup, skincare and fragrance. BY TERRY is stocked in more than 20 markets and is represented in 45 countries including France, UK and USA.
As an influential beauty brand around the world, BY TERRY understands its customers’ needs and wants to offer them a 360° personalised and innovative shopping experience. Personalised recommendations had to be found at every step of the shopping experience in order to help their customers make informed decisions without choice paralysis.
It was also vital that customers understood the reasoning behind BY TERRY’s recommendations. For this reason, a concise explanation concerning the products’ relevance to the customer had to be included with every suggestion.
Having established such an international presence, BY TERRY needed to cater a service that would be quick and easy to implement internationally in various languages and support multiple currencies. Furthermore, as their technical team is outsourced they needed a solution which was quick and easy to implement without taking multiple hours and days to do.
Finding a way to give accurate real-time recommendations that take into account all possible permutations on each landing page was key, all whilst checking stock availability, colour, consumer profile, discontinued products all while enhancing the shopping experience with 1 to 1 personalisation.
Beauty Matching Engine (BME) provided customers with powerful, real-time, and meaningful customized suggestions that drove traffic to purchase.
Using the Virtual Assistant, consumers entered their details by answering interactive assessment style questions about their skin condition, skin issues, and preferences for the fragrance or scent.
Beauty Matching Engine solution allowed BY TERRY to upgrade their customer's experience. This feature enabled unique, personalized engagement at each touchpoint on their online shopping journey, from up-sells to landing pages and product recommendations.
By merging AI with a beauty specific and competitor intelligence, Beauty Matching Engine (BME) applied complex and dynamic machine learning algorithms to identify nuanced patterns within consumer datasets.
The engine then narrows down customer choice, in order to dynamically predict and personalise which products customers are more likely to buy, thus increasing sales and loyalty.
Increase in Average Order Value