The health and beauty retailer hosted the Big Data Hackathon in Hong Kong for 36 hours
A.S. Watson hosted its first retail-themed Big Data Hackathon in Hong Kong on 29 January.
The event took place in an attempt to solve real-life business problems in retail and recommend how to improve customer experiences online.
The 36-hour non-stop hacking frenzy attracted 110 professionals in data and technology science.
The professionals who were split into 16 teams and challenged to detect imminent health incidences, develop algorithms for prediction, assortment planning, pricing and personalisation of offers.
A.S. Watson’s Group Chief Operating Officer Malina Ngai said: “For retailers, big data is a game-changer.
“A.S. Watson Group is adopting a data-first strategy towards understanding customer shopping behaviour, mapping them to our selection of products, shop floor space planning, marketing strategy and selection of store locations.
“We organised this hackathon to enable the local start-up communities, data scientist and programmers to bring their creative ideas to life and provide solutions to enable retailers to become smarter and faster.”
After two days of hacking the winners were chosen based on the judging criteria which included innovation of the technical solution, business impact and quality of the pitch.
Dr Watson was announced as the winning team with members including, Jeffrey Leung, Amy Eau, Eugene Choi, Justin Yek and Jaclyn Tsui.
Leung said: “Big data enables retailers to predict and personalise customer needs accurately.
“This is especially useful when it comes to improving health and wellbeing of customers.”
The winning concept used machine learning algorithms and integrated weather, search keyword and product information, and translated it for a better customer experience.
Ngai added: “Data science is one the fastest growing jobs today around the world.
“I hope that A.S. Watson’s Hackathon provided a unique opportunity for Hong Kong talents not only to gain a better understanding in retail, but also to arouse interests in the application of big data in retail.”