Hong Kong takes centre stage at beauty retail-based Big Data hackathon

International beauty and health retailer, A.S. Watson Group (ASW), supports tech innovation and beauty-based entrepreneurship with the first ever retail-themed Big Data hackathon in Hong Kong.

Beauty retail leader A.S. Watson Group (ASW) hosted the first-ever retail-themed Big Data hackathon in Hong Kong. Lasting 36 hours, the non-stop hackathon appealed to over 110 professionals in technology and data science.

Divided into 16 teams, the participants were tasked with solving real-life business issues and offer recommendations on how to boost the customer experience in a retail setting.

Gaining customer insights

Over the course of the two-day hackathon, entrants were asked how the industry could detect certain imminent health incidences, develop an algorithm for prediction, conduct assortment planning, pricing and the personalisation of offers to customers.

“For retailers, big data is a game-changer,” expressed Malina Ngai, Chief Operating Officer, ASW Group.

Commenting on how the beauty and health arenas are shaping its forward-planning, Ngai went on to say: “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.”

The hackathon formed part of this wider initiative, by helping to “enable the local startup communities, data scientist and programmers to bring their creative ideas to life, and provide solutions to enable retailers to become smarter and faster”, Ngai continued.

Spotlight on Hong Kong: Big Data opportunities

ASW’s Big Data-inspired event marks the first time a retailer in Hong Kong has provided gigabytes of business data for use in a hackathon while providing participants with exposure to real-world business scenarios and providing previously unidentified solutions to overcoming them.

At present, data science and big data technology remain relatively unexplored in Hong Kong, with awareness surrounding its capabilities limited.

Therefore, ASW highlights retail as a “key contributor to economic growth” in Hong Kong. It also states that the core “challenge for retailers is to find innovative, efficient and effective ways to draw insights from the ever-increasing amount of structured and unstructured information available about shoppers’ behaviours”.

As the company aims to encourage more companies to organise similar activities to promote the advancement of big data and data science in Hong Kong, Ngai added: “Data and analytics will never replace the experience and judgment in running a retail business, but it can definitely provide us with the tools to perform better. Big data will play a major role in shaping the future of the retail industry.”

Judging criteria

The winners were selected based on the innovation of the technical solution, business impact and quality of the pitch.

A number of prestigious judges considered the awarding criteria, before announcing the winners at the ASW Hackathon.These judges included: Malina Ngai, Group Chief Operating Officer of A.S. Watson Group; Dominic Wong, Managing Director of PARKnSHOP Hong Kong; Tony Verb, Managing Partner of GreaterBay Ventures & Advisors; Donald Tang, Private Investor, Former CEO of D.E. Shaw & Co. (Asia Pacific); Cally Chan, General Manager of Microsoft Hong Kong & Macau; and Jack Lau, Chairman, Swanland. AI & Adjunct Professor, Electronic and Computer Engineering, HKUST.

Winner

Dr. Watson was announced as the winner of the hackathon, along with winning team members Jeffrey Leung, Amy Lau, Eugene Choi, Justin Yek and Jaclyn Tsui. The team’s winning concept comprised a project that uses a machine learning algorithm and integrates weather, search keyword, product information to translate this data into a better customer experience.

Using the app, this enables beauty and health consumers to access health tips and contents utilising collaborative filtering logic to provide personalised information and product recommendation.

Runners-up

Trendmate, designed to enhance the in-store experience of customers by providing personalised and targeted product recommendation, was awarded the first runner-up project.  

The module enhancement also offers in-app contents related to both the interests of the customers and the latest hot topics in the market, when consumers enter the store.

10 Fold Cross Validator was announced as the second runner-up, with its Scan as You Go app feature. The new development strives to help customers scan items in-store and get comprehensive product information as well as personalised offers and discounts immediately. This, in turn, assists with understanding customer behaviour to ascertain optimal discounts.