Amrita Students Win First Prize in SynerGE HACK-E-LTH by GE Healthcare
January 13, 2022 - 6:00
- A team of 4 students won Rs. 2 lakhs for developing the project in GE HACK-E-LTH
- The idea was to explore Amazon Personize Application Programming Interface (API) to generate a personalized recommendation based on clickstream data
- The project improved user experience tenfold and increased customer retention
A team of four students from Amrita Vishwa Vidyapeetham (Amrita University), Coimbatore, won the first prize at HACK’E’LTH 2021. The 8-week program GE HACK-E-LTH hackathon was conducted between the months of September 2021 and December 2021 and provided an opportunity for students to work on real-time business challenges under the mentorship of GE digital tech experts and build innovative technologies and solutions that can be integrated with our Digital Technology products.
The winning project focused on exploring the use of Amazon Personalize to upgrade the current GE Healthcare E-Commerce website. The prototype project was evaluated by a panel of senior technology leaders and has been highly appreciated by the jury at SynerGEevent organized by GE Healthcare, and a cash prize of Rs. 2 Lakhs has been awarded. The team, Arun Joshua Thomas, Sandeep Rajakrishnan, Samyuktha T. H. and Vighnesh Shankar, were mentored by Mr. Prasanna Hebbar (Principal Software Architect at GE Healthcare) and Mr. Bhaskaran (Head – Technical (Learning & Development – Amrita Vishwa Vidyapeetham)).
Commenting about the students winning the award, Mr. Bhaskaran said, “We are very proud of our students who have worked extremely hard to complete this amazing project that will improve user experience and customer delight. The idea was to explore Amazon Personize Application Programming Interface (API) to generate personalized recommendations based on clickstream data. As part of eCommerce Personalization, the team generated personalized recommendation which recommends products based on popular products, browsing history, etc.
The project showcased a personalized recommendation system that showed relevant recommendations to users based on their past browsing history. The research done by the team showed that the project improved user experience tenfold and increased customer retention. The project was built using Amazon Personalize, Amazon Web Services (AWS) Lambda functions, Next.js on the frontend and various other AWS tools. Finally, after 3 rounds of judging, the project presented by Team Amrita emerged as the winning project.
The model focused on using AWS Personalize for giving recommendations about products for the customers. If a customer is a new customer (cold) then it shows a list of popular products. If a customer is visiting the GE Healthcare website again it uses the past browsing history of the customer to decide on the recommendations. This idea was implemented by the students. This can be worked on further to include it in the GE Website. The advantage of using Personalize is that it simplifies the entire process. Unlike traditional Machine Learning algorithms where one has to train the model, here one can just feed the data and choose a recipe (algorithm). This project can result in improved sales and customer delight for GE Healthcare.