Elevating Guest Repurchasing Behavior Using Buy It Again Recommendations

November 2, 2023

Amit Pande

Principal Data Scientist, Guest & Personalization

Headshot of Rankyung Park, a woman with light brown skin, black hair tied up, wearing black hairband and black shirt, photographed again a white background.
Rankyung Park

Lead Data Scientist

RELATED POSTS

Real-Time Personalization Using Microservices

By Amit Pande, Prathyusha Kanmanth Reddy, and Pushkar Chennu, May 11, 2023
How Target's Personalization team uses microservices to improve our guest experience

Using BERT Model to Generate Real-time Embeddings

By Pushkar Chennu and Amit Pande, March 23, 2022
How we chose and implemented an effective model to generate embeddings in real-time. Target has been exploring, leveraging, and releasing open source software for several years now, and we are seeing positive impact to how we work together already. In early 2021, our recommendations team started to consider real-time natural language input from guests, such as search queries, Instagram posts, and product reviews, because these signals can be useful for personalized product recommendations. We planned to generate representations of those guest inputs using the open source Bidirectional Encoder Representations from Transformers (BERT) model.