Revving up Sales: Quantifying Automobile Relatedness and Predicting Next Purchase through Network Embeddings

This research project aims to enhance the decision-making process in the automotive industry. We analyzed the complete circulation permit data from 2016 to 2021 to establish a relational network structure of vehicles and their embedding representation. Then, we developed recommendation systems that were fine-tuned using customer data. Consequently, the project intends to provide valuable insights for decision-making that can cater to the needs of current and future customers.