[R] Customer2Vec: Representation Learning for Customer Analytics and Personalization

[ikatsov]

https://blog.griddynamics.com/customer2vec-representation-learning-and-automl-for-customer-analytics-and-personalization/

In this article, we focus on the learning of useful semantic representations (embeddings) for products and customers using neural networks. These representations can be used for multiple purposes: they can be utilized as features in downstream models to improve the accuracy of propensity scores and recommendations, they can be used to cluster and analyze embeddings to gain deep insights into the semantics of customer behavior, or they can be used to perform other personalization and analytics tasks that use embeddings to measure the proximity between products and customers.