Leveraging Real-Time User Actions to Personalize Etsy Ads

Etsy's adSformer Diversifiable Personalization Module (ADPM) personalizes ranking models by capturing temporal and content signals from user actions within a one-hour session. The ADPM module consists of three components: an adSformer encoder, pretrained representations, and representations learned on the fly. The adSformer encoder uses a modified transformer block to learn a deep representation of the user's session. Pretrained representations leverage item embeddings trained offline, while representations learned on the fly are generated in the downstream models. These components are concatenated to create a dynamic user representation that is integrated into ranking models. The ADPM improves the relevance of sponsored search results by encoding user actions such as search queries, favorites, and purchases. By combining three components, the ADPM outperforms models that use each component independently and provides robustness to input distribution shifts. The ADPM has been deployed in Etsy's sponsored search system, resulting in significant gains in offline and online evaluations.