arXiv:2603. 20775v2 Announce Type: replace Abstract: In personalized marketing, uplift models estimate the incremental effect of an intervention by modeling how customer behavior would change under alternative treatments using counterfactual analysis.
By Yuxuan Yang, Dugang Liu, Yiyan Huang
The paper introduces AICOME, a framework that uses AI-derived respondent-level measures to recover both individual and group-level effects in contextual models. By applying AICOME to the 2022 China Family Panel Studies, the authors validate that AI measures can replicate key survey variables such as computer use, foreign-language use, weekly hours, and management responsibilities, especially when rich respondent and job data are available. The study also identifies boundary conditions, noting reduced performance when only occupation and basic demographics are used or when multiple related constructs are simultaneously unobserved.
By Wenxin Jiang, Xuyang Wang, Yuxiao Wu
arXiv:2601. 17717v3 Announce Type: replace Abstract: Large Language Models (LLMs) have emerged as powerful tools for generating data across various modalities.
By Kaituo Zhang, Mingzhi Hu, Hoang Anh Duy Le, Fariha Kabir Torsha, Zhimeng Jiang, Minh Khai Bui, Chia-Yuan Chang, Yu-Neng Chuang, Zhen Xiong, Ying Lin, Guanchu Wang, Na Zou
arXiv:2608. 13461v1 Announce Type: new Abstract: Post-click conversion rate (CVR) is a key metric in various scenarios including e-commerce and advertising, reflecting the efficiency and user experience in the second stage of the conversion process.
By Jiayi Dan, Bo Li, Lu Deng, Yong Wang
arXiv:2608. 14606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic survey respondents, but existing evaluations ask whether answers look plausible at the individual level.
By Mantas Lukauskas, Viktorija \v{S}arkauskait\.e
arXiv:2609.06189v1 Announce Type: new
Abstract: This study examines how Customer Relationship Management (CRM), Master Data Management (MDM), and Customer Knowledge Management (CKM) jointly constitut...
By Tejasvi c. Addagada