电商CTR预测技术演进与营销应用实践研究
A Study on the Evolution and Marketing Applications of CTR Prediction in E-Commerce
摘要: 点击率(CTR)预测是电子商务平台实现智能营销的关键技术，广泛应用于广告投放、商品推荐和用户行为分析等核心场景。随着线上交易规模扩大，精准、高效的CTR预测模型成为提升用户体验与平台收益的重要工具。本文围绕CTR预测在电商中的实际价值，梳理其演进路径与主流方法，重点探讨其在提升广告转化率、优化资源配置与构建用户画像中的应用成效，并展望了个性化、可解释预测模型在未来电商智能营销中的发展方向。
Abstract: Click-Through Rate (CTR) prediction is a key technology for intelligent marketing on e-commerce platforms, widely applied in core scenarios such as advertising delivery, product recommendation, and user behavior analysis. As the scale of online transactions expands, accurate and efficient CTR prediction models have become essential tools for enhancing user experience and increasing platform revenue. This paper focuses on the practical value of CTR prediction in e-commerce, reviews its development trajectory and mainstream methods, and highlights its effectiveness in improving ad conversion rates, optimizing resource allocation, and constructing user profiles. Furthermore, it explores the future direction of personalized and interpretable prediction models in the context of intelligent e-commerce marketing.
文章引用：刘颖琪, 赵金波. 电商CTR预测技术演进与营销应用实践研究[J]. 电子商务评论, 2025, 14(11): 411-419. https://doi.org/10.12677/ecl.2025.14113452

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