Livestream e-commerce integrates live streaming and online shopping, allowing viewers to make purchases while watching. However, effective marketing strategies remain a challenge due to limited empirical research and subjective biases from the absence of quantitative data. Current tools fail to capture the interdependence between live performances and feedback. This study identified computational features, formulated design requirements, and developed LiveRetro, an interactive visual analytics system. It enables comprehensive retrospective analysis of livestream e-commerce for streamers, viewers, and merchandise. LiveRetro employs enhanced visualization and time-series forecasting models to align performance features and feedback, identifying influences at channel, merchandise, feature, and segment levels. Through case studies and expert interviews, the system provides deep insights into the relationship between live performance and streaming statistics, enabling efficient strategic analysis from multiple perspectives.

翻译：直播电商融合了直播与在线购物，使观众能在观看过程中完成购买。然而，由于缺乏实证研究以及定量数据缺失带来的主观偏差，如何制定有效的营销策略仍是一大挑战。现有工具无法捕捉直播表现与反馈之间的相互依赖性。本研究识别了计算特征，制定了设计需求，并开发了交互式可视化分析系统LiveRetro。该系统能够对主播、观众及商品进行全面的直播电商回顾分析。LiveRetro采用增强型可视化与时间序列预测模型，对齐表现特征与反馈，识别在渠道、商品、特征及片段层面的影响。通过案例研究与专家访谈，该系统深入揭示了直播表现与直播统计数据之间的关系，实现了多角度的高效策略分析。