LiveRetro: Visual Analytics for Strategic Retrospect in Livestream E-Commerce

Yuchen Wu, Yuansong Xu, Shenghan Gao, Xingbo Wang, Wenkai Song, Zhiheng Nie, Xiaomeng Fan, Quan Li

Room: 109

2023-10-26T03:12:00ZGMT-0600Change your timezone on the schedule page
2023-10-26T03:12:00Z
Exemplar figure, described by caption below
LiveRetro system, consisting of Session View, Segment View, Exploration View, and Record View.
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Keywords

Livestream E-commerce, Visual Analytics, Multimodal Video Analysis, Marketing Strategy, Time-series Modeling.

Abstract

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.