Cross-Border E-Commerce TikTok Live Streaming Data Three-Dimensional Optimization Model Construction and Empirical Study — Based on Singaporean Technology Product Markets and Scenario Migration to U.S. Warehousing Services

In zero-paid-traffic scenarios, TikTok technology live streams typically face a systemic dilemma characterized by scarce traffic entry points, inadequate audience retention, and depressed average order values. Extant research predominantly focuses on low-involvement product categories and paid growth strategies, leaving a theoretical gap in systematic investigation of organic growth mechanisms for high-involvement technology products. Grounded in attention economy theory and collaborative optimization theory, this study employs 42 live streams featuring 15 technology products from Tesen Global Technology in Singapore as a natural experiment. We construct a three-dimensional collaborative optimization model encompassing “time slots—scripts—product mix” and implement real-time attention allocation via online gradient descent algorithms, while dynamically iterating product combinations through Thompson Sampling. Validation using 73-day panel data demonstrates that post-intervention, organic follower growth increased by 208%, conversion rates rose by 125%, average order value climbed by 20.5%, and cumulative advertising expenditure savings reached $12,000; 5,000 randomization permutation tests confirm robust effects (p<0.01). Furthermore, applying service marketing theory, we migrate the model to the U.S. small-to-medium warehousing sector, proposing an “inventory turnover rate visualization live stream + service package matrix” approach, which is projected to reduce customer-per-lead costs (CPL) from $180 to $90. This research establishes a multi-dimensional collaborative optimization framework for live streaming, filling theoretical voids regarding high-involvement product growth in zero-ad-spend contexts and providing a replicable methodological paradigm for organic cross-border e-commerce expansion.