E‑commerce Innovation and Data Governance: Summaries of Recent Research Topics

The material explains how to obtain an e‑book by following the DataFunSummit WeChat public account and replying with the keyword “电商”.

Alibaba leads e‑commerce innovation: a real‑time online learning re‑ranking model – Introduces the Learning at Serving Time (LAST) method, which updates the ranking model instantly without waiting for user feedback, reducing model bias and improving recommendation performance.

Application of causal inference in internet e‑commerce user growth – Discusses the distinction between causality and correlation, major causal inference schools, and presents gain models for marketing, including theory, modeling, evaluation, challenges, and recommended literature.

How to build full‑link data lineage in e‑commerce scenarios – Explains the concept and importance of data lineage, strategies for constructing a lineage foundation, and practical uses such as table switching, field exploration, and automated metric decomposition, highlighting its role in improving data management efficiency and quality.

Insights from TikTok Group’s data governance practice in e‑commerce – Details challenges at different data‑warehouse maturity stages and solutions through standardized processes, stability and quality assurance, cost governance, and tooling, with a look at future directions.

Detailed e‑commerce tracking and attribution analysis solution from TikTok Group – Describes the overall framework, tracking management, SDK capabilities, attribution platform, and analysis products that enhance tracking quality, development efficiency, and attribution accuracy.

Volcano Engine’s e‑commerce metric management practice based on DataLeap – Covers the background of metric system construction, management methodology, consumption practice, and future plans, emphasizing data consistency, standardized production processes, clear data assets, unified consumption services, and customization.

AI Agent application on the 1688 e‑commerce platform – Explores how logical inference satisfies complex B‑type user needs, improves procurement experience, and drives e‑commerce intelligence, with discussion of solution architecture, AI innovation paradigm, and future roadmap.

XinXuan Group’s data construction journey and its use in live‑stream e‑commerce – Describes the supply‑chain‑centric data system that reduces costs and supports decision‑making, challenges in platform building, data trust, value transmission, and the adoption of TOGAF and V‑shaped architecture for enterprise data management.

The closing note reiterates the e‑book acquisition method via the public account.