User Experience Analysis of Taobao Detail Page Using User Journey and VOC Data

This article is the second in a ten‑part series on Taobao APP user‑experience data science, focusing on the product detail page.

It describes how user‑journey data (module‑level exposure, clicks, dwell time) and Voice‑of‑Customer (VOC) data from merchant‑customer service chats are collected, labeled, and used to identify key factors influencing browsing decisions.

The methodology includes defining the business problem, selecting relevant data sources, building a multi‑level VOC tag taxonomy, extracting binary phrases with BIO‑CRF, clustering with DBSCAN, and constructing objective‑subjective correlation models.

Data preparation details module‑level event tracking (e.g., price, title modules) and VOC labeling (e.g., product inquiry, packaging, usage). The analysis follows four steps: set goals, design analysis, draw conclusions, and propose product strategies.

Key findings for the men’s‑clothing category show high user attention on specific modules, with VOC indicating concerns about size, quality, etc. Optimization suggestions target module redesign and A/B testing, resulting in significant improvements in conversion rate and reduced dwell time, though overall UV conversion gain was modest.

The article concludes with a brief team introduction and recruitment invitation.