百货网用户购物行为数据

1.精准营销：可用于分析用户浏览、搜索、收藏及购买记录，洞察其兴趣与潜在需求，利用关联规则找商品组合推优惠套餐；按购物频率和时间发营销信息，提升转化率。 2.商品优化与选品：分析销售数据、用户评价和浏览热度，用聚类算法评估商品。结合用户偏好预测需求，为选品和库存管理提供依据。 3.用户体验提升：分析用户购物行为轨迹和操作时间，如停留时长、页面跳转。通过分析用户停留久或跳出频繁，查找问题，优化以提升体验。 4.市场竞争分析：分析用户偏好、价格和策略差异，制定更优市场策略，增强竞争力。

1. Precision Marketing: This dataset can be used to analyze users' browsing, searching, favoriting and purchase records, gain insights into their interests and potential demands, identify optimal product combinations via association rules to launch preferential promotional packages, and send targeted marketing information based on shopping frequency and timing to improve conversion rates.
2. Product Optimization and Selection: Analyze sales data, user reviews and browsing popularity, evaluate products through clustering algorithms, predict market demands by combining user preferences, and provide reliable basis for product selection and inventory management.
3. User Experience Enhancement: Analyze users' shopping behavior trajectories and operational time indicators such as stay duration and page jump frequency. Identify existing problems by analyzing users with prolonged stay or frequent page bounces, and optimize the platform to improve overall user experience.
4. Market Competition Analysis: Analyze user preferences, price differences and peer competitive strategies, formulate more effective market strategies to enhance core competitiveness.

搜集汇总

背景与挑战

背景概述

该数据集记录了百货网平台上用户的购物行为信息，包括浏览、搜索、收藏、购买等操作，可用于精准营销、商品优化和用户体验提升等场景。数据格式为EXCEL，经过缺失值、重复值和异常值处理，并运用聚类和关联规则算法进行分析。