电商用户数据
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抖音电商用户分群与精准营销策略分析 User_ID 每个用户的唯一标识符，便于追踪和分析。 Age 用户的年龄，提供对人口统计偏好的洞察。 Gender 用户的性别，使能性别特定的推荐和定位。 Location 用户所在地区：郊区、农村、城市，影响偏好和购物习惯。 Income 用户的收入水平，表明购买力和支付能力。 Interests 用户的兴趣，如运动、时尚、技术等，指导内容和产品推荐。 Last_Login_Days_Ago 用户上次登录以来的天数，反映参与频率。 Purchase_Frequency 用户进行购买的频率，表明购物习惯和忠诚度。 Average_Order_Value 用户下单的平均价值，对定价和促销策略至关重要。 Total_Spending 用户消费的总金额，表明终身价值和购买行为。 Product_Category_Preference 用户偏好的特定产品类别。 Time_Spent_on_Site_Minutes 用户在电子商务平台上花费的时间，表明参与程度。 Pages_Viewed 用户在访问期间浏览的页面数量，反映浏览活动和兴趣。 Newsletter_Subscription 用户是否订阅了营销活动通知。
Analysis of Douyin E-commerce User Segmentation and Precision Marketing Strategies User_ID: Unique identifier for each user to facilitate tracking and analysis. Age: User's age, providing insights into demographic preferences. Gender: User's gender, enabling gender-specific recommendations and targeting. Location: User's region (suburban, rural, urban), which influences preferences and shopping habits. Income: User's income level, indicating purchasing power and payment capacity. Interests: User interests such as sports, fashion, technology, etc., guiding content and product recommendations. Last_Login_Days_Ago: Number of days since the user's last login, reflecting engagement frequency. Purchase_Frequency: User's purchase frequency, indicating shopping habits and loyalty. Average_Order_Value: Average order value placed by the user, critical for pricing and promotional strategies. Total_Spending: Total amount spent by the user, indicating lifetime value and purchasing behavior. Product_Category_Preference: Specific product categories preferred by the user. Time_Spent_on_Site_Minutes: Total time (in minutes) a user spends on the e-commerce platform, reflecting engagement level. Pages_Viewed: Number of pages viewed by the user during a visit, reflecting browsing activity and interests. Newsletter_Subscription: Whether the user has subscribed to marketing campaign notifications.
