二维码云服务不同行业用户活跃度分析数据

二维码云服务提供商可以利用不同行业用户活跃度分析数据来针对性地优化服务功能和提升用户体验，同时，通过识别和分析不同行业用户平均活跃度得分情况，为二维码云服务提供商的行业市场选择、营销决策和机会挖掘提供数据支持。步骤1：数据抽取和预处理，从公司内部的二维码云服务管理平台抽取用户的使用信息，包括记录日期、用户ID、行业、二级行业、近30日用户累计登陆天数、近30日用户最大登陆天数、近30日用户累计生码数、近30日用户最大生码数、近7日留存标记（即近七日内用户登陆过即为1表示留存，未登录过即为0表示未留存）。去除无效或错误记录，保证数据质量。 步骤2：对登录天数和生码数进行归一化处理，其中：近30日登录天数归一化结果=近30日用户累计登陆天数/近30日用户最大登陆天数；近30日生码数归一化结果=近30日用户累计生码数/近30日用户最大生码数 步骤3：进行用户活跃度计算，计算公式为：用户活跃度评分=W1×近30日登录天数归一化结果+W2×近30日生码数归一化结果+W3×近7日留存标记，W1、W2、W3是权重系数，跟据实际情况进行调整； 步骤4：对于每个行业，计算该行业用户平均活跃度得分，公式为：该行业用户平均活跃度得分=该行业所有用户的活跃度得分之和/行业内的用户数量。

QR code cloud service providers can leverage user activity analysis data across various industries to optimize service functions and enhance user experience in a targeted manner. Meanwhile, by identifying and analyzing the average activity scores of users across different industries, they can obtain data support for industry market selection, marketing decision-making and opportunity discovery.
Step 1: Data extraction and preprocessing. Extract user usage information from the company's internal QR code cloud service management platform, including recording date, user ID, industry, secondary industry, cumulative login days of the user in the past 30 days, maximum login days of the user in the past 30 days, cumulative number of generated QR codes of the user in the past 30 days, maximum number of generated QR codes of the user in the past 30 days, and 7-day retention flag (i.e., 1 indicates retained if the user has logged in within the past 7 days, 0 indicates not retained if the user did not log in). Remove invalid or erroneous records to ensure data quality.
Step 2: Normalize the login days and QR code generation volumes, where: Normalized result of login days in the past 30 days = Cumulative login days of the user in the past 30 days / Maximum login days of the user in the past 30 days; Normalized result of QR code generation volumes in the past 30 days = Cumulative number of generated QR codes of the user in the past 30 days / Maximum number of generated QR codes of the user in the past 30 days.
Step 3: Calculate user activity score, with the formula: User activity score = W1 × Normalized result of login days in the past 30 days + W2 × Normalized result of QR code generation volumes in the past 30 days + W3 × 7-day retention flag, where W1, W2 and W3 are weight coefficients that can be adjusted according to actual conditions.
Step 4: For each industry, calculate the average activity score of users in this industry, with the formula: Average activity score of users in the industry = Sum of activity scores of all users in the industry / Number of users in the industry.