吉林省低托滞前制动钳产品消费水平分层数据

统计分析吉林省低托滞前制动钳产品消费数据，根据消费比例评估消费能力，获得消费能力分层数据。其应用场景广泛，对企业内部，为产业结构调整，仓储计划的设立以及产品广告营销策略提供数据支持；对上游原料供应商，可根据不同产品消费情况，更精准地规划生产与备货，提升产业链协同效率；对于本行业全领域，提供数据指导生产实践，提高服务水平，降本增效的优秀实践，提供市场洞察和参考基准，为其在生产、服务、营销等多环节多链条上提供数据支撑。1、数据收集：从数据库中根据吉林省低托滞前制动钳产品消费记录梳理数据，选中字段为：订单编号，客户识别码（脱敏代码），订单时间，产品大类，产品名称，消费区域，统计年份，订单内消费数量（件），订单内消费金额（元）； 2、数据加工：以统计年份为基础，a.先针对本区域内订单交易用SUM函数求和，得到本年总消费数量（件）和本年总消费金额（元），具体年份以数据包内字段显示为准；b.进行算法计算：消费数量占比A=订单内消费数量/本年总消费数量*100%；消费金额占比B=订单内消费金额/本年总消费金额*100%；数据计算四舍五入，结果保留两位小数（件数相关数值只有整数，精确到个位）；计算消费水平系数S，S＝A＋B。c.消费水平系数按从大到小进行排序，对S≥0.50的，给予“A类消费”分层；对0.50＞S≥0.30的，则给予“B类消费”分层；0.30＞S＞0.00的，则给予“C类消费”分层（数据包内皆为清洗筛选后的有效消费数据，不存在S等于0.00或小于0.00的情况） 3、数据应用：A类消费：将数据总结回传市场部门，结合客户档案，建立专门的订单-客户-客服关系管理团队，与他们保持密切的一对一沟通；B类消费：根据消费历史推送个性化推荐及优惠政策，刺激消费；C类消费：搭建数据档案，为订单及订单客户人群制定用户画像，构建大区域性用户分析的数据方案。

This dataset conducts statistical analysis on the consumption data of low-dwell front brake calipers products in Jilin Province, evaluates consumption capacity based on consumption proportions, and obtains consumption capacity stratified data. It has a wide range of application scenarios: for internal enterprise operations, it provides data support for industrial structure adjustment, warehouse planning formulation, and product advertising and marketing strategies; for upstream raw material suppliers, it enables more accurate production and stock planning based on different product consumption situations, improving the collaborative efficiency of the industrial chain; for the entire industry, it provides data guidance for production practices, improves service levels, offers excellent practices for cost reduction and efficiency enhancement, provides market insights and reference benchmarks, and supports multiple links and chains including production, service and marketing with data.

1. Data Collection: Sort out the data from the database according to the consumption records of low-dwell front brake calipers products in Jilin Province. The selected fields are: order number, customer identification code (anonymized code), order time, product category, product name, consumption region, statistical year, order consumption quantity (unit: piece), and order consumption amount (unit: Yuan).

2. Data Processing: Based on the statistical year:
a. First, use the SUM function to sum the regional order transactions to obtain the total annual consumption quantity (unit: piece) and total annual consumption amount (unit: Yuan). The specific year shall prevail as shown in the fields of the data package.
b. Perform algorithm calculations: Consumption quantity proportion A = (order consumption quantity / total annual consumption quantity) * 100%; Consumption amount proportion B = (order consumption amount / total annual consumption amount) * 100%. The data calculation shall be rounded, with results retained to two decimal places (values related to quantity are only integers, accurate to the unit). Calculate the consumption level coefficient S, where S = A + B.
c. Sort the consumption level coefficients in descending order. For those with S ≥ 0.50, they are classified as "Class A Consumption"; for 0.50 > S ≥ 0.30, they are classified as "Class B Consumption"; for 0.30 > S > 0.00, they are classified as "Class C Consumption" (all data in the package is valid consumption data after cleaning and screening, and there are no cases where S equals 0.00 or is less than 0.00).

3. Data Application:
Class A Consumption: Summarize the data and feed it back to the marketing department, combine it with customer files, establish a dedicated order-customer-customer service relationship management team, and maintain close one-on-one communication with them;
Class B Consumption: Push personalized recommendations and preferential policies based on consumption history to stimulate consumption;
Class C Consumption: Establish data files, develop user portraits for orders and order customer groups, and build a data plan for large regional user analysis.

搜集汇总

背景与挑战

背景概述

该数据集基于吉林省低托滞前制动钳产品的消费记录，通过统计消费数量和金额占比，计算消费水平系数，将消费能力划分为A、B、C三个层次。它旨在为企业提供数据支持，用于产业结构调整、仓储计划和营销策略优化，同时协助上游供应商精准规划生产，提升产业链协同效率，并为全行业提供市场洞察和参考基准，实现降本增效。