北京市铝扣板产品用户消费能力分层数据

铝扣板产品的销售受地区经济结构，产业组成等条件影响，因此数据收集整理以省份作为划分区间。本数据通过对北京市用户铝扣板产品历史下单数据的收集和分析计算,了解该地区该商品用户消费情况，对消费者进行消费级别的划分，为相关产品批发、零售行业制定采购、销售策略提供数据支持，更好地为消费者提供个性化的商品和服务，从而帮助企业更准确地掌握市场动态，提升行业销售竞争力。1、数据收集：从数据库中根据北京市用户铝扣板产品消费记录梳理数据，选中字段为：订单编号，订单日期，销售省份，客户名称，货品，货品具体描述，统计年份； 2、数据加工：以统计年份为基础，a.先针对订单涉及交易用SUM函数求和，得到该客户消费金额（该客户消费金额字段数值为该客户所有订单累计结果）；得到某年总销售金额（元），具体年份以数据包内字段显示为准；b.该客户消费金额占比=该客户消费金额（元）/某年总销售金额（元）*100%；数据计算四舍五入，结果保留两位小数；c.用户消费占总消费的比例按从大到小进行排名，消费分类运用ABCDEF序列法，对占比大于等于1%以上，给予“A类消费”分层；占比在小于1%到大于等于0.8%区间，则给予“B类消费”分层；占比在小于0.8%到大于等于0.6%区间，则给予“C类消费”分层；占比在小于0.6%到大于等于0.4%区间，则给予“D类消费”分层；占比在小于0.4%到大于等于0.3%区间，则给予“E类消费”;占比在小于0.3%范围内，则给予“F类消费”分层。（数据包内皆为有效消费数据，因此不存在占比为0或小于0的情况） 3、数据应用：A类消费：建立专门的客户关系管理团队，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；C类消费：推荐性价比高的产品组合，激励消费；针对D类及其它分层用户制定宽泛的用户画像，构建大区域性用户分析模型。The sales of aluminum gusset plates are affected by regional economic structure, industrial composition and other relevant conditions. Therefore, the data collection and organization are divided by provinces. This dataset is collected, analyzed and calculated based on the historical order data of aluminum gusset plate products from users in Beijing, aiming to understand the consumer spending situation of this product in this region, classify consumers by their consumption level, provide data support for the formulation of procurement and sales strategies for the wholesale and retail industries of related products, better provide personalized products and services for consumers, and thus help enterprises accurately grasp market dynamics and enhance the sales competitiveness of the industry. 1. Data Collection: Sort out data from the database according to the consumption records of aluminum gusset plate products by users in Beijing, with the selected fields including: order ID, order date, sales province, customer name, product, detailed product description, and statistical year. 2. Data Processing: Based on the statistical year: a. First, sum the transaction amounts of involved orders using the SUM function to obtain the total consumption amount of a single customer (the value of the customer's consumption amount field is the cumulative result of all orders of this customer); the total annual sales amount (in yuan) shall be subject to the field value in the data package. b. The customer's consumption proportion = (customer's consumption amount (yuan) / total annual sales amount (yuan)) * 100%; the calculation result shall be rounded and retained to two decimal places. c. Rank the proportion of user consumption in total consumption from largest to smallest, and use the ABCDEF sequence method for consumption classification: assign "Class A Consumption" tier to users with a proportion ≥ 1%; assign "Class B Consumption" tier to users with a proportion in the range of [0.8%, 1%); assign "Class C Consumption" tier to users with a proportion in the range of [0.6%, 0.8%); assign "Class D Consumption" tier to users with a proportion in the range of [0.4%, 0.6%); assign "Class E Consumption" tier to users with a proportion in the range of [0.3%, 0.4%); assign "Class F Consumption" tier to users with a proportion < 0.3%. (All data in the package are valid consumption data, so there are no cases where the proportion is 0 or less than 0.) 3. Data Application: - Class A Consumption: Establish a dedicated customer relationship management team to maintain close one-on-one communication with these customers; - Class B Consumption: Push personalized recommendations based on consumption history; - Class C Consumption: Recommend cost-effective product combinations to stimulate consumption; - For users in Class D and other tiers: Develop broad user personas and build large-scale regional user analysis models.