青海省铝扣板产品用户消费能力分层数据
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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。本数据通过对青海省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：从数据库中根据青海省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 factors. Therefore, data collection and organization adopt provinces as the segmentation units. This dataset is collected and analyzed based on the historical order data of aluminum gusset plate products from users in Qinghai Province, aiming to understand the consumer spending situation of this product in this region, classify consumers by their consumption tiers, provide data support for the formulation of procurement and sales strategies by wholesale and retail industries of related products, better deliver personalized products and services to consumers, thus helping enterprises accurately grasp market trends and enhance the sales competitiveness of the industry. 1. Data Collection: Sort out the data from the database according to the consumption records of aluminum gusset plate products by users in Qinghai Province, with the selected fields including: order ID, order date, sales province, customer name, product, product detailed description, statistical year. 2. Data Processing: Based on the statistical year: a. First, use the SUM function to sum the transaction amounts involved in the orders, to obtain the total consumption amount of a single customer (the value of this customer's consumption amount field is the cumulative result of all orders of this customer); obtain the total sales amount (in yuan) of a certain year, and the specific year shall prevail as shown in the fields in the data package. b. The proportion of the customer's consumption amount = (customer's consumption amount (yuan) / total sales amount of the year (yuan)) * 100%; the data calculation is rounded, and the result is retained to two decimal places. c. Rank the proportion of each user's consumption in the total consumption from largest to smallest, and apply the ABCDEF sequence method for consumption classification: users with a proportion greater than or equal to 1% are classified as "Class A Consumption"; users with a proportion between less than 1% and greater than or equal to 0.8% are classified as "Class B Consumption"; users with a proportion between less than 0.8% and greater than or equal to 0.6% are classified as "Class C Consumption"; users with a proportion between less than 0.6% and greater than or equal to 0.4% are classified as "Class D Consumption"; users with a proportion between less than 0.4% and greater than or equal to 0.3% are classified as "Class E Consumption"; users with a proportion less than 0.3% are classified as "Class F Consumption". (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: For "Class A Consumption": Establish a dedicated customer relationship management (CRM) team to maintain close one-on-one communication with these customers; For "Class B Consumption": Push personalized recommendations based on their consumption history; For "Class C Consumption": Recommend cost-effective product combinations to stimulate consumption; For "Class D" and other stratified users: Develop broad user personas and build large-scale regional user analysis models.
