福建省洗衣平台鞋类清洗用户消费能力分层数据
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统计分析在福建省内各种鞋类清洗用户的消费数据，通过对历史下单用户画像建立，对用户进行标签制定，定位用户消费级别，为企业在福建省各地开发合作的洗衣门店，设立智能共享自助洗衣收发柜，制定广告营销策略提供数据支持，从而帮助企业更准确地掌握市场动态，提升客户满意度和竞争力。1.数据采集：通过洗衣平台后台收集数据，对福建省内用户在2023年内的各种鞋类的清洗次数、清洗金额做数据记录。2.数据处理：消费占比=某用户清洗金额/清洗总金额*100%；3.数据分类：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分类法，对占比大于等于0.1%以上，给予“A类消费”分层；占比在小于0.1%到大于等于0.08%区间，则给予“B类消费”分层；占比在小于0.08%到大于等于0.06%区间，则给予“C类消费”分层；占比在小于0.06%到大于等于0.04%区间，则给予“D类消费”分层；占比在小于0.04%到大于等于0.02%区间，则给予“E类消费”;占比在小于0.02%以下，则给予“F类消费”分层。4.数据应用：通过这样的分析流程，企业不仅能够更准确地把握市场动态，还能够有效提升客户满意度和市场竞争力。
This dataset conducts statistical analysis on consumption data of footwear cleaning users in Fujian Province. By establishing historical order user profiles, formulating user tags and positioning user consumption tiers, it provides data support for enterprises to develop cooperative laundry stores across Fujian, set up intelligent shared self-service laundry pickup and drop-off lockers, and formulate advertising and marketing strategies, thereby helping enterprises accurately grasp market dynamics, improve customer satisfaction and market competitiveness. 1. Data Collection: Data was collected via the backend of the laundry platform, recording the number of cleaning orders and total cleaning expenditure for various footwear products of users in Fujian Province during 2023. 2. Data Processing: Consumption proportion = (cleaning expenditure of a single user / total cleaning expenditure) * 100%. 3. Data Classification: The proportion of each user's consumption in the total consumption is ranked in descending order. The ABCDEF classification method is applied for consumption stratification: users with a proportion ≥ 0.1% are categorized as "Class A Consumption"; users with a proportion between <0.1% and ≥0.08% are categorized as "Class B Consumption"; users with a proportion between <0.08% and ≥0.06% are categorized as "Class C Consumption"; users with a proportion between <0.06% and ≥0.04% are categorized as "Class D Consumption"; users with a proportion between <0.04% and ≥0.02% are categorized as "Class E Consumption"; users with a proportion <0.02% are categorized as "Class F Consumption". 4. Data Application: Through this analysis workflow, enterprises can not only accurately grasp market trends, but also effectively enhance customer satisfaction and market competitiveness.
