户外防风炫光镜客户分层消费分析数据
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为分析户外防风炫光镜在客户群体中的销售情况，需要运用大数据平台收集统计相关产品的销售数据，运用算法进行加工处理后，得到客户的消费系数。对计算所得的消费系数进行分级评价，可以对相应的用户进行标签制定，定位用户消费级别，为企业在生产、装配、零部件采购、库房规划以及镜片储备的选择等相关决策提供数据支撑。本项数据分析在眼镜行业内有巨大的应用价值和推广价值，对行业的市场发展有重要的意义。收集户外防风炫光镜的相关销售数据，形成存证数据包。2.算法公式：客户的消费系数P=订单金额K*消费黏性指数N/平台月度消费总额M*1000。 其中消费黏性指数N由系统统计该客户在公司名下线上店铺累计消费次数得出。将客户的消费系数P按从大到小进行排名。3.根据客户的消费系数P的值对客户的消费数据进行分层评级，当P≥5时，评为“A级消费”；当1≤P＜5时，评为“B级消费”；当0.3≤P＜1时，评为“C级消费”；当P＜0.3时，评为“D级消费”。
To analyze the sales status of outdoor windproof anti-glare glasses among customer groups, relevant sales data of the products shall be collected and counted via big data platforms, and processed with algorithms to obtain the customer consumption coefficient. Hierarchical evaluation of the calculated consumption coefficients allows the formulation of corresponding user tags and positioning of users' consumption levels, providing data support for enterprises' relevant decisions including production, assembly, parts procurement, warehouse planning and lens inventory selection. This data analysis has great application and promotion value in the eyewear industry, and is of great significance to the market development of the industry. 1. Collect relevant sales data of outdoor windproof anti-glare glasses to form an evidential data package. 2. Algorithmic formula: The customer consumption coefficient P = (Order amount K × Consumption stickiness index N) / Monthly total platform consumption amount M × 1000. The consumption stickiness index N is calculated by the system based on the cumulative number of consumption times of the customer on the company's online stores. Rank the customers' consumption coefficients P in descending order. 3. Perform hierarchical rating on customers' consumption data according to the value of their consumption coefficient P: - Grade A consumption when P ≥ 5; - Grade B consumption when 1 ≤ P < 5; - Grade C consumption when 0.3 ≤ P < 1; - Grade D consumption when P < 0.3.
