关于整貂批发意向分析数据

通过收集和分析批发商对整貂类产品相关数据,了解批发商的采购水平和意向度，从而了解该产品是否畅销，从而为本行业的所有企业制定生产策略，更好地为批发商提供个性化的产品和服务1、数据处理：对采集到的数据进行降噪、清洗、脱敏、聚集、分析。 2.数据加工:重复率评分=满分上限100-(ROUND(重复批发排名/总记录数（696）*100,2)；单笔评分=满分上限100-(ROUND(单笔批发最大金额排名/总记录数（696）*100,2)；平均分=（RFM评分+重复率评分+单笔评分）/3；综合得分=ROUND(SQRT(((RFM评分-平均分)^2+(重复率评分-平均分)^2+(单笔评分-平均分)^2)/3),2)；得到的综合评分：0-10分标记为“高意向度批发商”，10-25分区间内标记为“中意向度批发商”，25分以上标记为“低意向度批发商”。

By collecting and analyzing data related to whole mink products from wholesalers, this dataset aims to understand the procurement levels and purchase intentions of wholesalers, evaluate the market sales performance of the products, and provide references for all enterprises in the industry to formulate production strategies and deliver personalized products and services to wholesalers more effectively. 1. Data Processing: Denoise, clean, anonymize, aggregate and analyze the collected raw data. 2. Data Scoring and Classification: The specific scoring formulas are as follows: Repeat Rate Score = 100 (full score ceiling) - ROUND((Repeated Wholesale Ranking / Total Records (696)) * 100, 2); Single Transaction Score = 100 (full score ceiling) - ROUND((Ranking of Maximum Single Wholesale Transaction Amount / Total Records (696)) * 100, 2); Average Score = (RFM Score + Repeat Rate Score + Single Transaction Score) / 3; Comprehensive Score = ROUND(SQRT(((RFM Score - Average Score)^2 + (Repeat Rate Score - Average Score)^2 + (Single Transaction Score - Average Score)^2) / 3), 2). Wholesalers are categorized based on their comprehensive scores: those with scores of 0-10 are marked as "High-intent Wholesalers", those with scores in the range of 10-25 are marked as "Medium-intent Wholesalers", and those with scores above 25 are marked as "Low-intent Wholesalers".

搜集汇总

数据集介绍

特点

该数据集包含696条关于整貂批发商的数据，数据来源于自行产生，涵盖了批发商的唯一标识、批发品类、金额、数量等信息。通过RFM评分、重复率评分等算法规则，评估批发商的意向度，帮助企业了解产品畅销情况并制定个性化服务策略。