台州区域客户对劳保鞋需求量分析数据
收藏资源简介：
通过收集和分析台州区域客户对劳保鞋的需求量、消费相关数据，了解客户对劳保鞋需求量的购买力水平和消费偏好，为本行业的所有企业提供依据。通过将客户等级划分为“高、中、低”有助于更好的梳理客户，高等级可每月1至2次进行沟通，中等级可每季度1至2次进行沟通，低等级可半年1至2次进行沟通，更好的为客户提供个性化的商品和服务，从而制定更精准的营销策略。1.数据采集：采集客户对劳保鞋的相关交易数据。2.数据处理：对采集到的数据进行分类、合并、累加，便于分析使用。3.算法加工：将处理后的数据进行需求量分析，P=（单笔最少订单数量a1/单笔最少消费额度b1+单笔最高订单数量a2/单笔最高消费额度b2+平均订单数量a3/平均消费额度b3）*K，K为消费系数，不同区域系数大小值不同，按经验取值台州K值为0.7。4.数据分类分级：根据计算出的需求量水平，将客户等级划分为“高、中、低”（2000分以上标记为“高等级”，1000-2000分区间内标记为“中等级”，1000分以下标记为“低等级”，有助于更好的梳理客户，高等级可每月1至2次进行沟通，中等级可每季度1至2次进行沟通，低等级可半年1至2次进行沟通，从而制定更精准的营销策略。
This dataset is constructed by collecting and analyzing the demand volume and consumption-related data of Taizhou regional customers for safety shoes, aiming to understand the purchasing power level and consumption preferences of customers towards safety shoes, and provide a reliable basis for all enterprises in the safety footwear industry. Classifying customers into three tiers: High, Medium, and Low, helps better organize customer groups: high-tier customers can be contacted 1 to 2 times per month, medium-tier customers 1 to 2 times per quarter, and low-tier customers 1 to 2 times every six months, so as to deliver personalized products and services and formulate more precise marketing strategies. The workflow of this dataset includes four parts: 1. Data Collection: Collect relevant transaction data of customers regarding safety shoes. 2. Data Processing: Classify, merge and accumulate the collected data to facilitate subsequent analysis work. 3. Algorithm-based Analysis: Perform demand volume analysis on the processed data with the following formula: P = (a1/b1 + a2/b2 + a3/b3) * K, where a1 represents the minimum single-order quantity, b1 represents the minimum single-order consumption amount, a2 represents the maximum single-order quantity, b2 represents the maximum single-order consumption amount, a3 represents the average order quantity, b3 represents the average consumption amount, and K is the consumption coefficient with varying values across different regions. According to empirical experience, the K value for Taizhou region is 0.7. 4. Data Classification and Tiering: Divide customers into the aforementioned three tiers based on the calculated demand score: customers with a score above 2000 are marked as "High tier", those with a score ranging from 1000 to 2000 are marked as "Medium tier", and those with a score below 1000 are marked as "Low tier". Such tiering helps better organize customer groups, enabling targeted communication frequency and ultimately supporting the formulation of more precise marketing strategies.
