江苏省专利代理客户价值度分析数据
收藏资源简介：
通过收集和分析客户专利代理业务相关数据，了解客户对知识产权相关服务的购买力水平和消费偏好，不仅为行业内的所有企业在制定服务策略上提供数据支撑，还能向上游反馈至知识产权服务内容设计与定价策略，更好地为用户制订个性化的专利服务，起到精准客户管理的作用。向下游延伸至企业客户知识产权管理决策支持，具备较强的业务复用性与跨行业参考价值。行业内通过客户价值度分级，可以识别专利服务产品的高价值客户并制定差异化的营销和服务策略，例如：A级客户作为优质伙伴，深度绑定，优先分配订单提供一对一精准服务；B级客户持续深化合作，明确交付周期压缩、追踪进度等....助力企业优化公司资源配置，提升客户满意度和忠诚度，实现客户价值的最大化。1.数据采集： 采集各个客户专利代理的数据，包括客户编号、付款时间、分析时间、省市、服务项目等数据字段。 2.数据预处理： 对采集到的数据进行清洗，去除重复记录，处理缺失值。 3.算法加工：R得分 根据用户付款时间距离分析时间的天数（D）划分为5个等级: 0≤D≤10为5分，10＜D≤20 为4分，20＜D≤30 为3分，30＜D≤50为2分，50<D 为1分； F得分 根据总服务次数（S）,划分为5个等级: 0<S≤2为1分，2＜S≤5 为2分，5＜S≤10 为3分，10＜S≤15为4分，15< S为5分； M得分根据服务总金额 （Z）,划分为5个等级，0<Z≤5000为1分，5000＜Z≤10000 为2分，10000＜Z≤2000 0为3分，20000＜Z≤30000为4分，30000< Z为5分； RFM得分=0.2*R+0.3*F+0.5*M；客户等级分为ABC三级，0≤X≤2为C级，2＜X≤4为B级，4＜X为A级。
By collecting and analyzing data related to customers' patent agency services, this dataset aims to understand customers' purchasing power and consumption preferences for intellectual property (IP)-related services. It not only provides data support for all enterprises in the industry when formulating service strategies, but also feeds back to the upstream design of IP service content and pricing strategies, so as to better develop personalized patent services for users and realize precise customer management. Extending downstream to support enterprise customers' IP management decision-making, this dataset has strong business reusability and cross-industry reference value. Within the industry, customer value grading can identify high-value customers of patent service products and formulate differentiated marketing and service strategies. For example: Class A customers are regarded as high-quality partners with in-depth binding, priority order allocation and one-to-one precise service provision; Class B customers are for deepening cooperation, with clear delivery cycle compression, progress tracking, etc. This helps enterprises optimize their resource allocation, improve customer satisfaction and loyalty, and maximize customer value. 1. Data Collection: Collect data of each customer's patent agency services, including data fields such as customer ID, payment time, analysis time, province and city, service items, etc. 2. Data Preprocessing: Clean the collected data, remove duplicate records, and handle missing values. 3. Algorithm Calculation: - R Score: Divided into 5 levels based on the number of days (D) between the user's payment time and the analysis time: 5 points for 0≤D≤10, 4 points for 10<D≤20, 3 points for 20<D≤30, 2 points for 30<D≤50, and 1 point for D>50. - F Score: Divided into 5 levels based on the total number of services (S): 1 point for 0<S≤2, 2 points for 2<S≤5, 3 points for 5<S≤10, 4 points for 10<S≤15, and 5 points for S>15. - M Score: Divided into 5 levels based on the total service amount (Z): 1 point for 0<Z≤5000, 2 points for 5000<Z≤10000, 3 points for 10000<Z≤20000, 4 points for 20000<Z≤30000, and 5 points for Z>30000. - RFM Score = 0.2*R + 0.3*F + 0.5*M. - Customer levels are divided into three grades: Class C for 0≤X≤2, Class B for 2<X≤4, and Class A for X>4.
