Logistics customer loss early warning method, device and equipment and storage medium
A customer loss and logistics technology, applied in the field of logistics management, can solve problems such as different timeliness, low loyalty of major customers, fierce price wars among express delivery giants, etc., to achieve the effect of convenient maintenance and avoiding sudden loss
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Embodiment 1
[0044] Usually, 80% of the sales of a logistics company come from 20% of its overall customers, and such customers are called major customers in the industry. It can be understood that major customers are mainly the customer groups that have core significance and value to the sellers in the market. For small and medium customers, major customers mainly play a significant role in promoting the long-term development and profit improvement of enterprises. It can be seen that key customers are the key factors for logistics companies to increase subsequent sales and obtain profits.
[0045] However, in the current logistics industry, there are generally large fluctuations in the order quantity of large customers. In order to avoid the impact on the income of logistics companies due to the sudden loss of large customers, the present invention provides an early warning method for the loss of logistics customers, which can predict the loss of logistics customers probability, so that i...
Embodiment 2
[0089] The present invention also provides a logistics customer loss early warning device, see image 3 , the device consists of:
[0090] The data processing module 1 is used to collect the original order data of each logistics customer in a historical period, organize and summarize the original order data, and calculate some attributes related to customer loss;
[0091] The model creation module 2 is used to establish a Logistics model based on several attributes, input single-volume data including lost customers into the Logistics model for analysis, and determine the relevant parameters of the Logistics model;
[0092] The early warning module 3 is used to use the Logistics model to predict customer loss based on the determined relevant parameters of the Logistics model, and issue early warning information.
[0093] Wherein, the data processing module 1 includes a data set creation unit and a statistical analysis unit. The data set creation unit is used to remove outlier...
Embodiment 3
[0096] The above-mentioned second embodiment describes the logistics customer loss early warning device of the present invention in detail from the perspective of modularized functional entities. The following describes the logistics customer loss early warning device of the present invention in detail from the perspective of hardware processing.
[0097] Please see Figure 4 , the logistics customer churn warning device 500 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and memory 520 , one or more storage media 530 (such as one or more mass storage devices) for storing application programs 533 or data 532 . Wherein, the memory 520 and the storage medium 530 may be temporary storage or persistent storage. The program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each module m...
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