Real estate customer transaction probability prediction method and device, and server
A probabilistic forecasting and real estate technology, applied in forecasting, instruments, electrical digital data processing, etc., can solve the problem of intention degree (the probability of transaction cannot be effectively predicted, etc., and achieve the effect of reducing the difficulty of intention analysis and improving sales performance
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Embodiment 1
[0041] See figure 1 , figure 1 It is a schematic flowchart of a method for predicting the transaction probability of real estate customers provided by Embodiment 1 of the present invention. The method mainly includes the following steps:
[0042] S101. Obtain historical behavior data of the customer to be tested on the target real estate. The historical behavior data of the customer to be tested includes one or more behavior characteristics and a corresponding first frequency of occurrence.
[0043] The model takes "customer id + property id" as the basic unit, that is, to predict the transaction probability of the customer to be tested, based on the historical behavior data of the customer to be tested for the target real estate. For the historical behavior of the user to be tested to other properties The data are not used to predict the transaction probability of the target real estate. Wherein, the historical behavior data includes behavior characteristics, and the first ...
Embodiment 2
[0080] On the basis of Embodiment 1, this embodiment provides a device for predicting the transaction probability of real estate customers. Please refer to Figure 5 The real estate customer transaction probability prediction device 50 is used to realize the steps of the real estate customer transaction probability prediction method described in the first embodiment above, and the prediction device 50 includes a data acquisition module 51 and a processing module 52 .
[0081] Wherein the data acquisition module 51 is used to obtain the historical behavior data of the customer to be measured to the target real estate, the historical behavior data of the customer to be measured comprises one or more behavior characteristics and the corresponding first frequency of occurrence; The decision tree structure obtained by training the training set; the training set includes historical behavior data and customer types of customers selected from the database, and the historical behavior d...
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