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Real estate customer transaction probability prediction method, server and computer storage medium

A probabilistic forecasting, real estate technology, applied in forecasting, computing, instruments, etc., can solve problems such as limited passivity

Active Publication Date: 2019-04-12
重庆锐云科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, sales staff rely on traditional reception methods, and the contact with customers and understanding of information are often very limited and passive.
Different salespersons cannot form effective judgment standards due to their own ability and experience. Therefore, how to uniformly judge customer intentions and how to form a unified judgment standard is the main problem.

Method used

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  • Real estate customer transaction probability prediction method, server and computer storage medium
  • Real estate customer transaction probability prediction method, server and computer storage medium
  • Real estate customer transaction probability prediction method, server and computer storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0044] See figure 1 , figure 1 The flowchart of the method for predicting the transaction probability of real estate customers provided in this embodiment mainly includes:

[0045] S101. Obtain historical behavior data of the customer to be tested with respect to the target real estate, where the historical behavior data includes one or more behavior characteristics and corresponding frequency of occurrence.

[0046] The model takes "customer openid + real estate id" as the basic unit, that is, to predict the transaction probability of the customer under test, based on the historical behavior data of the customer under test for the target real estate. For the historical behavior of the user under test on other real estate The data are not used to predict the transaction probability of the target real estate. Wherein, the historical behavior data includes behavior characteristics, and occurrence frequency corresponding to each behavior characteristic.

[0047] Optionally, be...

Embodiment 2

[0090] This embodiment is further described on the basis of the first embodiment.

[0091] The model takes "customer openid+property id" as the basic unit, the number of visitors of this unit in the customer file, the duration of visits in the behavior table, the number of clicks, the number of days since the last visit, and the average daily visits within the visit period Various behavioral data such as duration and average daily visit times are factor variables to construct the data basis of the model.

[0092] Obtain the data required for modeling from the database, embed SQL queries into the Python code through the Python database module, read the data from it and store it as a data structure for subsequent analysis, such as DataFrame, etc.

[0093] Divide the training data into transaction users and non-transaction users, and compare the data characteristics of the two types of data: mean, standard deviation, minimum value, 1 / 4, 1 / 2 / , 3 / 4 quantile and maximum value, etc. ...

Embodiment 3

[0116] This embodiment provides a server, see Figure 10 As shown, it includes a processor 101, a memory 102 and a communication bus 103, wherein:

[0117] The communication bus 103 is used to realize connection and communication between the processor 101 and the memory 102;

[0118] The processor 101 is configured to execute one or more programs stored in the memory 102, so as to realize the steps of the method for predicting the transaction probability of a real estate client in the first and / or second embodiment above.

[0119] This embodiment also provides a computer storage medium, the computer storage medium stores one or more programs, and one or more programs can be executed by one or more processors, so as to implement the first and / or second embodiment above Each step of the real estate customer transaction probability prediction method in .

[0120] Obviously, those skilled in the art should understand that each module or each step of the above-mentioned embodimen...

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Abstract

The invention discloses a real estate customer transaction probability prediction method, a server and a computer storage medium, and the method comprises the steps: obtaining the historical behaviordata of a to-be-tested customer for a target building, and enabling the historical behavior data to comprise one or more behavior characteristics and corresponding occurrence frequencies; comparing the occurrence frequency of each behavior feature with a target threshold interval, and determining a target division attribute of the behavior feature; obtaining a first conditional probability meetinga transaction condition and a second conditional probability meeting a non-transaction condition corresponding to each target division attribute from a transaction model and a non-transaction model which are obtained through modeling in advance; calculating a first transaction probability of the to-be-tested client according to each first condition probability, and calculating a first non-transaction probability of the to-be-tested client according to each second condition probability; calculating a target transaction probability of the to-be-tested client according to the first transaction probability and the first non-transaction probability; accurate estimation of the real estate customer transaction probability is achieved, and the accuracy rate reaches 80% or above according to actual verification.

Description

technical field [0001] The invention relates to the field of real estate data analysis, in particular to a method for predicting the transaction probability of real estate customers, a server and a computer storage medium. Background technique [0002] At present, real estate companies will receive a large number of potential customers during the project sales process, and the judgment and prediction of customers' purchase intentions during the customer reception process are completely based on the self-judgment of the sales staff. However, sales staff rely on traditional reception methods, and their contact with customers and understanding of information are often very limited and passive. Different salespersons cannot form effective judgment standards due to their own abilities and experience. Therefore, how to uniformly judge customer intentions and how to form a unified judgment standard is the main problem. Contents of the invention [0003] The real estate customer ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/16
CPCG06Q10/04G06Q50/16
Inventor 李琦宋卫东
Owner 重庆锐云科技有限公司
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