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An official website visitor loss analysis method based on passenger subdivision

An analysis method and technology of website visitors, applied in marketing, equipment, electronic digital data processing, etc., can solve the problems of official website visitor behavior data, business guidance, visitor value, loss rate, ticket purchase rate, etc., to improve competition force effect

Pending Publication Date: 2019-05-03
科技谷(厦门)信息技术有限公司
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AI Technical Summary

Problems solved by technology

[0003] At present, all airlines have purchased tickets on their official websites, but they have not conducted in-depth analysis and research on visitor behavior, resulting in the lack of important information such as visitor value, churn rate, and ticket purchase rate, and it is difficult to directly generate official website visitor behavior data. Business Guidance

Method used

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  • An official website visitor loss analysis method based on passenger subdivision
  • An official website visitor loss analysis method based on passenger subdivision

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Embodiment

[0033] refer to figure 1 As shown, the present invention discloses a method for analyzing the loss of official website visitors based on passenger subdivision, including the following steps:

[0034] S1. Obtain original official website access log data.

[0035] S2. Perform data cleaning on the original official website access log data to obtain a visitor behavior database, and the visitor behavior database includes a set of visitor behavior variables. Data cleaning is achieved through the following methods:

[0036] Use Hive to perform the first stage of data cleaning on the original official website access log data, including new feature construction and missing value processing. Missing value processing is to interpolate the missing data in variables according to the actual business significance.

[0037] Use R language for the first stage of data cleaning, including outlier processing, outlier processing, and data normalization. The outlier processing is aimed at the l...

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Abstract

The invention discloses an official website visitor loss analysis method based on passenger subdivision. The method comprises the following steps: obtaining original official website access log data;performing data cleaning on the original official website access log data; establishing a visitor value analysis model, and calculating a visitor value score by using a PCA algorithm; carrying out k-means Clustering analysis on the visitor behavior database, and achieving classification of visitor groups; And aiming at different types of visitor groups, respectively training a logit model to obtain a visitor loss analysis and ticket buying probability prediction model. Conducting data mining based on official website access log data, and conducting value analysis, grouping, loss analysis and ticket buying probability prediction on visitors, and providing a powerful basis for a marketing department to achieve precise marketing.

Description

technical field [0001] The invention relates to the technical field of big data processing, in particular to a method for analyzing visitor loss of an official website based on passenger subdivision. Background technique [0002] At present, taking civil aviation flights is an important way for people to travel. With the continuous development of aviation e-commerce and the general trend of Internet +, this also requires a more complete marketing platform support and increasingly perfect e-marketing channels and function construction. [0003] At present, all airlines have purchased tickets on their official websites, but they have not done in-depth analysis and research on visitor behavior, resulting in the lack of important information such as visitor value, churn rate, and ticket purchase rate, and it is difficult to directly generate official website visitor behavior data. Business guidance. Contents of the invention [0004] In order to solve the above problems, the ...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q50/30G06K9/62G06F16/215G06F16/2458
Inventor 陈思恩杨紫胜廖雅哲吴炎泉
Owner 科技谷(厦门)信息技术有限公司
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