Custom vehicle customer questionnaire analysis processing method and device

Abstract

The invention provides a user-defined vehicle customer questionnaire analysis processing method and device, and the method comprises the steps: collecting a vehicle customer questionnaire in a user-defined manner, investigating questionnaire information, and obtaining the questionnaire relation of a person, a vehicle and a question; vehicle questionnaire information is collected, and vehicle questionnaires of different survey channels are collected to form a data set through a data aggregation channel; obtaining a vehicle questionnaire data set, and storing the vehicle questionnaire data set into an aggregation Entering a service analysis layer, and analyzing the questionnaire information according to three service algorithms of brand, vehicle type and vehicle series; entering a question analysis layer, and performing algorithm analysis on the questionnaire information; entering a locating algorithm analysis layer, and carrying out locating algorithm analysis on the questionnaire information; entering a combinatorial algorithm analysis layer, and performing combinatorial algorithm analysis on the questionnaire information; and entering a value application layer, performing value mining according to the questionnaire data, entering customer insight, and portraying the automobile questionnaire customer according to different business systems of brands, automobile models and automobile series.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a method and device for analyzing and processing a customized vehicle customer questionnaire. Background Art

[0002] The customer questionnaire data currently collected by automobile manufacturers has the following problems: (1) Low data value: The collected questionnaire information does not provide effective feedback to the manufacturer and needs to rely on manual analysis, which cannot quickly tap the potential value of the questionnaire; (2) Inconsistent data format: The questionnaire data collected from different channels has a chaotic format and is not standardized, which makes it difficult to process; (3) Difficult data processing: Due to the lack of an automated processing mechanism, the process of analyzing questionnaire data is time-consuming and inefficient, which affects the practicality of the data. Therefore, for customized vehicle customer questionnaires, it is urgent to parse valuable questionnaire data and solve the problems of difficult customer questionnaire processing and chaotic questionnaires, which lead to low questionnaire value and practicality. Summary of the invention

[0003] In view of the defects in the prior art, the purpose of the present invention is to provide a method and device for parsing and processing a customized vehicle customer questionnaire, which standardizes the questionnaire data through database analysis, business analysis, problem analysis, positioning algorithm analysis, and assembly algorithm analysis to quickly generate structured customer portraits and data models.

[0004] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

[0005] A method for parsing and processing a customized vehicle customer questionnaire, the method comprising:

[0006] S1: Customize the collection of vehicle customer questionnaires, investigate questionnaire information, and obtain the questionnaire relationship between people, vehicles, and questions;

[0007] S2: Collect vehicle questionnaire information. By aggregating data channels, vehicle questionnaires from different survey channels are aggregated to form a data set.

[0008] S3: Obtain the vehicle questionnaire data set and store it in the aggregation business database;

[0009] S4: Enter the business analysis layer and analyze the questionnaire information using three business algorithms: brand, model, and car series;

[0010] S5: Enter the question analysis layer and perform question set algorithm analysis, title algorithm analysis, option algorithm analysis, answer algorithm analysis and respondent algorithm analysis on the questionnaire information;

[0011] S6: Enter the position-selecting algorithm parsing layer, and perform question set position-selecting algorithm parsing, question position-selecting algorithm parsing, option position-selecting algorithm parsing, answer position-selecting algorithm parsing, and respondent position-selecting algorithm parsing on the questionnaire information;

[0012] S7: Enter the combined algorithm analysis layer to perform combined question set algorithm analysis, combined question algorithm analysis, combined option algorithm analysis, combined answer algorithm analysis, and combined respondent algorithm analysis on the questionnaire information;

[0013] S8: Enter the value application layer, conduct value mining based on questionnaire data, enter customer insights, and profile automobile questionnaire customers based on different business systems of brands, models, and car series.

[0014] Preferably, the survey channels include online and offline methods.

[0015] Preferably, the data stored in the aggregation service database supports storage in EXCEL format.

[0016] A device for parsing and processing a customized vehicle customer questionnaire, used to implement any of the above-mentioned methods for parsing and processing a customized vehicle customer questionnaire, the device comprising:

[0017] Questionnaire data aggregation module: used to collect and summarize customer questionnaire data;

[0018] Database: used to store and manage aggregated questionnaire data;

[0019] Parsing module: used to classify and analyze the questionnaire data by brand, model, and car series business dimensions, and to perform algorithm analysis on question sets, questions, options, answers, and respondents;

[0020] Algorithm processing module: Applying position-taking algorithm and combination algorithm to deeply analyze and mine the questionnaire data, the position-taking algorithm analysis includes question set position-taking algorithm analysis, question position-taking algorithm analysis, option position-taking algorithm analysis, answer position-taking algorithm analysis and respondent position-taking algorithm analysis; the combination algorithm analysis includes combined question set algorithm analysis, combined question algorithm analysis, combined option algorithm analysis, combined answer algorithm analysis and combined respondent algorithm analysis;

[0021] Value mining module: used to provide customer portraits and feedback on questionnaire value based on parsed data.

[0022] Compared with the prior art, the present invention provides a customized vehicle customer questionnaire parsing and processing method and device, which uniformly access the questionnaire data of automobile customers, parse and analyze the vehicle questionnaire data, standardize the questionnaire data through database parsing, business parsing, problem parsing, positioning algorithm parsing, and assembly algorithm parsing, and parse and refine the questionnaire data based on the attribute dimensions of vehicle brand, model, and series to form a standard data structure storage and questionnaire data warehouse, which are used to improve vehicle problems, enhance vehicle performance, and provide accurate questionnaire services for customers who continue to pay attention to automobiles. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0024] Figure 1 This is a flow chart of the method for parsing and processing a customized vehicle customer questionnaire in Example 1. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0026] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0027] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in the subsequent figures. In addition, all directional indications in this application (such as up, down, left, right, front, back, bottom...) are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the figures). If the specific posture changes, the directional indication will also change accordingly. Furthermore, the descriptions involving "first", "second", etc. in the application are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated.

[0028] Example 1

[0029] like Figure 1As shown, the method for parsing and processing the customized vehicle customer questionnaire in this embodiment includes:

[0030] S1: Customize the collection of vehicle customer questionnaires, survey questionnaire information, and obtain the questionnaire relationship between people, vehicles, and questions. The survey channels include online and offline methods.

[0031] S2: Collect vehicle questionnaire information, and aggregate vehicle questionnaires from different channels into a data set through the aggregation data channel.

[0032] S3: Obtain the vehicle questionnaire data set, store it in the aggregation business database, and support EXCEL storage.

[0033] S4: Enter the business analysis layer and analyze the questionnaire information using three business algorithms: brand, model, and series.

[0034] S5: Enter the question analysis layer and perform question set algorithm analysis, title algorithm analysis, option algorithm analysis, answer algorithm analysis and respondent algorithm analysis on the questionnaire information.

[0035] S6: Enter the positioning algorithm parsing layer to perform question set positioning algorithm parsing, question positioning algorithm parsing, option positioning algorithm parsing, answer positioning algorithm parsing and respondent positioning algorithm parsing on the questionnaire information.

[0036] S7: Enter the combined algorithm analysis layer to perform combined question set algorithm analysis, combined question algorithm analysis, combined option algorithm analysis, combined answer algorithm analysis and combined respondent algorithm analysis on the questionnaire information.

[0037] S8: Enter the value application layer, conduct value mining based on questionnaire data, enter customer insights, and profile automobile questionnaire customers based on different business systems of brands, models, and car series.

[0038] Example 2

[0039] This embodiment provides a customized vehicle customer questionnaire analysis and processing device, which is used to implement the customized vehicle customer questionnaire analysis and processing method described in the above embodiment, and the device includes:

[0040] Questionnaire data aggregation module: used to collect and summarize customer questionnaire data;

[0041] Database: used to store and manage aggregated questionnaire data, including data in EXCEL format;

[0042] Parsing module: used to classify and analyze the questionnaire data by brand, model, and car series business dimensions, and to perform algorithm analysis on question sets, questions, options, answers, and respondents;

[0043] Algorithm processing module: Apply position-taking algorithm and combination algorithm to deeply analyze and mine questionnaire data. Position-taking algorithm analysis includes question set position-taking algorithm analysis, question position-taking algorithm analysis, option position-taking algorithm analysis, answer position-taking algorithm analysis and respondent position-taking algorithm analysis; combination algorithm analysis includes combination question set algorithm analysis, combination question algorithm analysis, combination option algorithm analysis, combination answer algorithm analysis and combination respondent algorithm analysis;

[0044] Value mining module: used to provide customer portraits and feedback on questionnaire value based on parsed data.

[0045] The above describes the specific embodiments of the present invention. Based on the above description, relevant personnel can make various changes and modifications without departing from the technical concept of the present invention.

Claims

1. A method for analyzing and processing a customized vehicle customer questionnaire, characterized in that: The method comprises: S1: Customize the collection of vehicle customer questionnaires, investigate questionnaire information, and obtain the questionnaire relationship between people, vehicles, and questions; S2: Collect vehicle questionnaire information. By aggregating data channels, vehicle questionnaires from different survey channels are aggregated to form a data set. S3: Obtain the vehicle questionnaire data set and store it in the aggregation business database; S4: Enter the business analysis layer and analyze the questionnaire information using three business algorithms: brand, model, and car series; S5: Enter the question analysis layer and perform question set algorithm analysis, title algorithm analysis, option algorithm analysis, answer algorithm analysis and respondent algorithm analysis on the questionnaire information; S6: Enter the position-selecting algorithm parsing layer, and perform question set position-selecting algorithm parsing, question position-selecting algorithm parsing, option position-selecting algorithm parsing, answer position-selecting algorithm parsing, and respondent position-selecting algorithm parsing on the questionnaire information; S7: Enter the combined algorithm analysis layer to perform combined question set algorithm analysis, combined question algorithm analysis, combined option algorithm analysis, combined answer algorithm analysis, and combined respondent algorithm analysis on the questionnaire information; S8: Enter the value application layer, conduct value mining based on questionnaire data, enter customer insights, and profile automobile questionnaire customers based on different business systems of brands, models, and car series.

2. The method for analyzing and processing the customized vehicle customer questionnaire according to claim 1, characterized in that: The survey channels include online and offline methods.

3. The method for analyzing and processing the customized vehicle customer questionnaire according to claim 1, characterized in that: The storage in the aggregation service database supports storage in EXCEL format.

4. A self-defined vehicle customer questionnaire analysis and processing device, used to implement the self-defined vehicle customer questionnaire analysis and processing method according to any one of claims 1 to 3, characterized in that: The device comprises: Questionnaire data aggregation module: used to collect and summarize customer questionnaire data; Database: used to store and manage aggregated questionnaire data; Parsing module: used to classify and analyze the questionnaire data by brand, model, and car series business dimensions, and to perform algorithm analysis on question sets, questions, options, answers, and respondents; Algorithm processing module: Apply positioning algorithm and combination algorithm to conduct in-depth analysis and mining of questionnaire data, the positioning algorithm analysis includes question set positioning algorithm analysis, question positioning algorithm analysis, option positioning algorithm analysis, answer positioning algorithm analysis and respondent positioning algorithm analysis; the combination algorithm analysis includes combination question set algorithm analysis, combination question algorithm analysis, combination option algorithm analysis, combination answer algorithm analysis and combination respondent algorithm analysis; Value mining module: Used to provide customer portrait and feedback on questionnaire value based on the analyzed data.

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