Data acquisition method based on applet

Abstract

The invention relates to the technical field of data acquisition, in particular to a data acquisition method based on an applet, and the method comprises the following data acquisition steps: 1, analyzing a demand, and determining the data acquisition content according to the target of the required data acquisition, and 2, positioning the data type, and carrying out regional division through the geographic position. Compared with the universality of information collection of traditional questionnaire survey, the data platform of the scheme sets multiple groups of classification standards for the content of the questionnaire survey in a development link, sets a question bank and collects data for clients of different classifications, so that the collected information is more accurate, and in the collection process, the collection efficiency is improved. According to the method, data processing and screening can be carried out only by replacing questions, meanwhile, the proportion of necessary questions is guaranteed, core data collection of questionnaire objects is accurate and does not deviate, and auxiliary collection of client classification information feedback is carried out by replacing the questions.

Description

Technical Field

[0001] The present invention relates to the technical field of data collection, and particularly relates to a data collection method based on a mini-program. Background Art

[0002] WeChat mini-program is an application that can be used without downloading and installation. Users can directly access and use it in WeChat. Users do not need to download and install the application program. They only need to search in WeChat or scan the QR code to directly use it, which is convenient and fast. Mini-programs are applicable to various industries and fields, such as retail, catering, tourism, education, medical care, etc., to meet the needs of different users. The WeChat platform conducts strict security reviews and management on mini-programs to ensure the data and privacy security of users.

[0003] After retrieval, based on the authorized announcement number CN111310092B, it discloses a data collection method based on a mini-program, which is specifically implemented according to the following steps: Step 1: Build a perfect task system, and realize three functions including task release, task query, and task tracking through the transmission of information between the front end and the back end; Step 2: Implement a high-concurrency solution to ensure the platform's processing ability for a large number of requests when multiple users access, and avoid server unresponsiveness caused by lags and thread blockages; Step 3: Complete task review: Combine automatic review with manual review to improve the accuracy of review results; Step 4: Perform data annotation. The present invention establishes a data collection platform to assist users in directly obtaining the required specific data, without the need for users to perform a large amount of screening and elimination of data by themselves, reducing the proportion of invalid data in big data, providing a large amount of high-quality data, improving data validity, and further improving utilization rate and user work efficiency.

[0004] Currently, when collecting customer data in WeChat mini-programs, especially some sales-related WeChat mini-programs, they mainly obtain customer information in the form of questionnaires. However, in most cases, the content of the questionnaires is relatively fixed and cannot push corresponding questionnaire questions according to the classification of customers after they log in. At the same time, after the information collection of the questionnaire survey, it is basically simple option screening to obtain the content of information collection, resulting in a relatively large proportion of the content of useless data collection, which directly affects the accuracy of subsequent data integration. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a data collection method based on a mini-program. The data collection steps are as follows:

[0006] The first step: Requirement analysis. According to the target of the required data collection, clarify the content of data collection;

[0007] Step 2: Locate the data type, divide the area by geographical location, and then collect the feedback information of customers through the form of questionnaire surveys;

[0008] Step 3: Design an interface with a comfortable user experience, and quickly build the interface through the UI component library of the WeChat mini-program, such as WeUI;

[0009] i: Use the development framework of the WeChat mini-program (such as WXML, WXSS, JavaScript, etc.) to build the application;

[0010] ii: Utilize the APIs of the WeChat mini-program (such as wx.request, wx.getUserInfo, etc.) to implement data collection and interaction functions;

[0011] Step 4: Content development, design the login method. After logging in based on WeChat, there is no need for secondary identity authentication. The data collection of the mini-program can enter the questionnaire interface through methods such as customer independent selection and advertisement pop-ups;

[0012] Based on the data collected from the questionnaire survey, use the local storage or cloud development services provided by the WeChat mini-program to implement the data storage function, and upload the collected data to the server or cloud to achieve the data upload function;

[0013] i: Use the cloud development services of the WeChat mini-program (such as cloud database, cloud functions, cloud storage, etc.) to simplify backend development;

[0014] ii: The cloud database is used to store user data and the information collected;

[0015] iii: Cloud functions are used to process data and execute business logic;

[0016] Step 5: Data processing, process and analyze the collected data on the server side or in the cloud;

[0017] i: Use the JSON format to transmit data;

[0018] ii: Use the HTTPS protocol to encrypt data transmission to ensure data security;

[0019] Step 6: Data analysis, use data analysis tools (such as the Pandas library of Python, R language, etc.) to perform data cleaning, statistical analysis, and visualization;

[0020] i: Use programming languages such as Python and R and data analysis libraries (such as Pandas, NumPy, Matplotlib, etc.) to perform data processing and analysis;

[0021] ii: Use machine learning algorithms (such as classification, clustering, regression, etc.) to perform in-depth analysis;

[0022] Step 7: Collect data security and protect user privacy;

[0023] i: Use the user authentication and authorization mechanism provided by WeChat (such as OAuth 2.0) to ensure the authenticity of the user's identity. Only after obtaining the user's consent can the user's data be collected and used.

[0024] Furthermore, the content development in the fourth step may set up a question bank for the questionnaire survey, and push corresponding questionnaire questions according to the customer's login information.

[0025] Furthermore, necessary questions and replacement questions are set in the question bank. The necessary questions are targeted at the objects for which data collection is required, and the replacement questions are replaced with corresponding content according to the customer category, for example, replacing questions with titles, replacing questions with obvious gender distinctions, and replacing questions with age group differences.

[0026] Furthermore, after the questionnaire survey, the necessary questions ensure that the survey subjects can have basic feedback from customers on the collection objects, and by replacing the questions, targeted information collection can be carried out for different types of customers.

[0027] Furthermore, the question options of the questionnaire are set in singular numbers. In order to ensure the coverage of the options, they are divided into five, namely F1, F2, F3, F4, and F5. The default F3 option is a balanced option, that is, when the customer chooses the F3 option, it means that the customer neither supports nor opposes.

[0028] Furthermore, the data analysis in the sixth step, after the customer completes and submits the questionnaire, obtains the final customer feedback through the authenticity and classification of the questionnaire content.

[0029] Furthermore, Python is used to conduct the first screening and classification of the questionnaire survey customers, dividing the questionnaire survey into A1 and A2 categories.

[0030] Furthermore, the customer's age is confirmed through the identity information used by the customer to log in, and compared with the answers to the questionnaire options to determine whether there is a situation where cross-age group answers are selected that misleads the accuracy of data collection. For example, the questionnaire question will ask how old you are this year. If the range of answers deviates from the actual range, the questionnaire will be invalid.

[0031] Furthermore, the login status of the account used by the customer is used to determine whether there is any violation of the questionnaire. That is, the use of an uncommon account to conduct the questionnaire causes errors in data collection. Prioritizing customer login accounts within the range of D1-D3 can reduce the situation of repeated operations by a single person with multiple accounts.

[0032] Furthermore, based on the customer's daily WeChat payment situation, the transaction amount of the customer through WeChat payment is judged. For the questionnaire questions regarding WeChat consumption, according to the consumption ranges from E1 to E4, it can be determined whether the customer has false answers.

[0033] The beneficial effects of the present invention are as follows: 1. Compared with the extensive information collection of traditional questionnaire surveys, the data platform of this solution, in the development process, sets multiple classification criteria for the content of the questionnaire survey, and through setting up question banks, collects data for different classified customers, making the collected information more accurate. During the collection process, data processing and screening can be carried out. At the same time, the proportion of necessary questions is ensured, so that the collection of core data for the questionnaire objects is accurate and will not deviate. And through replacing questions, auxiliary collection of customer classification information feedback is carried out.

[0034] 2. As described in 1, after data collection, by setting a certain sample data, the number of customers is specified and multiple groups are run in parallel. At the same time, the answer options of the questionnaire are pre-set and coordinated with the questions, so that the scores of the options are obtained from high to low. When conducting data analysis and summary, through the data dispersion of each group of samples, the design rationality of the questionnaire objects and the accuracy of customer information feedback can be synchronously processed and collected. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0036] Figure 1 It is a data collection schematic diagram of the data collection platform of the present invention;

[0037] Figure 2 It is a schematic diagram of the question classification content of the present invention;

[0038] Figure 3 It is a schematic diagram of the questionnaire processing classification of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The following will describe in detail the embodiments of the technical solutions of the present invention with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, so they are only examples and cannot be used to limit the protection scope of the present invention.

[0040] It should be noted that unless otherwise specified, the technical terms or scientific terms used in this application should have the ordinary meanings understood by those skilled in the art to which the present invention belongs.

[0041] As Figures 1 - 3 shown, a data collection method based on mini programs has the following data collection steps:

[0042] First step: Requirement analysis. According to the target of the required data collection, clarify the content of data collection;

[0043] Second step: Locate the data type. Divide the area by geographical location, and then collect the feedback information of customers through the form of questionnaire surveys;

[0044] Third step: Design an interface with a comfortable user experience. Quickly build the interface through the UI component library of WeChat mini programs, such as WeUI;

[0045] i: Use the development framework of WeChat mini programs (such as WXML, WXSS, JavaScript, etc.) to build the application;

[0046] ii: Utilize the APIs of WeChat mini programs (such as wx.request, wx.getUserInfo, etc.) to implement data collection and interaction functions;

[0047] Fourth step: Content development. Design the login method. After logging in based on WeChat, there is no need for secondary identity authentication. The data collection of the mini program can enter the questionnaire interface through methods such as customer independent selection and advertisement pop-ups;

[0048] After collecting based on the questionnaire survey, use the local storage or cloud development service provided by WeChat mini programs to implement the data storage function, and upload the collected data to the server or cloud to achieve the data upload function;

[0049] i: Use the cloud development service of WeChat mini programs (such as cloud database, cloud functions, cloud storage, etc.) to simplify backend development;

[0050] ii: The cloud database is used to store user data and the collected information;

[0051] iii: Cloud functions are used to process data and execute business logic;

[0052] Fifth step: Data processing. Process and analyze the collected data on the server side or in the cloud;

[0053] i: Use the JSON format to transmit data;

[0054] ii: Use the HTTPS protocol to encrypt data transmission to ensure data security;

[0055] Sixth step: Data analysis. Use data analysis tools (such as the Pandas library in Python, R language, etc.) to perform data cleaning, statistical analysis, and visualization;

[0056] i: Use programming languages such as Python and R, and data analysis libraries (such as Pandas, NumPy, Matplotlib, etc.) for data processing and analysis;

[0057] ii: Use machine learning algorithms (such as classification, clustering, regression, etc.) for in-depth analysis;

[0058] Step 7: Security of data collection and protection of user privacy;

[0059] i: Use the user authentication and authorization mechanisms provided by WeChat (such as OAuth 2.0) to ensure the authenticity of the user's identity. User data can only be collected and used after obtaining the user's consent.

[0060] For the content development in the fourth step mentioned above, a question bank for the questionnaire can be set up, and corresponding questionnaire questions can be pushed according to the information of the customer's login.

[0061] Based on the customer's gender:

[0062] Male - A1, Female - A2;

[0063] Based on the customer's age:

[0064] B1, Under 18 years old; B2, 18 - 30 years old; B3, 31 - 40 years old; B4, 41 - 50 years old; B5, 50 - 60 years old; B6, Over 60 years old;

[0065] Based on the online duration on WeChat:

[0066] D1, Use daily; D2, Use within three days; D3, Use within a week; D4, Use within a month; D5, Rarely use;

[0067] Based on the transaction records on WeChat:

[0068] Calculated from the 20th of last month to the 20th of the next month: E1, Below 200 yuan; E2, 200 - 1000 yuan; E3, 1000 - 10000 yuan; E4, Over 10000 yuan;

[0069] Necessary questions and replacement questions are set in the question bank. Necessary questions are for the objects of the required data collection, and replacement questions are for corresponding content replacement according to the customer category. For example, replacement of questions about appellations, questions with obvious gender distinctions, and questions with age group differences;

[0070] The total number of questions pushed by the question bank is Cn, the number of necessary questions is Cm, and the number of replacement questions is Cx:

[0071] Cm / Cn ≥ 70%;

[0072] C(1、2、3、....、n)

[0073] After the questionnaire survey, the necessary questions ensure that the respondents can have the basic feedback from customers on the collected objects. By replacing the questions, targeted information collection is carried out for different types of customers.

[0074] The question options in the questionnaire survey are set to be odd numbers. To ensure the coverage of the options, they are divided into five, namely F1, F2, F3, F4, and F5. By default, the F3 option is the balanced option, that is, when a customer selects the F3 option, it means that the customer neither supports nor opposes.

[0075] In the data platform of this solution, in the development process, multiple classification criteria are set for the content of the questionnaire survey, and by setting up a question bank, data is collected for different classified customers, making the collected information more accurate. During the collection process, data processing and screening can be carried out. At the same time, the proportion of necessary questions is ensured, so that the core data collection of the questionnaire respondents is accurate and will not deviate. And by replacing the questions, auxiliary collection of customer classification information feedback is carried out.

[0076] For the data analysis in the sixth step, after the customer finishes answering the questionnaire and submits it, the final customer feedback is obtained through the authenticity and inductive classification of the questionnaire content.

[0077] I. Through Python, the customers of the questionnaire survey are screened and classified for the first time, and the questionnaire survey is divided into category A1 and category A2.

[0078] II. Through the identity information used by the customer to log in, the age of the customer is confirmed, and according to the option answers of the questionnaire survey, a comparison is made to determine whether there is a situation where misleading data collection accuracy occurs due to cross-age selection of answers. For example, the questionnaire survey question will ask how old the customer is this year. If the range of the answered answer deviates from the actual range, then this questionnaire survey is invalidated.

[0079] III. Through the login situation of the customer's account, it is judged whether there is a situation of violating the questionnaire survey, that is, using an infrequently used account to answer the questionnaire, resulting in data collection errors. Prioritizing the customer login accounts within the range of D1 - D3 can reduce the situation of a single person operating multiple accounts repeatedly.

[0080] IV. Through the customer's daily WeChat payment situation, the WeChat payment turnover amount of the customer is judged. For the questionnaire questions about WeChat consumption, according to the consumption range from E1 to E4, it can be judged whether the customer has false answering situations.

[0081] The number of people in the questionnaire survey for a single group does not exceed 50, preferably 30, which are respectively marked as G1, G2, G3, ..., G30, and the number of sample groups is set to 10 groups, and the grouping is successively H1, H2, H3, ..., H10;

[0082] The question options are F1 - F5. F1 is set as the most ideal answer, and so on, with the rating decreasing. F3 is the average option. When processing the options, the customer selects F1 as 10 points, F2 as 8 points, F3 as 6 points, F4 as 4 points, and F5 as 2 points;

[0083] The discrete data of the questionnaire survey scores of a single group of customers:

[0084] Take the average value:

[0085]

[0086] G is the number of people in a single group of samples, Fi is the score of a single customer's questionnaire, is the average score;

[0087] After obtaining the average value, calculate the standard deviation:

[0088]

[0089] Through the value of σ, compare the single - group sample with the set standard value of the questionnaire object;

[0090] Also, through the setting of 10 groups of samples, set the evaluation interval for the questionnaire object. Define the interval as X(X1, X Z );

[0091] In the grouping of H1 - H10, if the number within the X interval exceeds 6 groups and includes 6 groups, then the questionnaire object meets the design standard. For the questionnaire content outside the X interval, under the conditions of meeting I, II, III, and IV, conduct a key analysis of the questionnaire outside the X interval.

[0092] After data collection, by setting a certain sample data, the number of customers is specified and multiple groups are run in parallel. At the same time, the answer options of the questionnaire are pre - set, and combined with the questions, the scores of the options are obtained from high to low. When conducting data analysis and summary, through the data dispersion of each group of samples, the design rationality of the questionnaire object and the accuracy of customer information feedback can be processed and collected synchronously.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and the description of the present invention.

Claims

1. A data collection method based on a small program, characterized in that: The steps for data collection are as follows: Step 1: Demand analysis: clarify the content of data collection according to the target of data collection; Step 2: Locate the data type, divide the regions by geographical location, and then collect customer feedback information through questionnaire surveys; Step 3: Design an interface that is comfortable for the user experience, using the UI component library of WeChat Mini Programs; i: Use the WeChat applet development framework to build applications; ii: Use the API of WeChat applet to realize data collection and interaction functions; Step 4: Content development and login design. After logging in through WeChat, no secondary identity authentication is required. The data collection of the mini program can be done through customer self-selection and ad pop-up window to enter the questionnaire interface; After collecting data based on the questionnaire survey, use the local storage or cloud development service provided by the WeChat applet to realize the data storage function, and upload the collected data to the server or cloud to realize the data upload function; i: Use WeChat Mini Program’s cloud development service to simplify backend development; ii: The cloud database is used to store user data and collected information; iii: Cloud functions are used to process data and execute business logic; Step 5: Data processing: Process and analyze the collected data on the server or cloud; i: Use JSON format to transmit data; ii: Use HTTPS protocol to encrypt data transmission to ensure data security; Step 6: Data analysis, using data analysis tools for data cleaning, statistical analysis and visualization; i: Use Python, R programming languages ​​and data analysis libraries to perform data processing and analysis; ii: Use machine learning algorithms to perform in-depth analysis; Step 7: Collect data security and protect user privacy; i: Use the user authentication and authorization mechanism provided by WeChat to ensure the authenticity of the user's identity. Only after obtaining the user's consent can the user's data be collected and used.

2. According to claim 1, a data collection method based on a small program is characterized in that: The content development in the fourth step may set up a question bank for the questionnaire survey and push corresponding questionnaire questions based on the customer's login information.

3. The data collection method based on a small program according to claim 2 is characterized in that: The question bank includes necessary questions and replacement questions. The necessary questions are targeted at the objects for which data collection is required, and the replacement questions are replaced with corresponding content according to the customer category. The replacement questions include replacement of titles, replacement of questions with obvious gender distinction, and replacement of questions with age group differences.

4. The data collection method based on a small program according to claim 3 is characterized in that: The necessary questions ensure that the survey subjects can obtain basic feedback from customers on the collection objects after the questionnaire survey. By replacing the questions, targeted information collection can be carried out for different types of customers.

5. The data collection method based on a small program according to claim 4 is characterized in that: The question options of the questionnaire are set in singular numbers. In order to ensure the coverage of the options, they are divided into five, namely F1, F2, F3, F4, and F5. The default F3 option is a balanced option, that is, when the customer chooses the F3 option, it means that the customer neither supports nor opposes.

6. The data collection method based on a small program according to claim 5, characterized in that: The data analysis in the sixth step is to obtain the final customer feedback through the authenticity and classification of the questionnaire content after the customer completes and submits the questionnaire.

7. The data collection method based on a small program according to claim 6 is characterized in that: Through Python, the customers of the questionnaire are screened and classified for the first time, and the questionnaires are divided into A1 and A2 categories.

8. The data collection method based on a small program according to claim 7 is characterized in that: The customer's age is confirmed through the identity information used by the customer to log in, and compared with the answers to the questionnaire options to determine whether there is a situation where cross-age group selection answers mislead the accuracy of data collection.

9. The data collection method based on a small program according to claim 8, characterized in that: The method of judging whether there is any violation of the questionnaire by the login status of the customer's account, that is, using an uncommon account to conduct the questionnaire, resulting in errors in data collection, and giving priority to customer login accounts within the range of D1-D3, can reduce the situation of repeated operations by a single person with multiple accounts.

10. A data collection method based on a small program according to claim 9, characterized in that: The amount of payment made by a customer through WeChat can be determined by the customer's daily payment through WeChat. For the questionnaire questions on WeChat consumption, it can be determined whether the customer has made false answers based on the consumption range of E1 to E4.

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