Electronic check problem option sequence design optimization method and device and storage medium

Abstract

The invention relates to an electronic check question option sequence design optimization method and device and a storage medium, and the method comprises the steps: completing the design of a questionnaire, and carrying out the logic grouping of questions according to an actual condition; obtaining the click rate of questions and question options, and calculating the subsequent click rate of the question options in the question group; searching and connecting the two questions, wherein the questions with less than n question options are merged; and searching the problem options with huge click rate for optimization. According to the method, the change of the overall click rate / operation frequency of the questionnaire is calculated by adjusting the position of the question option, visual reference is provided for a designer from the point of click rate change, the designer is assisted to quickly lock the optimal question option item design, and the scientificity and rationality of questionnaire design are improved.

Description

Technical Field

[0001] The present invention relates to the field of electronic verification, and more particularly, to an optimization method, device, and storage medium for the order design of electronic verification problem options. Background Art

[0002] In the design of electronic questionnaires, it is crucial to reasonably set problem options. It can not only effectively shorten the time for filling out the questionnaire but also significantly improve the answering experience of the respondents. Currently, questionnaire design mainly relies on manual judgment based on experience. However, in existing design methods, it is not intuitive for designers to judge whether the questionnaire option design is reasonable, resulting in situations such as too long answering time and respondents' resistance due to poor option settings, thereby affecting the quality and recovery rate of questionnaire data. Summary of the Invention

[0003] The purpose of the present invention is to provide an optimization method, device, and storage medium for the order design of electronic verification problem options to solve the problem that existing electronic questionnaire design cannot intuitively allow designers to judge whether the questionnaire option design is reasonable, affecting the quality and recovery rate of questionnaire data.

[0004] To achieve the above object, the present invention adopts the following technical solutions: An optimization method for the order design of electronic verification problem options includes the following steps: Complete the design of the questionnaire and logically group the questions according to the actual situation; Obtain the click-through rate of questions and question options, and calculate the subsequent click-through rate of question options within the current question group; Find and merge questions with fewer than n question options when connecting two questions; Find and optimize question options with a large click-through rate.

[0005] In one embodiment, the logical grouping includes: Group the questions based on language description; Group the questions based on the actual operation scenario.

[0006] In one embodiment, the calculation of the subsequent click-through rate of question options within the current question group includes: Estimate the click-through rate of each question option in the original questionnaire through pilot samples or historical data; Calculate the contribution of each option within the question group.

[0007] In one embodiment, the calculation of the contribution of each option within the question group includes: Calculate the click-through rate of the option itself ; Calculate the click-through rate from the previous question to option O , where L is the level to which the question to which option O belongs belongs; Calculate the click-through rate of the questions following option O , where q is the related question following option O; Calculate the total contribution of option O in the entire question group .

[0008] In one embodiment, in the search for connecting two questions, questions with fewer than n question options are merged, including: Promote all options under one question to the previous question for selection.

[0009] In one embodiment, the optimization of the question option with a huge click-through rate is as follows, including: Loop through each question in the question group; Traverse each question in the question group along the question path of the question group; Mark the question options at the bottom layer whose total click-through rate exceeds the threshold; Traverse all questions along the question path starting from the first question; If the number of question options of the current question has not reached n, start optimizing the question options for the current question; Traverse the marked question options related to the current question in sequence of level and serial number; Calculate the change in click-through rate when promoting a question option to the current question; Find the optimal adjustment plan for the current question; Complete the option filling and optimization of one question, and loop to the next question; When the optimization of the entire group of questions is completed, recalculate the total click-through rate of the question group; Loop through the calculation and optimization of all question groups. After all are completed, sum up the new click-through rates of all question groups.

[0010] In one embodiment, the calculation of the change in click-through rate when promoting a question option to the current question includes: Calculate the total contribution value of the adjusted question option ; Recalculate the difference in the total contribution value of the adjusted question option : , where, is the click-through rate of the option itself, L is the level to which the question to which option O belongs belongs, q is the related question following option O, and j is the level at which question option O is located. Then the level crossed when adjusting question O to question Q is .

[0011] In one of the embodiments, the searching for the optimal adjustment solution for the current problem includes: Calculating the contribution value differences for all problem options, and sorting them from largest to smallest; Finding the problem option corresponding to the maximum value of the contribution value difference, and modifying its attributed problem and level to problem Q and the level where problem Q is located; Correcting the click-through rates of the problem options for the new and old position paths: subtracting ; Canceling the to-be-optimized mark of the adjusted problem option, and it will no longer participate in subsequent loop calculations; If the number of options for the current problem is less than the maximum value, the next problem item can be modified continuously, and the above steps can be repeated.

[0012] An electronic verification problem option sequence design optimization device includes: A problem logic grouping module, configured to perform logic grouping according to the actual situation after the questionnaire design is completed; A problem option click-through rate calculation module, configured to obtain the click-through rates of problems and problem options, and calculate the subsequent click-through rates of problem options within this problem group; A problem merging module, configured to find problems with less than n problem options among two consecutive problems for merging; A problem option optimization module, configured to find problem options with a huge click-through rate for optimization.

[0013] In one of the embodiments, when the instruction is executed by the processor, the steps of the above method are implemented.

[0014] From the above technical solutions, it can be seen that the present invention has at least the following advantages and positive effects compared with the prior art: An electronic verification problem option sequence design optimization method, device, and storage medium according to an embodiment of the present invention calculate the change in the overall click-through rate / operation times of the questionnaire by adjusting the positions of problem options, and give designers an intuitive reference from the perspective of click-through rate changes, helping designers quickly lock in the optimal problem option entry design and improving the scientificity and rationality of questionnaire design. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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.

[0016] Figure 1 It is a flowchart of an electronic verification problem option sequence design optimization method in an embodiment of the present invention; Figure 2Schematic diagram of optimizing the process of finding problem options with extremely high click-through rates in step S4 of the present invention; Figure 3 Schematic diagram of the process of finding the optimal adjustment plan for the current problem in step S408 of the present invention; Figure 4 Schematic diagram of the structure of the device for optimizing the design of the order of electronic verification problem options in the present invention. Detailed implementation manners

[0017] In order to more clearly explain the purpose, technical solution and advantages of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The exemplary embodiments can be implemented in various forms and should not be construed as limited to the examples described herein; on the contrary, providing these embodiments makes the present invention more comprehensive and complete, and conveys the concept of the exemplary embodiments to those skilled in the art in an all-round way.

[0018] In addition, the described features, structures or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to give a full understanding of the embodiments of the present invention. However, those skilled in the art will realize that the technical solutions of the present invention can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, well-known methods, devices, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present invention.

[0019] The block diagrams shown in the accompanying drawings are only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0020] The flowcharts shown in the accompanying drawings are only illustrative and do not necessarily include all the contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined. Therefore, the actual execution order may change according to the actual situation.

[0021] The present invention will be described in detail below with reference to specific embodiments.

[0022] Embodiment 1 The present invention provides a method for optimizing the design of the order of electronic verification problem options. Refer to Figure 1 , Figure 1This is a schematic flow chart of the optimization method for the order design of electronic verification problem options in the present invention.

[0023] It can be seen from Figure 1 that an optimization method for the order design of electronic verification problem phenomena includes the following steps: S1. Complete the design of the questionnaire and logically group the questions according to the actual situation.

[0024] Logical grouping confines the questions and their option constraints within a logical scope, and the optimization and adjustment of question options cannot exceed the scope of this group. Restricting the optimization access within this group is a means to ensure the rationality of the optimized questions.

[0025] Logical grouping includes grouping questions based on language description and grouping questions based on actual operation scenarios.

[0026] By grouping questions based on language description, since two completely unrelated questions cannot be merged, first, group the questions based on the language description of the questions, and only questions of the same category can be merged into one category. For example, the question about the hygiene of the restaurant storefront and the question about the sales of dishes cannot be grouped together, and there is no way to merge two completely unrelated questions.

[0027] By grouping questions based on actual operation scenarios, such questions mostly appear in the verification questionnaire. The verification personnel need to perform different actions at different locations and different times. If the time and space of the questionnaire questions are misaligned, it will cause trouble for the verification personnel to record information. For example: Question 1: Verification of the address situation: A: The address is reachable B: The address is incomplete C: The address has been demolished Question 2: Business operation situation at the registered address of the enterprise: A: Verify that the enterprise operates here B: Other enterprises operate here C: No enterprise operates here If the verification object is an enterprise operating in an office building, then these two questions are two logical groups because the first question is verified outside the office building and the second question is verified after going upstairs. The two questions are not verified in the same place and cannot be verified at the same time node. It cannot be required that the verification personnel do not perform operations when arriving at the location and then answer both types of questions after going upstairs. If the number of verification tasks is huge, the probability of registration errors will increase.

[0028] However, if the verification object is a factory or mine enterprise, then the business situation of the enterprise can be judged when arriving at the place of business. These two issues can be registered at the same location, and the above two issues can be grouped into one group of issues. Therefore, it is necessary to group the issues according to the actual operation scenarios of the issues.

[0029] S2. Obtain the click-through rates of the questions and question options, and calculate the subsequent click-through rates of the question options within this question group.

[0030] Since the optimized design of the question options is already at the end of the entire questionnaire design, the logical rationality of the question items has been designed. The premise for optimizing the question options is that it cannot affect the overall logic. Therefore, the optimization of the question options can only be adjusted upward along the existing question path, and a certain question option cannot be adjusted to other question branches. Moreover, downward adjustment will increase the click-through rate. Therefore, the question options can only be adjusted longitudinally upward along the question path and cannot be adjusted horizontally across question paths.

[0031] Therefore, the optimization method focused on in this solution is to adjust the question options upward along the question path of the original questionnaire, calculate the impact on the overall click-through rate by adjusting the positions of the question options, and find the adjustable and optimized ways and methods for each question and question option on the question path. Therefore, it is necessary to first obtain the questionnaire or question group to be optimized and relevant data, including the click-through rates of each question and question option, and calculate the subsequent question click-through rates corresponding to each question option: 1. Estimate and obtain in advance the click-through rates of each question option in the original questionnaire through pilot samples or historical data; 2. Calculate the contribution of a single option in the question group: Let option O be at the level L of the question it belongs to, then: (1) Calculate the click-through rate of the option itself ; (2) Calculate the click-through rate from the previous question to option O ; (3) Calculate the subsequent question click-through rate of option O , where q is the subsequent associated question of option O; Then the total contribution of option O in the entire question group is: .

[0032] S3. Search for questions with fewer than n question options when connecting two questions and merge them.

[0033] When the number of question options in two consecutive questions is less than a certain value (usually considering the device used by the respondent to answer the questionnaire. For example, when the device used is a mobile phone, generally to control split-screen on the mobile phone, the number of question options under one question is controlled within 8; when the device used is a computer, generally to reduce the respondent's aversion, the number of question options under one question is controlled within 15), all the options under one question are promoted to the previous question for selection, which has no impact on the overall design logic of the questionnaire. For example: When all the options are moved to the previous question the reduction in click volume is . For example: Question 1: Does the enterprise operate at the address? A: Yes (click to enter the research session) B: No (click to jump to Question 2) Question 2: What is the operating situation at the address? A: Other enterprises operate at the address B: No enterprise operates at the address C: The address is incorrect Merge all of Question 2 into Question 1: Question 1: Does the enterprise operate at the address? A: Yes No: B: Other enterprises operate at this address C: No enterprise operates at this address D: The address is incorrect Merging Question 2 into Question 1, two questions are completed with one question. For the click volume, only Question 2 is missing, and the reduction is the click volume of Question 2 itself, that is, the reduction is the above-mentioned .

[0034] This adjustment method is the one with the least difficulty and the most common, because it is an adjustment of all the question options and has basically no impact on the overall logic of the questionnaire.

[0035] S4. Find and optimize the question options with a huge click volume.

[0036] Because the two factors affecting the total click volume are: one is the click volume of the question option itself, and the other is the question association level. The more levels there are, the greater the click linkage volume. Therefore, the click volume in the subsequent description is the sum of the click volume of the question option itself and the expected click volume of the subsequent questions, not the click volume of a single question option or a single question.

[0037] Refer to Figure 2 , Figure 2It is a schematic flow chart for optimizing the problem options with extremely high click-through rates in step S4 of the present invention.

[0038] Optimizing the problem options with extremely high click-through rates specifically includes the following steps: S401. Loop through each question in the question group; S402. Traverse each question in the question group along the question path of the question group; S403. Mark the problem options at the bottom layer whose total click-through rate exceeds the threshold; Since the optimization method of this solution is to increase the level of the problem options, when the bottom-layer problem options are promoted to the upper layer, the corresponding problem options in the original upper layer will also become invalid. Therefore, only the bottom-layer problem options need to be found. The click-through rate threshold is generally calculated as a fixed value according to the proportion of the total click-through rate of the questionnaire for screening. According to experience, a proportion of about 2% can be taken. For example, if the expected total click-through rate of a survey is 1 million, options with a click-through rate of more than 20,000 are screened out.

[0039] S404. Traverse all questions along the question path starting from the first question; S405. If for the current question Q, the number of problem options at the level where question Q is located has not reached n, start optimizing the options for the current question; S406. Traverse the marked problem options associated with the current question subsequently. The loop order is level and serial number, which can ensure traversing from the top-level question downwards; S407. Calculate the change in click-through rate when promoting a problem option to the current question; From the above total contribution formula of the problem options: Recalculate the difference in the total contribution value of the adjusted problem options: Let the level where the problem option O is located be j. Then the number of levels spanned when adjusting problem O to question Q is .

[0040] Then the contribution difference of the adjusted problem option O:

[0041] , where is the click-through rate of the option itself, L is the level to which the question where option O is located belongs, and q is the question associated with option O subsequently.

[0042] S408. Find the optimal adjustment plan for the current question; Refer to Figure 3 , Figure 3 It is a schematic flow chart for finding the optimal adjustment plan for the current question in step S408 of the present invention.

[0043] S4081. Calculate the contribution value differences for all question options and sort them from largest to smallest.

[0044] S4082. Find the question option corresponding to the maximum contribution value difference, and modify its belonging question and level to question Q and the level where question Q is located.

[0045] S4083. Correct the click-through rates of the question options for the new and old position paths: Subtract . For example: Question group: Question Q1: Option O1, Option O2 Question Q2: Option O21, Option O22 Question Q3: Option O31, Option O32 Question Q4: Option O41, Option O42 The path of Option O42 is O1 - O22 - O32 - O42 After modifying the question to which Option O42 belongs to Q1, the new question group becomes: Question Q1: Option O1, Option O2, Option O42 Question Q2: Option O21, Option O22 Question Q3: Option O31, Option O32 Question Q4: Option O41 At this time, the click-through rates of question options O1, O22, and O32 need to be subtracted by the click-through rate of Option O42 itself.

[0046] S4084. Cancel the to-be-optimized mark of the adjusted question option and no longer participate in subsequent loop calculations.

[0047] S4085. If the number of options for the current question is still less than the maximum value, the next question item can be continued to be modified, and the above steps are repeated.

[0048] S409. Complete the option filling and optimization for one question, and loop to the next question; S410. When the optimization of the entire group of questions is completed, recalculate the total click-through rate of this question group; S411. Loop to calculate and optimize all question groups. After all are completed, the sum of the new click-through rates of all question groups is the expected total of this questionnaire.

[0049] Illustrate with an example: Suppose an enterprise verification questionnaire: Question A: Address information status Option A1: Address is correct Option A2: Address cannot be found Option A3: Address is unknown or missing Question B: Verify whether the enterprise operates locally Option B1: Yes Option B2: No Question C: Business operation of other enterprises at the address Option C1: Other enterprises operate here Option C2: No enterprise operates here Question D: Abnormal status of address information Option D1: The address has been demolished Option D2: The specified unit cannot be found Option D3: The specified floor cannot be found Question E: Information of other enterprises Option E1: Other enterprises unrelated to the verified enterprise Option E2: Financial agency company Option E3: The enterprise cannot be found in the public office area Question F: Number of on-site office workers Question G: Area of the office space Optimize the above questions according to an electronic verification question option sequence design and optimization method of the present invention to reduce the number of clicks.

[0050] S1. Complete the design of the questionnaire and logically group the questions according to the actual situation; Based on the above Questions A to G, it is obtained that Questions A to E are questions for verifying the enterprise address, and Questions F and G are the specific business conditions after the verified enterprise is found. Therefore, Questions A to E are divided into the first question group, and Questions F and G are divided into the second question group. The following examples will be optimized with the first question group as an example.

[0051] S2. Obtain the click-through rates of the questions and their options, and calculate the subsequent click-through rates of the question options within this question group; (The total click-through rate is 64)

[0052] S3. Find the questions with fewer than n question options when connecting two questions and merge them; Assume that the maximum number of question options in a question is limited to 4, then Questions B and C can be merged, and the total click-through rate after merging is 54;

[0053] S4. Find the question options with extremely high click-through rates and optimize them.

[0054] 1. Mark the question items exceeding the threshold; Assume the threshold is set to 10. Then both option B1 and option C1 meet the requirements. Given that question A has 3 question options and it is stipulated that each question can have 4 question options, therefore, one more question option can be set for question A.

[0055] 2. Adjust options B1 and C1 for question A and calculate the contribution difference after adjustment; ,

[0056] Because , so option C1 of the question is preferentially adjusted.

[0057] 3. Recalculate the click-through rate after adjustment. The total click-through rate is 48;

[0058] In summary, after the above adjustments, the total click-through rate has decreased from 64 to 48, a 25% reduction in the number of clicks. That is to say, 25% of the click work of the operators can be reduced after optimization.

[0059] Embodiment 2 Reference Figure 4 , the present invention provides an optimization device for the design of the order of electronic verification question options, Figure 4 which is a schematic structural diagram of the optimization device for the design of the order of electronic verification question options of the present invention.

[0060] From Figure 4 , it can be seen that an optimization device for the design of the order of electronic verification question options includes: a question logic grouping module 210, a question option click-through rate calculation module 220, a question merging module 230, and a question option optimization module 240.

[0061] Among them, the question logic grouping module 210 is used to perform logical grouping according to the actual situation after the questionnaire design is completed.

[0062] The question option click-through rate calculation module 220 is used to obtain the click-through rate of questions and question options and calculate the subsequent click-through rate of question options within this question group.

[0063] The question merging module 230 is used to find questions with fewer than n question options among two consecutive questions and merge them.

[0064] The question option optimization module 240 is used to find question options with a large click-through rate for optimization.

[0065] Embodiment 3 Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in most cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, disk, optical disc) and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server or network device, etc.) to execute the method described in the present invention.

[0066] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present invention. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include known common knowledge or conventional technical means in the technical field not disclosed in the present invention. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present invention are pointed out by the claims. It should be understood that the present invention is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A method for optimizing the order of electronic verification question options, characterized in that: The following steps are involved: Complete the design of the questionnaire and logically group the questions according to the actual situation; Obtain the number of clicks on questions and question options, and calculate the number of subsequent clicks on question options within the same question group; Find the questions that have less than n options among the two connected questions and merge them; Find options for questions that have a lot of traffic and optimize them.

2. The method for optimizing the sequence design of electronic verification question options according to claim 1, characterized in that: The logical groupings include: Group questions based on their language descriptions; Questions are grouped based on real-world operational scenarios.

3. The method for optimizing the sequence design of electronic verification question options according to claim 1, characterized in that: The calculation question option subsequent clicks within this question group include: Obtain the number of clicks on each question option in the original questionnaire through pilot samples or historical data estimates; Calculate the contribution of each option in the problem group.

4. The method for optimizing the sequence design of electronic verification question options according to claim 3 is characterized in that: The calculation of the contribution of each option in the problem group includes: Calculate the number of clicks on the option itself ; Calculate the number of clicks from the previous question to option O , where L is the level to which the question of option O belongs; Calculate Option O follow-up question clicks , where q is the follow-up related question of option O; Calculate the total contribution of Option O to the entire problem set .

5. The method for optimizing the sequence design of electronic verification question options according to claim 1, characterized in that: The searching and merging of the two questions with less than n options includes: Promote all options under a question to the previous question for selection.

6. The method for optimizing the sequence design of electronic verification question options according to claim 1, characterized in that: The Find Highly Trafficked Questions option is optimized to include: Cycle through each question in the group; Traverse each problem in the problem group along the problem path of the problem group; Mark the question option whose total clicks exceed the threshold and is at the bottom; Traverse all questions along the question path starting from the first question; If the number of question options for the current question has not reached n, start optimizing the question options for the current question; Traverse the marked question options that are subsequently associated with the current question, in the order of level and sequence number; Calculate the change in clicks that would elevate a question option to the current question; Find the best solution to the current problem; Complete the optimization of options for a question and loop to the next question; When the optimization of the entire group of questions is completed, the total number of clicks for the group of questions is recalculated; Calculate and optimize all question groups in a loop. When all are completed, add up the new clicks for all question groups.

7. The method for optimizing the sequence design of electronic verification question options according to claim 6, characterized in that: The calculation is to elevate a question option to the change in click volume of the current question, including: Calculate the total contribution of the adjusted question options ; Recalculate the total contribution value difference of the adjusted question options : ,in, is the number of clicks on the option itself, L is the level of the question where option O belongs, q is the subsequent related question of option O, j is the level where question option O belongs, then the level that is crossed when question O is adjusted to question Q is .

8. The method for optimizing the sequence design of electronic verification question options according to claim 6, characterized in that: The method of finding the optimal adjustment solution for the current problem includes: Calculate the contribution value difference of all question options and sort them from large to small; Find the question option corresponding to the maximum value of the contribution value difference, and modify its belonging question and level to question Q and the level where question Q is located; Correct the click volume of the new and old location path question options: the click volume of all path question options is subtracted ; Cancel the optimization mark of the adjusted problem option, and it will no longer participate in the subsequent cycle calculation; If the number of options for the current question is less than the maximum, you can continue to modify the next question item and repeat the above steps.

9. An electronic verification question option sequence design optimization device, characterized in that: include: The question logic grouping module is used to perform logical grouping according to the actual situation after the questionnaire design is completed; The question option click volume calculation module is used to obtain the click volume of the question and question options, and calculate the subsequent click volume of the question options in the question group; The question merging module is used to find two consecutive questions with less than n options and merge them; The question option optimization module is used to find question options with huge click volumes for optimization.

10. A storage medium having instructions stored thereon, characterized in that: When the instructions are executed by a processor, the steps of the method described in any one of claims 1 to 8 are implemented.

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