Intelligent funnel diagram generation method

Abstract

The invention relates to an intelligent funnel diagram generation method, and relates to the field of data visualization, and the method comprises the steps: collecting the number of users of N data types, the N data types having a progressive relationship, and N being a positive integer; according to the number of the N users, N-1 conversion rate parameters are obtained through calculation; according to the number of the N users and the N-1 conversion rate parameters, combining historical record data, and calculating to obtain N number generation parameters and N-1 conversion rate generation parameters; and according to the N number generation parameters and the N-1 conversion rate generation parameters, configuring N pieces of funnel diagram generation information, and generating a funnel diagram. According to the method, the problems that the amount of information contained in the funnel diagram is small, and the data visualization degree is not high can be solved.

Description

Technical Field

[0001] This application relates to the field of data visualization, and particularly to a method for intelligently generating a funnel chart. Background Art

[0002] A funnel chart is a data visualization tool used to display the hierarchical relationship and changing trend of data. However, the current funnel chart can only display the number of users or the conversion rate, and cannot be associated with historical data. Therefore, the information contained is less, and the degree of data visualization is not high. Summary of the Invention

[0003] This application provides a method for intelligently generating a funnel chart, aiming to solve the problems of less information and low visualization degree in traditional funnel charts.

[0004] The technical solution of the present invention to solve the above technical problems is as follows: The present invention provides a method for intelligently generating a funnel chart, and the method includes: Collect the number of users of N data types, where the N data types have a progressive relationship, and N is a positive integer; Calculate N - 1 conversion rate parameters based on the number of N users; Calculate N quantity generation parameters and N - 1 conversion rate generation parameters based on the number of N users, N - 1 conversion rate parameters, and combined with historical record data; Configure N funnel chart generation information according to the N quantity generation parameters and N - 1 conversion rate generation parameters, and generate a funnel chart.

[0005] Among them, the calculating N - 1 conversion rate parameters based on the number of N users includes: Calculate the ratio of the number of users of the Nth data type to the number of users of the (N - 1)th data type according to the progressive relationship to obtain the Nth conversion rate parameter; Continue to calculate to obtain N - 1 conversion rate parameters.

[0006] Among them, the calculating N quantity generation parameters and N - 1 conversion rate generation parameters based on the number of N users, N - 1 conversion rate parameters, and combined with historical record data includes: Collect N historical user quantities and N - 1 historical conversion rates according to the record data within the historical time; Calculate N quantity generation parameters based on the number of N users and the number of N historical users; Calculate N conversion rate generation parameters based on the N - 1 conversion rate parameters and the N - 1 historical conversion rates.

[0007] Among them, collecting N historical user numbers and N - 1 historical conversion rates according to the recorded data within the historical time includes: According to the recorded data within the historical time, collecting all user numbers and conversion rate parameters of the N data types within the preset historical time range, obtaining N sets of historical user numbers and N - 1 sets of historical conversion rates; Calculating the means of the N sets of historical user numbers and N - 1 sets of historical conversion rates respectively to obtain N historical user numbers and N - 1 historical conversion rates.

[0008] Among them, calculating N quantity generation parameters according to the N user numbers and N historical user numbers includes: Combining the N user numbers and N historical user numbers according to the N data types; Calculating the ratio of each user number to the corresponding historical user number as the quantity generation parameter, and calculating to obtain N quantity generation parameters.

[0009] Among them, configuring N funnel chart generation information according to the N quantity generation parameters and N - 1 conversion rate generation parameters to generate a funnel chart includes: Generating N quantity identification coefficients and N - 1 conversion rate identification coefficients according to the N quantity generation parameters and N - 1 conversion rate generation parameters; Generating a basic funnel chart, where the basic funnel chart includes N funnel chart regions corresponding to the N data types; Identifying the N funnel chart regions according to the N quantity identification coefficients and N - 1 conversion rate identification coefficients according to the N quantity generation parameters and N - 1 conversion rate generation parameters to obtain a funnel chart.

[0010] Among them, generating N quantity identification coefficients and N - 1 conversion rate identification coefficients according to the N quantity generation parameters and N - 1 conversion rate generation parameters includes: Calculating the ratio of the quantity generation parameter of the Nth data type to the sum of the quantity generation parameter and the conversion rate generation parameter respectively to obtain the Nth quantity identification coefficient and the Nth conversion rate identification coefficient, where the identification coefficient includes the proportion of the identified area; Continuing to calculate N quantity identification coefficients and N - 1 conversion rate identification coefficients according to the N quantity generation parameters and N - 1 conversion rate generation parameters, where the quantity identification coefficient of the first quantity type is 1 and the conversion rate identification coefficient is 0.

[0011] In the present invention, according to the number of N users and N - 1 conversion rate parameters, combined with historical record data, N quantity generation parameters and N - 1 conversion rate generation parameters are calculated and obtained. Historical data is associated in the parameter generation of the funnel chart to increase the information content of the funnel chart; then, according to the N quantity generation parameters and N - 1 conversion rate generation parameters, N funnel chart generation information is configured to generate a funnel chart, improving the visualization degree of the funnel chart.

[0012] In summary, the present invention achieves the effects of increasing the information content contained in the funnel chart and improving the visualization degree of the funnel chart. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of the steps of an intelligent generation method for a funnel chart provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present application.

[0015] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined.

[0016] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or having more advantages than other embodiments. In order for any person skilled in the art to implement and use the present invention, the following description is given. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope that conforms to the principles and features disclosed in the present invention.

[0017] The following will be further described in detail with reference to the attached Figure 1 , to further illustrate the present application.

[0018] Example 1, as Figure 1 shown, the embodiment of the present invention provides a method for intelligently generating a funnel chart, which specifically includes the following steps: S100 Collect the number of users of N data types, where the N data types have a progressive relationship, and N is a positive integer; S200 Calculate N - 1 conversion rate parameters based on the number of N users; S300 Calculate N quantity generation parameters and N - 1 conversion rate generation parameters based on the number of N users and N - 1 conversion rate parameters, in combination with historical record data; S400 Configure N funnel chart generation information according to the N quantity generation parameters and N - 1 conversion rate generation parameters, and generate a funnel chart.

[0019] Among them, the specific steps of S100 are: To implement the method for intelligently generating the funnel chart described in this embodiment, it is first necessary to implement step S100, that is, to collect the number of users of N data types. The N data types are different data levels with a progressive relationship. And N is a positive integer.

[0020] Exemplarily, in the scenario of online shopping, there can be the number of users of 3 data types. Among them, the number of users of the first data type can be the number of users who browse a certain commodity interface; the number of users of the second data type can be the number of users who have submitted an order; the number of users of the third data type can be the number of users who have actually made a payment. Obviously, in this example, N = 3.

[0021] Further, in step S200 of the present invention, calculating N - 1 conversion rate parameters based on the number of N users includes: According to the progressive relationship, calculate the ratio of the number of users of the Nth data type to the number of users of the (N - 1)th data type to obtain the Nth conversion rate parameter; Continue to calculate to obtain N - 1 conversion rate parameters.

[0022] In the embodiment of the present application, the conversion rate parameter can be the ratio of the number of users of the subsequent data type with a progressive relationship to the number of users of the previous data type. For example, in the online shopping scenario mentioned in S100, the first conversion rate parameter is the ratio of the number of users who have submitted an order to the number of users who browse a certain commodity interface, and the second conversion rate parameter is the ratio of the number of users who have actually made a payment to the number of users who have submitted an order.

[0023] Specifically, assume that the number of users browsing a certain product interface is 100, the number of users who have submitted orders is 50, and the number of users who have actually made payments is 40. Then the first conversion rate parameter is 50 / 100*100% = 50%, and the second conversion rate parameter is 40 / 50*100% = 80%. If there are more data types, calculate the conversion rate parameters by analogy according to the above method until N - 1 conversion rate parameters are obtained. Among them, the number of conversion rate parameters is N - 1. In this example, N is 3, so the total number of conversion rate parameters is 3 - 1 = 2. The reason why the number of conversion rate parameters is N - 1 is that when calculating the number of users of the Nth data type, there is no number of users of the N + 1th data type to compare with the number of users of the Nth data type to obtain the Nth conversion rate parameter. Therefore, the total number of conversion rate parameters is N - 1.

[0024] Further, in step S300 of the present invention, calculating N quantity generation parameters and N - 1 conversion rate generation parameters according to the N user quantities and the N - 1 conversion rate parameters, in combination with historical record data, includes: Collecting N historical user quantities and N - 1 historical conversion rates according to the record data within the historical time; Calculating N quantity generation parameters according to the N user quantities and the N historical user quantities; Calculating N conversion rate generation parameters according to the N - 1 conversion rate parameters and the N - 1 historical conversion rates.

[0025] Among them, collecting N historical user quantities and N - 1 historical conversion rates according to the record data within the historical time includes: Collecting all user quantities and conversion rate parameters of the N data types within a preset historical time range according to the record data within the historical time, to obtain N historical user quantity sets and N - 1 historical conversion rate sets; Calculating the means of the N historical user quantity sets and the N - 1 historical conversion rate sets respectively, to obtain N historical user quantities and N - 1 historical conversion rates.

[0026] In this embodiment, collecting the total number of users and conversion rate parameters of N data types within a preset historical time range based on the data records within the historical time is to expand the coverage of historical data as much as possible to obtain more representative historical data, which serves as a reference object for the data of the funnel chart to be generated, so as to increase the information content of the generated funnel chart. Among them, the data records within the historical time are a data set generated within a certain period in the past that can be represented by a funnel chart. For example, in the scenario of online shopping described in S200, if the historical time is defined as 7 days, the data records within the historical time can be the number of users browsing a certain product interface every day within 7 days, the number of users submitting orders, the number of users actually making payments, and the corresponding first conversion rate parameter and second conversion rate parameter. By continuously collecting data for 7 days, N historical user number sets and N - 1 historical conversion rate sets are obtained.

[0027] Next, by calculating the means of the 7-day historical user number set and historical conversion rate set, the N (N = 3) historical user numbers and N - 1 (N - 1 = 2) historical conversion rates can be obtained, which can summarize the data record situation within 7 days.

[0028] Then, by comparing the N historical user numbers and N - 1 historical conversion rates with the data of the funnel chart to be generated, the quantity generation parameter and conversion rate generation parameter are obtained, and the identification coefficient is obtained accordingly and marked in the generated funnel chart, so that historical data can be associated in the funnel chart, increasing the information content and visualization degree of the funnel chart.

[0029] Furthermore, step S300 in the present invention further includes calculating N quantity generation parameters based on the N user numbers and N historical user numbers, including: Combining the N user numbers and N historical user numbers according to the N data types; Calculating the ratio of each user number to the corresponding historical user number as the quantity generation parameter, and obtaining N quantity generation parameters.

[0030] In this embodiment, to obtain the quantity generation parameter, it is first necessary to match the user data for the funnel chart to be generated with the historical user data one by one, and then calculate the ratio. For example, in the online shopping scenario described in S200, it is necessary to match the user data for the funnel chart to be generated with the number of users who browsed a certain product interface, the number of users who submitted orders, and the number of users who actually made payments in the historical user data one by one, and then calculate the ratio. If the number of users who browsed a certain product interface per day in the user data for the funnel chart to be generated is 80, and the average number of users who browsed a certain product interface per day in the historical user data is 100, then the quantity generation parameter for the data type of the number of users who browsed a certain product interface is 80 / 100 = 0.8. The quantity generation parameters for other data types are calculated in the same way, and ultimately all N quantity generation parameters are calculated.

[0031] In this embodiment, the conversion rate generation parameter is calculated in the same way as the quantity generation parameter. For example, in the online shopping scenario described in S200, the user data for which the funnel chart is to be generated needs to be matched one-to-one with the first conversion rate parameter and the second conversion rate parameter in the historical user data, and then their ratios are calculated. For example, if the first conversion rate parameter in the user data for which the funnel chart is to be generated is 0.8, and the average daily first conversion rate parameter in the historical user data is 0.5, then the conversion rate generation parameter for the first conversion rate parameter is 0.8 / 0.5 = 1.6. The same procedure is applied to the other conversion rate generation parameters, ultimately calculating all N-1 conversion rate generation parameters.

[0032] Furthermore, in step S400 of the present invention, N funnel chart generation information is configured according to the N quantity generation parameters and N-1 conversion rate generation parameters to generate a funnel chart, including: Generate N quantity identification coefficients and N-1 conversion rate identification coefficients according to the N quantity generation parameters and N-1 conversion rate generation parameters; Generate a basic funnel chart, wherein the basic funnel chart includes N funnel chart areas corresponding to the N data types; According to the N quantity identification coefficients and N-1 conversion rate identification coefficients, and based on the N quantity generation parameters and N-1 conversion rate generation parameters, the N funnel chart regions are identified to obtain a funnel chart.

[0033] The step of generating N quantity identification coefficients and N-1 conversion rate identification coefficients according to the N quantity generation parameters and N-1 conversion rate generation parameters includes: Calculate the ratio of the quantity generation parameter and the conversion rate generation parameter of the Nth data type to the sum of the two, and obtain the Nth quantity identification coefficient and the Nth conversion rate identification coefficient, wherein the identification coefficient includes the proportion of the identification area; Continue to generate N quantity generation parameters and N-1 conversion rate generation parameters, and calculate to obtain N quantity identification coefficients and N-1 conversion rate identification coefficients. Among them, the quantity identification coefficient of the first quantity type is 1, and the conversion rate identification coefficient is 0.

[0034] In the embodiments of the present application, calculating the conversion rate identification coefficient and the quantity identification coefficient is to measure the proportions of the conversion rate and the user quantity in the change of the data to be generated for the funnel chart compared with the historical data. By marking the marked areas with different areas according to the identification coefficients, the weights of the conversion rate and the conversion quantity in the change compared with the historical data can be visually displayed, so as to increase the information content and visualization degree of the funnel chart.

[0035] Specifically, to calculate the quantity identification coefficient and the conversion rate identification coefficient, it is necessary to first calculate the sum of the quantity generation parameter and the conversion rate generation parameter, and then divide the quantity generation parameter and the conversion rate generation parameter by the value of the sum respectively, so that the quantity identification coefficient and the conversion rate identification coefficient can be obtained.

[0036] For example, in an embodiment, the conversion rate generation parameter is 1.6, that is, the conversion rate has increased by 1.6 times compared with the historical data, and the quantity generation parameter is 0.4, that is, the user quantity of this data type has decreased to 0.4 times of the historical data. Then the quantity identification coefficient is 0.4 / (0.4 + 1.6) = 0.2, and the conversion rate identification coefficient is 1.6 / (0.4 + 1.6) = 0.8. Obviously, the sum of the quantity identification coefficient and the conversion rate identification coefficient is always 1.

[0037] By the same method, all N quantity generation parameters and N-1 conversion rate generation parameters can be obtained. Among them, since there is no corresponding conversion rate generation parameter for the quantity generation parameter of the first quantity type, the conversion rate generation parameter of the first quantity type is replaced by 0 in the calculation process, and the corresponding quantity identification coefficient of the first quantity type is 1 / (1 + 0) = 1. Through the above method, all N quantity identification coefficients and N-1 conversion rate identification coefficients can be calculated, and then the funnel chart can be generated.

[0038] In the embodiments of the present application, the way to generate the funnel chart is to first generate a basic funnel chart according to the data to be generated for the funnel chart, and then mark the basic funnel chart according to the aforementioned identification coefficients.

[0039] Specifically, data processing software such as Excel and Matplotlib can be used to generate a basic funnel chart based on the input data for generating a funnel chart, which serves as the basis for annotation. Then, according to the quantity annotation coefficient and conversion rate annotation coefficient calculated above, the areas of different data types in the funnel chart are annotated with areas to show the proportion of the changes in the user quantity and conversion rate in the change compared with the previous data. Specifically, it can be represented by the proportion of the area of the marked region. Since the sum of the quantity identification coefficient and the conversion rate identification coefficient is 1, the area of the data type region can be divided according to the magnitudes of the quantity identification coefficient and the conversion rate identification coefficient. For example, if the conversion rate identification coefficient is 0.2 and the quantity identification coefficient is 0.8, in the color block of the corresponding data type in the funnel chart, the conversion rate identification can occupy 20% of the area, and the quantity identification can occupy 80% of the area, and different colors can be used for identification, so as to clearly show the proportion of the changes in the user quantity and conversion rate in the change compared with the previous data. This improves the information content and data visualization degree of the funnel chart.

[0040] It should be noted that the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0041] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0042] This specification and the accompanying drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. An intelligent generation method for a funnel chart, characterized in that, The method includes: Collecting the number of users of N data types, where the N data types have a progressive relationship, and N is a positive integer; Calculating N-1 conversion rate parameters based on the N user numbers; Calculating N quantity generation parameters and N-1 conversion rate generation parameters based on the N user numbers, the N-1 conversion rate parameters, and combined with historical record data; Configuring N funnel chart generation information according to the N quantity generation parameters and N-1 conversion rate generation parameters, and generating a funnel chart.

2. The intelligent generation method of the funnel chart according to claim 1, wherein Calculating N-1 conversion rate parameters based on the N user numbers, including: Calculating the ratio of the number of users of the Nth data type to the number of users of the (N-1)th data type according to the progressive relationship to obtain the Nth conversion rate parameter; Continuing to calculate N-1 conversion rate parameters.

3. The intelligent generation method of the funnel chart according to claim 1, wherein Calculating N quantity generation parameters and N-1 conversion rate generation parameters based on the N user numbers, the N-1 conversion rate parameters, and combined with historical record data, including: Collecting N historical user numbers and N-1 historical conversion rates according to the record data within the historical time; Calculating N quantity generation parameters based on the N user numbers and the N historical user numbers; Calculating N conversion rate generation parameters based on the N-1 conversion rate parameters and the N-1 historical conversion rates.

4. The intelligent generation method of the funnel chart according to claim 3, characterized in that Collecting N historical user numbers and N-1 historical conversion rates according to the record data within the historical time, including: Collecting all user numbers and conversion rate parameters of the N data types within a preset historical time range according to the record data within the historical time to obtain N sets of historical user numbers and N-1 sets of historical conversion rates; Respectively calculating the means of the N sets of historical user numbers and the N-1 sets of historical conversion rates to obtain N historical user numbers and N-1 historical conversion rates.

5. The intelligent generation method of the funnel chart according to claim 1, wherein, Calculating N quantity generation parameters based on the N user numbers and the N historical user numbers, including: Combining the N user numbers and the N historical user numbers according to the N data types; Calculating the ratio of each user number to the corresponding historical user number as the quantity generation parameter, and calculating N quantity generation parameters.

6. The intelligent generation method of the funnel chart according to claim 1, wherein Configuring N funnel chart generation information according to the N quantity generation parameters and N-1 conversion rate generation parameters, and generating a funnel chart, including: Generating N quantity identification coefficients and N-1 conversion rate identification coefficients according to the N quantity generation parameters and N-1 conversion rate generation parameters; Generating a basic funnel chart, where the basic funnel chart includes N funnel chart areas corresponding to the N data types; Identifying the N funnel chart areas according to the N quantity generation parameters and N-1 conversion rate generation parameters according to the N quantity identification coefficients and N-1 conversion rate identification coefficients to obtain a funnel chart.

7. The intelligent generation method of the funnel chart according to claim 1, wherein Generating N quantity identification coefficients and N-1 conversion rate identification coefficients according to the N quantity generation parameters and N-1 conversion rate generation parameters, including: Calculate the ratios of the quantity generation parameter and the conversion rate generation parameter of the Nth data type to the sum of the two respectively, and obtain the Nth quantity identification coefficient and the Nth conversion rate identification coefficient, where the identification coefficient includes the proportion of the identified area; Continue to calculate and obtain N quantity identification coefficients and N - 1 conversion rate identification coefficients according to the N quantity generation parameters and N - 1 conversion rate generation parameters, where the quantity identification coefficient of the first quantity type is 1 and the conversion rate identification coefficient is 0.

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