Method and device for determining influencing factors, and storage medium

Abstract

The application provides a method and device for determining an influence factor and a storage medium, relates to the field of communication, and is used for improving the accuracy of determining the influence factor. The method comprises the following steps: acquiring a plurality of index variables, the index variable being a change amount of a business index within two time periods, and the index variable corresponding to at least one influence factor. For each index variable, a first influence degree is determined according to the index variable, so as to determine a plurality of first influence degrees, and the first influence degree is used for indicating the influence degree of the at least one influence factor on the business index. According to the plurality of first influence degrees, a second influence degree of each influence factor in the at least one influence factor is determined, and the second influence degree is used for indicating the influence degree of the influence factor on the business index. According to the second influence degree of each influence factor in the at least one influence factor, at least one target factor is determined, and the target factor is the influence factor whose second influence degree is greater than a preset influence degree threshold.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication, and in particular to a method and device for determining an influencing factor and a storage medium. BACKGROUND

[0002] With the development of communication technology, the number of users gradually increases, and the competition between operators gradually shifts to the number of users. Operators can analyze user behavior, determine user behavior that has a greater impact on business indicators of the operator, and develop strategies based on user behavior with a greater impact to gain more users.

[0003] However, user behavior is complex, resulting in many factors affecting business indicators. For example, user behavior can be any of the following: the type of mobile card opened by the user, the type of package used by the user, the area where the user is located, and one user behavior can be an influencing factor. Therefore, staff need to determine the influencing factor with a greater impact from a large number of influencing factors, and manual analysis can reduce the accuracy of determining the influencing factor. SUMMARY

[0004] The present application provides a method and device for determining an influencing factor and a storage medium to improve the accuracy of determining the influencing factor.

[0005] To achieve the above object, the present application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a method for determining an influencing factor. The method comprises: obtaining a plurality of index variables, the index variable being the change amount of the business indicator within two time periods, and the index variable corresponding to at least one influencing factor. For each index variable, a first influence degree is determined according to the index variable to determine a plurality of first influence degrees, the first influence degree being used to indicate the influence degree of the at least one influencing factor on the business indicator. According to the plurality of first influence degrees, a second influence degree of each influencing factor in the at least one influencing factor is determined, the second influence degree being used to indicate the influence degree of the influencing factor on the business indicator. According to the second influence degree of each influencing factor in the at least one influencing factor, at least one target factor is determined, the target factor being the influencing factor with a second influence degree greater than a preset influence degree threshold.

[0007] Optionally, the method for determining an influencing factor can further comprise: obtaining a business indicator of a plurality of time periods. A plurality of index combinations are generated according to the business indicators of the plurality of time periods, the index combination comprising: the business indicators of two time periods with the same time characteristics. The above "obtaining a plurality of index variables" comprises: for each index combination, generating an index variable according to the index combination to determine a plurality of index variables.

[0008] Optionally, the two time periods include a first time period and a second time period, and the first time period is earlier than the second time period. The method further includes determining an index change rate according to the plurality of index variables and the business index of the first time period corresponding to each index variable. The determining the first influence degree according to the index variable includes determining an index benchmark according to the index change rate and the business index of the first time period corresponding to the index variable, and the index benchmark is used to indicate a target change amount of the business index within the two time periods. The method further includes determining a target difference value according to the index variable and the index benchmark, and the target difference value is a difference between the index variable and the index benchmark. The determining the first influence degree according to the target difference value and the business index of the first time period corresponding to each index variable.

[0009] Optionally, one index variable corresponds to one business information, and the business information includes at least one influence factor. The determining the second influence degree of each influence factor in the at least one influence factor according to the plurality of first influence degrees includes, for each influence factor, determining the second influence degree of the influence factor according to a target operation, so as to determine the second influence degree of each influence factor. The target operation includes determining at least one target information from the plurality of business information based on a to-be-tested factor, the to-be-tested factor being any one of the at least one influence factor, and the target information being the business information in which the to-be-tested factor exists. The determining the second influence degree of the to-be-tested factor according to the first influence degree corresponding to each target information.

[0010] In a second aspect, the present application provides a device for determining an influence factor, which includes an acquisition module and a processing module.

[0011] The acquisition module is configured to acquire a plurality of index variables, and each index variable is a change amount of a business index within two time periods, and each index variable corresponds to at least one influence factor. The processing module is configured to, for each index variable, determine a first influence degree according to the index variable, so as to determine a plurality of first influence degrees, and each first influence degree is used to indicate an influence degree of the at least one influence factor on the business index. The processing module is further configured to determine a second influence degree of each influence factor in the at least one influence factor according to the plurality of first influence degrees, and each second influence degree is used to indicate the influence degree of the influence factor on the business index. The processing module is further configured to determine at least one target factor according to the second influence degree of each influence factor in the at least one influence factor, and each target factor is an influence factor whose second influence degree is greater than a preset influence degree threshold.

[0012] Optionally, the acquisition module is further configured to acquire the business index of a plurality of time periods. The processing module is further configured to generate a plurality of index combinations according to the business index of the plurality of time periods, and each index combination includes the business index of two time periods with the same time characteristics. The processing module is specifically configured to, for each index combination, generate an index variable according to the index combination, so as to determine the plurality of index variables.

[0013] Optionally, the two time periods include a first time period and a second time period, and the first time period is earlier than the second time period. The processing module is further configured to determine an index change rate according to the plurality of index variables and the service index of the first time period corresponding to each index variable. The processing module is specifically configured to determine an index benchmark according to the index change rate and the service index of the first time period corresponding to the index variable, and the index benchmark is used to indicate a target change amount of the service index in the two different time periods. The processing module is specifically configured to determine a target difference value according to the index variable and the index benchmark, and the target difference value is a difference between the index variable and the index benchmark. The processing module is specifically configured to determine a first influence degree according to the target difference value and the service index of the first time period corresponding to each index variable.

[0014] Optionally, one index variable corresponds to one service information, and the service information includes at least one influence factor. The processing module is further configured to determine, for each influence factor, a second influence degree of the influence factor according to the target operation, so as to determine the second influence degree of each influence factor. The target operation includes that the processing module is specifically configured to determine at least one target information from the plurality of service information based on a to-be-tested factor, the to-be-tested factor is any one of the at least one influence factor, and the target information is the service information in which the to-be-tested factor exists. The processing module is specifically configured to determine the second influence degree of the to-be-tested factor according to the first influence degree corresponding to each target information.

[0015] In a third aspect, a device for determining an influence factor is provided. The device includes a processor and a memory. The processor and the memory are coupled. The memory is configured to store one or more programs including computer-executable instructions. When the device for determining an influence factor is running, the processor executes the computer-executable instructions stored in the memory to implement the method for determining an influence factor described in any possible implementation manner of the first aspect.

[0016] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores instructions. When the instructions run on a computer, the computer executes the method for determining an influence factor described in any possible implementation manner of the first aspect.

[0017] In a fifth aspect, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the computer program causes a computer to implement the method for determining an influence factor described in any possible implementation manner of the first aspect.

[0018] The technical problems solved by the device for determining an influence factor, the computer device, the computer storage medium, or the computer program product and the technical effects achieved by the device for determining an influence factor, the computer device, the computer storage medium, or the computer program product can be referred to the technical problems solved and the technical effects achieved by the first aspect, which will not be repeated here.

[0019] The technical scheme provided in the application brings at least the following beneficial effects: the server can obtain a plurality of index variables, the index variable being a variation of a business index within two time periods, and the index variable corresponding to at least one influence factor. For each index variable, the server can determine a first influence degree according to the index variable, to determine a plurality of first influence degrees, the first influence degree being used to indicate an influence degree of the at least one influence factor on the business index. The server can determine a second influence degree of each influence factor in the at least one influence factor according to the plurality of first influence degrees, the second influence degree being used to indicate the influence degree of the influence factor on the business index. The server can determine at least one target factor according to the second influence degree of each influence factor in the at least one influence factor, the target factor being the influence factor whose second influence degree is greater than a preset influence degree threshold. In this way, the server can obtain the influence degree of the at least one influence factor on the business index, and then obtain the influence degree of each influence factor on the business index, so as to determine the influence factor with a greater influence degree, and the accuracy of determining the influence factor can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application, and, without in any way intending to be bound by a particular representation of these drawings, do not constitute an improper limitation of the application.

[0021] Figure 1 is an architecture schematic diagram of a determination system of an influence factor according to an example embodiment;

[0022] Figure 2 is a flowchart of a determination method of an influence factor according to an example embodiment;

[0023] Figure 3 is a flowchart of another determination method of an influence factor according to an example embodiment;

[0024] Figure 4 is a schematic diagram of a target factor of a positive influence degree according to an example embodiment;

[0025] Figure 5 is a schematic diagram of a target factor of a negative influence degree according to an example embodiment;

[0026] Figure 6 is a flowchart of another determination method of an influence factor according to an example embodiment;

[0027] Figure 7 is a structural block diagram of a determination device of an influence factor according to an example embodiment;

[0028] Figure 8is a structural schematic diagram of a determination device of an influence factor according to an exemplary embodiment;

[0029] Figure 9 is a conceptual partial view of a computer program product according to an exemplary embodiment. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0031] The character " / " in the present application generally represents an "or" relationship between the associated objects before and after. For example, A / B can be understood as A or B.

[0032] The terms "first" and "second" in the description and claims of the present application are used to distinguish different objects, rather than to describe a specific order of the objects.

[0033] In addition, the terms "comprise" and "have" and any variations thereof in the description of the present application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or modules is not limited to the listed steps or modules, but can optionally further comprise other steps or modules not listed, or can optionally further comprise other steps or modules inherent to the process, method, product or device.

[0034] In addition, in the embodiments of the present application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design solution described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or advantageous than other embodiments or design solutions. Rather, the use of the words "exemplary" or "for example" is intended to present concepts in a particular manner.

[0035] Before the determination method of the influence factor in the embodiments of the present application is described in detail, the implementation environment and application scenario of the embodiments of the present application are introduced.

[0036] An operator can analyze user behaviors, determine user behaviors that have a greater impact on business indicators of the operator, and formulate strategies according to the user behaviors that have a greater impact, to attract more users. However, user behaviors are complex, resulting in more factors that have an impact on business indicators. For example, a user behavior can be any one of the following: a type of mobile card opened by a user, a type of package used by a user, and a region where a user is located, and a user behavior can be used as an impact factor. Therefore, a staff member needs to determine impact factors that have a greater impact from a large number of impact factors, and human analysis can reduce the accuracy of determining impact factors.

[0037] To solve the above problem, an embodiment of the present application provides a method for determining an impact factor, which includes: a server can obtain a plurality of index variables, the index variable being a change amount of a business indicator within two time periods, and the index variable corresponding to at least one impact factor. For each index variable, the server can determine a first impact degree according to the index variable, to determine a plurality of first impact degrees, the first impact degree being used to indicate an impact degree of the at least one impact factor on the business indicator. The server can determine a second impact degree of each impact factor in the at least one impact factor according to the plurality of first impact degrees, the second impact degree being used to indicate an impact degree of the impact factor on the business indicator. The server can determine at least one target factor according to the second impact degree of each impact factor in the at least one impact factor, the target factor being an impact factor whose second impact degree is greater than a preset impact degree threshold. In this way, the server can obtain the impact degree of the at least one impact factor on the business indicator, and then obtain the impact degree of each impact factor on the business indicator, to determine an impact factor that has a greater impact, and the accuracy of determining the impact factor can be improved.

[0038] The implementation environment of the embodiment of the present application is introduced as follows.

[0039] Figure 1 An architecture schematic diagram of a system for determining an impact factor according to an exemplary embodiment is shown. The architecture includes a base station (such as base station 101) and a server (such as server 102). The base station and the server can perform wired / wireless communication.

[0040] The base station (such as base station 101) can include various forms of base stations, such as macro base stations, micro base stations (also known as small stations), relay stations, access points, etc. Specifically, it can be an access point (AP) in a Wireless Local Area Network (WLAN), a base station (BTS) in a Global System for Mobile Communications (GSM) or Code Division Multiple Access (CDMA), a base station (NodeB, NB) in a Wideband Code Division Multiple Access (WCDMA) network, an evolved Node B (eNB or eNodeB) in LTE, a relay station or access point, or a next-generation Node B (gNB) in vehicle-mounted equipment, wearable devices, and 5G networks, or a base station in a future Public Land Mobile Network (PLMN) network, etc.

[0041] In this embodiment, the base station can be a base station deployed in a cell. The base station can send service metrics for multiple time periods to the server.

[0042] A server (such as server 102) can send indicator request messages to the base station to request service indicators for multiple time periods.

[0043] It should be noted that the server can be a single physical server, or a server cluster consisting of multiple servers. Alternatively, the server cluster can be a distributed cluster. Alternatively, the server can be a cloud server. This application does not limit the specific implementation of the server.

[0044] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0045] like Figure 2 The image shows a method for determining an impact factor provided in an embodiment of this application. The method includes:

[0046] S201, The server retrieves multiple indicator variables.

[0047] Among them, the indicator variable is the change of business indicators in two time periods, and the indicator variable corresponds to at least one influencing factor.

[0048] It should be noted that in the embodiments of the present application, the index variable is the change amount of the business index, the business index can be business income or business expenditure, and the influence factor can include channel, product, and region.

[0049] In a possible design, the two time periods include a first time period and a second time period, and the first time period is earlier than the second time period.

[0050] For example, the two time periods include June 2021 and July 2021, the first time period is June 2021, and the second time period is July 2021.

[0051] In a possible implementation, for each index variable, the server can obtain the business index of the two time periods. The server can calculate the index variable according to the business index of the two time periods, so that the server can calculate a plurality of index variables.

[0052] In another possible implementation, the server can receive a first operation instruction for inputting a plurality of index variables. In response to the first operation instruction, the server can obtain the plurality of index variables.

[0053] For example, as shown in Table 1, an index variable and an influence factor corresponding to the index variable are shown. The business index is business income, and at least one influence factor includes a first channel, a second channel, a first product, a second product, and a third product. The first channel can include a plurality of second channels, the first product can include a plurality of second products, and the second product can include a plurality of third products. In Table 1, the two time periods include June 2021 and July 2021, and the at least one influence factor includes channel 1, channel 2, product 1, product 2, and product 3. Channel 1 is the first channel, channel 2 is any channel in the plurality of second channels, product 1 is the first product, product 2 is any product in the plurality of second products, and product 3 is any product in the plurality of third products.

[0054] Table 1: Index variable and influence factor corresponding to the index variable

[0055]

[0056]

[0057] That is, in a case where the at least one influence factor includes a social channel, a municipal channel, an Internet service, an Internet package, and an Internet high-value package, the index variable of the income is 10. In a case where the at least one influence factor includes a social channel, a manufacturer channel, a nationwide voice service, a nationwide voice package, and a nationwide voice low-value package, the index variable of the income is -10. In a case where the at least one influence factor includes a group channel, a group agent, a local voice service, a local voice package, and a local high-value voice package, the index variable of the income is 30.

[0058] It should be noted that in the embodiment of the present application, for Table 1, one row can be one record, and each record includes at least one influence factor.

[0059] In the embodiment of the present application, for each index variable, the server can perform S202.

[0060] S202, the server determines a first influence degree according to the plurality of index variables.

[0061] The first influence degree is used to indicate an influence degree of the at least one influence factor on the business index.

[0062] In the embodiment of the present application, before the server determines the first influence degree according to the index variable, the server can determine an index change rate according to the plurality of index variables and the business index of the first time period corresponding to each index variable.

[0063] In a possible design, the index change rate can be represented by Formula One.

[0064]

[0065] The cr_total is used to represent the index growth rate, and the c i The c i is used to represent the i th index variable, and the t i The N i is used to represent the business index of the first time period corresponding to the i th index variable, and the N is used to represent the number of index variables.

[0066] For example, in combination with Table 1, the plurality of index variables include 10, -10, and 20, and the business index of the first time period corresponding to each index variable in the plurality of index variables is 20, 20, and 0 respectively. Then the index change rate of the business income is 0.5.

[0067] In a possible implementation manner, the server can determine an index benchmark according to the index change rate and the business index of the first time period corresponding to the index variable.

[0068] The index benchmark is used to indicate a target change amount of the business index within two time periods.

[0069] In a possible design, the index reference can be represented by Formula Two.

[0070] x i = cr_total * t i Formula Two.

[0071] wherein, x i is used to represent the index reference of the i-th index variable, cr_total is used to represent the index growth rate, t i is used to represent the business index of the first time period corresponding to the i-th index variable.

[0072] It should be noted that in the embodiments of the present application, the index growth rate is multiplied by the business index of the first time period corresponding to the index variable to obtain the target change amount of the business index within two time periods.

[0073] In the embodiments of the present application, the server can determine a target difference value according to the index variable and the index reference, the target difference value being a difference between the index variable and the index reference.

[0074] In a possible design, the target difference value can be represented by Formula Three.

[0075] s i = c i - x i Formula Three.

[0076] wherein, s i is used to represent the target difference value of the i-th index variable, c i is used to represent the i-th index variable, x i is used to represent the index reference of the i-th index variable.

[0077] It should be noted that in the embodiments of the present application, the index variable is specifically used to indicate the actual change amount of the business index within two time periods, the index reference is used to indicate the target change amount of the business index within two time periods, and the target difference value is used to indicate the difference between the actual change amount and the target change amount.

[0078] Then, the server can determine a first influence degree according to the target difference value and the business index of the first time period corresponding to each index variable.

[0079] In a possible design, the first influence degree can be represented by Formula Four.

[0080]

[0081] wherein, cr_factor i is used to represent the first influence degree corresponding to the i-th index variable, s i is used to represent the target difference value of the i-th index variable, tj a service index of a first time period corresponding to the jth index variable.

[0082] For example, in combination with Table 1, the plurality of index variables include 10, -10, and 20, the service index of the first time period corresponding to each index variable in the plurality of index variables is 20, 20, and 0 respectively, and the index change rate of the service revenue is 0.5. The first influence degree corresponding to the index variable 10 is 0, the first influence degree corresponding to the index variable -10 is -0.25, and the first influence degree corresponding to the index variable 40 is 0.5.

[0083] It should be noted that in the embodiments of the present application, one row in Table 1 is one record, N is the number of index variables, and N is the number of records. The ith index variable is the ith record, and the first influence degree corresponding to the ith index variable is the first influence degree corresponding to the ith record.

[0084] In the embodiments of the present application, for each index variable, the server can perform S202. That is, for each index variable, the server can determine the first influence degree according to the index variable, to determine a plurality of first influence degrees.

[0085] S203, the server determines the second influence degree of each influence factor in at least one influence factor according to the plurality of first influence degrees.

[0086] The second influence degree is used to indicate the influence degree of the influence factor on the service index.

[0087] In a possible design, one index variable corresponds to one service information, and the service information includes at least one influence factor.

[0088] For example, in combination with Table 1, the index variable 10 corresponds to service information one, the service information one includes social channels, municipal channels, Internet services, Internet packages, and Internet high-value packages. The index variable -10 corresponds to service information two, the service information two includes social channels, manufacturer channels, national voice services, national voice packages, and national voice low-value packages. The index variable 20 corresponds to service information three, and the service information three includes group channels, group agents, local voice services, local voice packages, and local high-value voice packages.

[0089] In a possible implementation, for each influence factor, the server can determine the second influence degree of the influence factor according to the target operation, to determine the second influence degree of each influence factor.

[0090] In the embodiments of the present application, the target operation includes: the server can determine at least one target information from the plurality of service information based on the to-be-tested factor, the to-be-tested factor being any of the at least one influence factor, and the target information being the service information in which the to-be-tested factor exists. The server can determine the second influence degree of the to-be-tested factor according to the first influence degree corresponding to each target information.

[0091] In a possible design, the server can add the first influence degree corresponding to each target information to obtain the second influence degree of the to-be-tested factor.

[0092] For example, assuming that the plurality of service information includes: service information one, service information two, and service information three. The service information one includes: a social channel, a municipal channel, an Internet service, an Internet package, and an Internet high-amount package. The service information two includes: a social channel, a manufacturer channel, a nationwide voice service, a nationwide voice package, and a nationwide voice low-amount package. The service information three includes: a group channel, a group agent, a local voice service, a local voice package, and a local high-amount voice package. Assuming that the first influence degree corresponding to the service information one is 0, the first influence degree corresponding to the service information two is -0.25, the first influence degree corresponding to the service information three is 0.5, and the to-be-tested factor is a social channel, the target information includes: the service information one and the service information two, and the second influence degree of the to-be-tested factor is -0.25.

[0093] S204, the server determines at least one target factor according to the second influence degree of each influence factor in the at least one influence factor.

[0094] The target factor is an influence factor whose second influence degree is greater than a preset influence degree threshold.

[0095] In a possible implementation, for each influence factor, the server can compare the second influence degree of the influence factor with a preset influence degree threshold. If the second influence degree of the influence factor is greater than the preset influence degree threshold, the influence factor is determined as a target factor, to determine at least one target factor.

[0096] In another possible implementation, the server can sort the second influence degree of each influence factor in the at least one influence factor to obtain a plurality of sorted second influence degrees. The server determines at least one target factor from the plurality of sorted second influence degrees.

[0097] For example, the server can select the top 2% of influence factors as the at least one target factor.

[0098] It should be noted that in the embodiments of the present application, in the case that the second influence degree is a negative influence degree, the server can take the absolute value of each of the plurality of second influence degrees to obtain a plurality of target absolute values, and compare each of the plurality of target absolute values with the preset influence degree threshold. Alternatively, the server can take the absolute value of each of the plurality of second influence degrees to obtain a plurality of target absolute values, and sort the plurality of target absolute values.

[0099] It can be understood that the server can obtain a plurality of index variables, the index variable being a variation of the business index in two time periods, and the index variable corresponding to at least one influence factor. For each index variable, the server can determine a first influence degree according to the index variable, to determine a plurality of first influence degrees, the first influence degree being used to indicate the influence degree of the at least one influence factor on the business index. The server can determine a second influence degree of each of the at least one influence factor according to the plurality of first influence degrees, the second influence degree being used to indicate the influence degree of the influence factor on the business index. The server can determine at least one target factor according to the second influence degree of each of the at least one influence factor, the target factor being the influence factor whose second influence degree is greater than the preset influence degree threshold. In this way, the server can obtain the influence degree of the at least one influence factor on the business index, and then obtain the influence degree of each influence factor on the business index, so as to determine the influence factor with greater influence degree, and the accuracy of determining the influence factor can be improved.

[0100] In some embodiments, as shown in Figure 3 Before the server obtains the plurality of index variables, the method for determining the influence factor can further include the following steps: S301-S302.

[0101] S301, the server obtains the business index of a plurality of time periods.

[0102] In a possible implementation, the server can send an index request message to the base station, the index request message being used to indicate a request for the business index of a plurality of time periods. The base station can receive the index request message from the server. In response to the index request message, the base station can send an index response message to the server, the index response message including the business index of the plurality of time periods.

[0103] In another possible implementation, the server can receive a second operation instruction, the second operation instruction being used to input the business index of a plurality of time periods. In response to the second operation instruction, the server can obtain the business index of the plurality of time periods.

[0104] For example, as shown in Table 2, Table 2 shows the business index of a plurality of time periods. Wherein, the business index is business income, each time period can correspond to a plurality of business indexes, and the influence factors affecting the business index are different.

[0105] Table 2 business indicators of multiple periods

[0106]

[0107]

[0108] That is, on July 1, 2021, the business indicator is 10 under the condition that the influence factors include: internet channels, self-owned online touchpoints, nationwide voice services, nationwide voice packages, and nationwide voice high-amount packages. On July 1, 2021, the business indicator is 20 under the condition that the influence factors include: social channels, other channels, internet services, internet packages, and internet high-amount packages. On June 1, 2021, the business indicator is 30 under the condition that the influence factors include: social channels, city-level single stores, traffic services, traffic packages, and traffic low-amount packages. In the embodiments of the present application, the business indicators of other periods can be referred to the description of the business indicators of the periods described above, and will not be described herein.

[0109] S302, the server generates multiple index combinations according to the business indicators of multiple periods.

[0110] The index combinations include: the business indicators of two periods with the same time characteristics.

[0111] In a possible design, the two periods with the same time characteristics can be two periods of the same year, and the two periods with the same time characteristics can also be two periods of the same month.

[0112] For example, June 2020 and July 2020 are two periods of the same year, and therefore June 2020 and July 2020 are two periods with the same time characteristics. June 2020 and June 2021 are two periods of the same month, and therefore June 2020 and June 2021 are two periods with the same time characteristics.

[0113] In the embodiments of the present application, before the server generates multiple index combinations according to the business indicators of multiple periods, the server can preprocess the business indicators of multiple periods to obtain the business indicators of the same period.

[0114] For example, suppose the business indicators of multiple periods include the business indicators of June 2021 and the business indicators of July 2021. The preprocessing of the business indicators of multiple periods can respectively obtain the business indicators of June 2021 (as shown in Table 3) and the business indicators of July 2021 (as shown in Table 4).

[0115] Table 3 business indicators of June 2021

[0116]

[0117] That is, the influence factor includes: social channels, manufacturer channels, nationwide voice services, nationwide voice packages, nationwide voice low-amount package, and the business index of June 2021 is 20. The influence factor includes: group channels, group agents, local voice services, local voice packages, and local voice high-amount packages, and the business index of June 2021 is 30. The influence factor includes: social channels, social channels Demographics, traffic services, traffic packages, and traffic low-amount packages, and the business index of June 2021 is 10. In the embodiments of the present application, the introduction of other business indexes of June 2021 can refer to the description of the above business indexes of June 2021, which will not be described here.

[0118] Table 4 Business index in July 2021

[0119]

[0120]

[0121] That is, the influence factor includes: social channels, manufacturer channels, nationwide voice services, nationwide voice packages, nationwide voice low-amount package, and the business index of July 2021 is 10. The influence factor includes: group channels, group agents, local voice services, local voice packages, and local voice high-amount packages, and the business index of July 2021 is 0. The influence factor includes: social channels, social channels Demographics, traffic services, traffic packages, and traffic low-amount packages, and the business index of July 2021 is 20. In the embodiments of the present application, the introduction of other business indexes of July 2021 can refer to the description of the above business indexes of July 2021, which will not be described here.

[0122] In a possible implementation, for the business indexes of multiple periods, the server can combine the business indexes of two periods with the same time characteristics as an index combination to generate multiple index combinations.

[0123] For example, assuming that the business indexes of multiple periods include: the income in June 2020, the income in July 2020, the income in June 2021, and the income in July 2021. Then the multiple index combinations can include: index combination one (the income in June 2020 and the income in July 2020), index combination two (the income in June 2021 and the income in July 2021). Or the multiple index combinations can include: index combination three (the income in June 2020 and the income in June 2021), index combination four (the income in July 2020 and the income in July 2021).

[0124] In the embodiments of the present application, the server obtaining the plurality of index variables (S201) can include:

[0125] S303, for each index combination, the server generates an index variable according to the index combination to determine the plurality of index variables.

[0126] In a possible implementation, for each index combination, the server can generate an index variable according to the index combination by year-on-year or month-on-month to determine the plurality of index variables.

[0127] It should be noted that, in the embodiments of the present application, year-on-year refers to comparison with the same period in different years, and month-on-month refers to comparison with the previous adjacent period.

[0128] For example, assuming that the plurality of index combinations include: index combination one (the income in June 2020 is 10 and the income in July 2020 is 30), and index combination two (the income in June 2021 is 40 and the income in July 2021 is 30), the plurality of index variables include: 20, -10. Assuming that the plurality of index combinations include: index combination three (the income in June 2020 is 10 and the income in June 2021 is 40), and index combination four (the income in July 2020 is 30 and the income in July 2021 is 30), the plurality of index variables include: 30, 0.

[0129] It can be understood that the server can obtain the business indicators of a plurality of time periods. The server can generate a plurality of index combinations according to the business indicators of the plurality of time periods, the index combination including the business indicators of two time periods with the same time characteristics. For each index combination, the server can generate an index variable according to the index combination to determine the plurality of index variables. In this way, the server uses the business indicators of two time periods with the same time characteristics to obtain the index variable by month-on-month or year-on-year, which can improve the reliability of the index variable, thereby improving the accuracy of determining the influence factors.

[0130] In some embodiments, the method for determining the influence factors can further include: the server can combine at least one influence factor to obtain a plurality of combined factors, the combined factor including at least two influence factors. For each combined factor, the server can determine at least one combined information from the plurality of business information, the combined information being the business information in which the combined factor exists. The server can determine a third influence degree of the combined factor according to a first influence degree corresponding to each combined information in the at least one combined information to determine the third influence degree of each combined factor in the plurality of combined factors.

[0131] In one possible design, the server can sum the first influence values ​​corresponding to each of the at least one combination of information to obtain the third influence value of the combination factor.

[0132] For example, if the combination factor includes social channels and traffic business, and there are three combination information among multiple business information, and the first influence degree corresponding to the combination information is -0.25, 0, and 0.5 respectively, then the third influence degree of the combination factor is 0.25.

[0133] In some embodiments, after the server determines at least one target factor based on the second influence degree of each of the at least one influence factor (S204), the server may also display at least one target factor and the second influence degree corresponding to each target factor.

[0134] In one possible implementation, the server can use a drawing program to display at least one target factor and the second influence degree corresponding to each target factor, with one rectangle corresponding to one target factor, and the size of the rectangle being used to reflect the second influence degree corresponding to the target factor.

[0135] In one possible design, the larger the rectangle, the greater the second influence of the target factor. The smaller the rectangle, the smaller the second influence of the target factor.

[0136] For example, a plotting program can use the `plotly.express` function to draw a treemap. A treemap can reflect the influence of influencing factors through the size of the rectangles, and the influence of the target factor through the shade of the rectangles' color. For instance, a larger rectangle indicates a greater influence of the target factor, and a smaller rectangle indicates a smaller influence; a darker color indicates a greater influence of the target factor, and a lighter color indicates a smaller influence.

[0137] It should be noted that, in this embodiment of the application, the server can display target factors with a positive second influence degree and target factors with a negative second influence degree, respectively. The positive influence degree indicates that the target factor is positively correlated with the business indicator, and the negative influence degree indicates that the target factor is negatively correlated with the business indicator.

[0138] For example, such as Figure 4 As shown, this diagram illustrates a target factor for positive impact. The business indicator is business revenue, and within the social channels, specifically city-level single-store internet business data packages, low-cost data plans have the greatest positive impact on business revenue. For example... Figure 5 As shown, this diagram illustrates a target factor for negative impact. Among these, the negative impact of relocated products is greatest in the relocation business of city-level single stores within social channels.

[0139] It can be understood that the server can display at least one target factor and the second influence degree corresponding to each target factor, so as to facilitate the staff to determine the influence factor having a greater influence degree on the business index.

[0140] The method for determining the influence factor is described below in combination with specific embodiments.

[0141] As shown in the example of FIG. 6, the server can obtain a plurality of business indexes, and the business indexes correspond to at least one influence factor. The server can preprocess the plurality of business indexes to determine a plurality of index variables. The server can calculate a plurality of third influence degrees according to the plurality of index variables, and the third influence degrees are used to indicate the influence degree of the combined factor on the business index. The server can sort the plurality of third influence degrees to obtain a plurality of sorted third influence degrees. The server can draw a graph to display the plurality of third influence degrees. Figure 6 The above mainly describes the scheme provided by the embodiments of the present application from the perspective of the method. In order to realize the above functions, the determination device of the influence factor or the electronic equipment contains the hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that the determination method steps of the influence factor of each example described in combination with the embodiments disclosed in the present application can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driven hardware depends on the specific application and design constraints of the technical scheme. Professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0142] The embodiments of the present application also provide a determination device of an influence factor. The determination device of the influence factor can be a computer device, a CPU in the computer device, a module for determining the influence factor in the computer device, or a client for determining the influence factor in the computer device.

[0143] The embodiments of the present application can divide the functions of the determination of the influence factor according to the above method examples into function modules or function units. For example, each function module or function unit can be divided according to each function, or two or more functions can be integrated into one processing module. The integrated module can be realized in the form of hardware or software function module or function unit. The division of the modules or units in the embodiments of the present application is illustrative, and is only a logical function division. There can be another division mode in actual implementation.

[0144] As shown in the example of FIG. 6, the server can obtain a plurality of business indexes, and the business indexes correspond to at least one influence factor. The server can preprocess the plurality of business indexes to determine a plurality of index variables. The server can calculate a plurality of third influence degrees according to the plurality of index variables, and the third influence degrees are used to indicate the influence degree of the combined factor on the business index. The server can sort the plurality of third influence degrees to obtain a plurality of sorted third influence degrees. The server can draw a graph to display the plurality of third influence degrees.

[0145] Figure 7 ​The diagram shown is a structural schematic of an impact factor determination device provided in an embodiment of this application. The impact factor determination device is used to perform... Figure 2 , Figure 3 and Figure 6 The method for determining the impact factor is shown. The apparatus for determining the impact factor may include: an acquisition module 701 and a processing module 702.

[0146] The acquisition module 701 is used to acquire multiple indicator variables, which are the changes in business indicators over two time periods. Each indicator variable corresponds to at least one influencing factor. The processing module 702 is used to determine a first degree of influence for each indicator variable, thereby determining multiple first degrees of influence. The first degree of influence indicates the extent of influence of at least one influencing factor on the business indicator. The processing module 702 is also used to determine a second degree of influence for each of the at least one influencing factor based on the multiple first degrees of influence. The second degree of influence indicates the extent of influence of the influencing factor on the business indicator. The processing module 702 is further used to determine at least one target factor based on the second degree of influence for each of the at least one influencing factor. The target factor is an influencing factor whose second degree of influence is greater than a preset threshold.

[0147] Optionally, the acquisition module 701 is further configured to acquire business metrics for multiple time periods. The processing module 702 is further configured to generate multiple metric combinations based on the business metrics for multiple time periods, wherein the metric combinations include business metrics for two time periods with the same time characteristics. Specifically, for each metric combination, the processing module 702 is configured to generate metric variables based on the metric combination to determine multiple metric variables.

[0148] Optionally, the two time periods include a first time period and a second time period, with the first time period preceding the second time period. Processing module 702 is further configured to determine the rate of change of indicators based on multiple indicator variables and the business indicators corresponding to each indicator variable in the first time period. Specifically, processing module 702 is configured to determine an indicator benchmark based on the rate of change of indicators and the business indicators corresponding to each indicator variable in the first time period. The indicator benchmark is used to indicate the target change of the business indicator in the two different time periods. Specifically, processing module 702 is configured to determine a target difference based on the indicator variables and the indicator benchmark. The target difference is the difference between the indicator variable and the indicator benchmark. Specifically, processing module 702 is configured to determine a first degree of influence based on the target difference and the business indicators corresponding to each indicator variable in the first time period.

[0149] Optionally, one indicator variable corresponds to one piece of business information, and the business information includes at least one influencing factor. Processing module 702 is further configured to, for each influencing factor, determine a second degree of influence of the influencing factor based on a target operation, thereby determining the second degree of influence of each influencing factor. The target operation includes: processing module 702, specifically configured to determine at least one piece of target information from multiple pieces of business information based on a factor to be measured, where the factor to be measured is any one of the at least one influencing factor, and the target information is the business information containing the factor to be measured. Processing module 702, specifically configured to determine the second degree of influence of the factor to be measured based on a first degree of influence corresponding to each piece of target information.

[0150] Figure 8 This is a schematic diagram of the hardware structure of an apparatus for determining an impact factor according to an exemplary embodiment. The apparatus may include a processor 801, which executes application code to implement the method for determining the impact factor in this application.

[0151] The processor 801 may be a central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present application.

[0152] like Figure 8 As shown, the device for determining the influence factor may further include a memory 802. The memory 802 stores the application code that executes the scheme of this application, and its execution is controlled by the processor 801.

[0153] The memory 802 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magneto-optical disk storage, a magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this. The memory 802 can exist independently and be connected to the processor 801 through the bus 804. The memory 802 can also be integrated with the processor 801.

[0154] As shown in Figure 8 The determination apparatus of the influencing factor can further include a communication interface 803, wherein the processor 801, the memory 802, and the communication interface 803 can be coupled to each other, for example, through the bus 804. The communication interface 803 is configured to interact with other devices, for example, to support the information interaction between the determination apparatus of the influencing factor and other devices.

[0155] It should be noted that the apparatus structure shown in Figure 8 does not constitute a limitation on the determination apparatus of the influencing factor. In addition to the components shown in Figure 8 , the determination apparatus of the influencing factor can include more or fewer components than those shown in the figure, or combine certain components, or arrange different components.

[0156] In actual implementation, the functions implemented by the processing module 702 can be implemented by the processor 801 calling the program codes in the memory 802 as shown in Figure 8 .

[0157] The application further provides a computer readable storage medium, and the computer readable storage medium stores instructions. When the instructions in the computer readable storage medium are executed by a processor of a computer device, the computer is enabled to execute the influence factor determination method provided by the above-mentioned embodiments. For example, the computer readable storage medium can be a memory 802 including instructions, and the above-mentioned instructions can be executed by the processor 801 of the computer device to complete the above-mentioned method. Alternatively, the computer readable storage medium can be a non-transitory computer readable storage medium, for example, the non-transitory computer readable storage medium can be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device and the like.

[0158] Figure 9 A conceptual partial view of a computer program product provided by an embodiment of the application is schematically shown, and the computer program product includes a computer program for executing a computer process on a computing device.

[0159] In one embodiment, the computer program product is provided using a signal bearing medium 900. The signal bearing medium 900 can include one or more program instructions which, when executed by one or more processors, can provide the functionality or some of the functionality described above with respect to Figure 2 、 Figure 3 and Figure 6 . Thus, for example, with reference to the embodiment shown in Figure 2 , one or more features of S201-S204 can be assumed by one or more instructions associated with the signal bearing medium 900. Further, the program instructions in Figure 9 also describe example instructions.

[0160] In some examples, the signal bearing medium 900 can comprise a computer readable medium 901 such as, but not limited to, a hard disk drive, a compact disc (CD), a digital video disc (DVD), a digital tape, memory, read-only memory (ROM), random access memory (RAM), etc.

[0161] In some embodiments, the signal bearing medium 900 can comprise a computer recordable medium 902 such as, but not limited to, a memory, a read / write (R / W) CD, a R / W DVD, etc.

[0162] In some embodiments, the signal bearing medium 900 can comprise a communication medium 903 such as, but not limited to, a digital and / or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communication link, a wireless communication link, etc.).

[0163] The signal-bearing medium 900 can be conveyed by a wireless form of communication media 903. The one or more program instructions can be, for example, computer-executable instructions or logic-implementing instructions.

[0164] In some examples, such as for Figure 7 The described influence factor determination apparatus can be configured to provide various operations, functions, or actions in response to the one or more program instructions of the computer-readable medium 901, the computer-recordable medium 902, and / or the communication medium 903.

[0165] From the above description of the embodiments, it is clear that for the convenience and brevity of description, only the division of the above functional modules is taken as an example for description, and in actual application, the above functions can be completed by different functional modules, i.e., the internal structure of the apparatus is divided into different functional modules to complete the full classification or part of the functions described above.

[0166] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. For example, the apparatus embodiments described above are only illustrative, for example, the division of the modules or units is only a logical function division, and in actual implementation, another division manner can be adopted, for example, a plurality of units or components can be combined or integrated into another apparatus, or some features can be omitted or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, apparatuses or units, and can be electrical, mechanical or other forms.

[0167] The units described as separate components can or can not be physically separate, and the components displayed as units can be one physical unit or a plurality of physical units, i.e., can be located in one place, or can be distributed to a plurality of different places. Part or all of the classification units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0168] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The above integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0169] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application essentially or say the part that contributes to the prior art or the whole classification part or part of the technical solutions can be embodied in the form of a software product. The software product is stored in a storage medium, including a plurality of instructions to make a device (which can be a single-chip microcomputer, a chip, etc.) or a processor execute the whole classification part or part of the steps of the method of each embodiment of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various storage medium capable of storing program codes.

[0170] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any change or replacement within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of determining an influence factor, characterized by, The method comprises: obtaining a plurality of index variables, the index variable being a variation amount of a business index in two time periods, the index variable corresponding to at least one influencing factor; the two time periods comprising: a first time period and a second time period, the first time period being earlier than the second time period; determining an index change rate according to a plurality of index variables and a business index in the first time period corresponding to each index variable; for each index variable, determining a first influence degree according to the index variable to determine a plurality of first influence degrees, the first influence degree being used to indicate an influence degree of the at least one influencing factor on the business index; determining a second influence degree of each influencing factor in the at least one influencing factor according to a plurality of first influence degrees, the second influence degree being used to indicate an influence degree of the influencing factor on the business index; determining at least one target factor according to the second influence degree of each influencing factor in the at least one influencing factor, the target factor being an influencing factor whose second influence degree is greater than a preset influence degree threshold; wherein the determining a first influence degree according to the index variable comprises: determining an index reference according to an index change rate and a business index in the first time period corresponding to the index variable, the index reference being used to indicate a target variation amount of the business index in the two time periods; determining a target difference value according to the index variable and the index reference, the target difference value being a difference value between the index variable and the index reference; determining the first influence degree according to the target difference value and a business index in the first time period corresponding to each index variable.

2. The method of claim 1, wherein, Before the obtaining a plurality of index variables, the method further comprises: obtaining a plurality of time period business indexes; generating a plurality of index combinations according to the plurality of time period business indexes, the index combination comprising: business indexes of two time periods with the same time characteristics; the obtaining a plurality of index variables comprises: for each index combination, generating the index variable according to the index combination to determine a plurality of index variables.

3. The method according to any one of claims 1-2, characterized in that, One index variable corresponds to one business information, the business information comprising the at least one influencing factor; the determining a second influence degree of each influencing factor in the at least one influencing factor according to a plurality of first influence degrees comprises: for each influencing factor, determining the second influence degree of the influencing factor according to a target operation to determine the second influence degree of each influencing factor; the target operation comprising: determining at least one target information from a plurality of business information based on a to-be-tested factor, the to-be-tested factor being any influencing factor in the at least one influencing factor, the target information being the business information in which the to-be-tested factor exists; determining the second influence degree of the to-be-tested factor according to a first influence degree corresponding to each target information.

4. A device for determining influencing factors, characterized in that, The device comprises: The acquisition module is configured to acquire a plurality of index variables, the index variables being variation amounts of a business index within two time periods, the index variables corresponding to at least one influence factor; the two time periods including a first time period and a second time period, the first time period being earlier than the second time period; The processing module is configured to determine an index change rate according to the plurality of index variables and the business index of the first time period corresponding to each of the index variables; The processing module is further configured to determine, for each of the index variables, a first influence degree according to the index variable, to determine a plurality of first influence degrees, the first influence degree being used to indicate an influence degree of the at least one influence factor on the business index; The processing module is further configured to determine a second influence degree of each of the at least one influence factor according to the plurality of first influence degrees, the second influence degree being used to indicate the influence degree of the influence factor on the business index; The processing module is further configured to determine at least one target factor according to the second influence degree of each of the at least one influence factor, the target factor being an influence factor whose second influence degree is greater than a preset influence degree threshold; The processing module is specifically configured to determine an index benchmark according to the index change rate and the business index of the first time period corresponding to the index variable, the index benchmark being used to indicate a target variation amount of the business index within the two different time periods; The processing module is specifically configured to determine a target difference value according to the index variable and the index benchmark, the target difference value being a difference value between the index variable and the index benchmark; The processing module is specifically configured to determine the first influence degree according to the target difference value and the business index of the first time period corresponding to each of the index variables.

5. The apparatus of claim 4, wherein: The acquisition module is further configured to acquire business indexes of a plurality of time periods; The processing module is further configured to generate a plurality of index combinations according to the business indexes of the plurality of time periods, the index combination including business indexes of two time periods with the same time characteristics; The processing module is specifically configured to generate, for each of the index combinations, the index variable according to the index combination, to determine a plurality of index variables.

6. The apparatus of any one of claims 4-5, wherein, One of the index variables corresponds to one business information, the business information including the at least one influence factor; The processing module is further configured to determine, for each of the influence factors, the second influence degree of the influence factor according to a target operation, to determine the second influence degree of each of the influence factors; the target operation including: The processing module is specifically configured to determine at least one target information from a plurality of the business information based on a to-be-tested factor, the to-be-tested factor being any of the at least one influence factor, the target information being the business information in which the to-be-tested factor exists; The processing module is specifically configured to determine the second influence degree of the to-be-tested factor according to a first influence degree corresponding to each of the target information.

7. An apparatus for determining an influence factor, characterized by The apparatus includes: a processor and a memory; the processor and the memory are coupled. The memory is configured to store one or more programs including computer-executable instructions, and when the influence factor determining apparatus is running, the processor executes the computer-executable instructions stored in the memory to enable the influence factor determining apparatus to perform the influence factor determining method according to any one of claims 1-3.

8. A computer-readable storage medium having stored therein instructions, the computer-readable storage medium comprising: When the computer executes the instructions, the computer performs the influence factor determining method according to any one of claims 1-3.

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