A method and device for investment allocation of marketing information

Abstract

The present application provides a method and device for investment allocation of marketing information, belonging to the technical field of data operation analysis. The method includes: obtaining the historical delivery data of each piece of marketing information; selecting target delivery data from the historical delivery data according to a preset selection method, wherein the target delivery data includes investment cost and new user acquisition traffic; generating a fitting curve based on the target delivery data and determining the inflection point of the fitting curve, wherein the inflection point corresponds to inflection point delivery data, and the inflection point delivery data indicates a reference value of the investment cost of the marketing information; determining a marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data. The present application improves the accuracy of marketing information investment allocation.

Description

Technical Field

[0001] This application relates to the technical field of data operation analysis, and particularly to a method and device for investment allocation of marketing information. Background Art

[0002] Social Media Marketing (SMM) refers to promoting a company's products and services using social media and social networks. With the rapid development of social media platforms, more and more enterprises are currently leveraging social media platforms for brand promotion marketing activities. Social media platforms have gradually become the most important frontiers for consumer communication, consumer insights, and product planting.

[0003] When actually investing in social media marketing, it is not the case that the higher the advertising cost invested, the better the conversion effect will necessarily be. High investment in advertising costs can bring more exposure to advertisers and show exponential growth in the early stage of investment. However, as the advertising continues to be invested, the target audience reached will gradually tend to be stable. At this time, even if more advertising costs are invested, no new reach will be achieved, and it has no actual value for the conversion of advertising effects.

[0004] Currently, the way of marketing investment is to determine whether to continue to increase or decrease marketing investment based on the experience of technicians. However, due to different personnel experiences, it is often impossible to achieve the best reach effect, and the manual method causes inaccurate marketing investment allocation. Summary of the Invention

[0005] The purpose of the embodiments of this application is to provide a method and device for investment allocation of marketing information to solve the problem of inaccurate marketing investment allocation in the manual method. The specific technical solutions are as follows:

[0006] In a first aspect, a method for investment allocation of marketing information is provided. The method includes:

[0007] Obtain the historical delivery data of each piece of marketing information;

[0008] Select target delivery data from the historical delivery data according to a preset selection method, where the target delivery data includes investment cost and new user traffic;

[0009] Generate a fitting curve based on the target delivery data and determine the inflection point of the fitting curve. The inflection point corresponds to inflection point delivery data, and the inflection point delivery data indicates the reference value of the investment cost of marketing information;

[0010] Determine the marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data.

[0011] Optionally, the obtaining of the historical delivery data of each marketing message includes:

[0012] Obtaining the basic delivery data of each marketing message from each social media platform, each e-commerce platform, and each marketing message deliverer;

[0013] Determining the new user acquisition traffic of each marketing message based on the basic delivery data;

[0014] Taking the basic delivery data and the new user acquisition traffic as the historical delivery data of the marketing message.

[0015] Optionally, the selecting of the target delivery data from the historical delivery data according to a preset selection method includes:

[0016] Obtaining a data request, where the data request includes a data statistics dimension and a data presentation dimension;

[0017] Selecting the target delivery data from the historical delivery data according to the data statistics dimension and the data presentation dimension.

[0018] Optionally, the selecting of the target delivery data from the historical delivery data according to the data statistics dimension and the data presentation dimension includes:

[0019] Determining the data statistics dimension according to a first filtering control, where the data statistics dimension indicates the placement of the marketing message; according to the first filtering control, selecting a target placement dimension from the placement dimensions, where the target placement dimension includes the target social media platform for delivering the marketing message, the target KOL level in the target social media platform, or the target channel in the target social media platform;

[0020] The data presentation dimension includes the category of the marketing message. According to the data presentation dimension, determining the target delivery data of at least one category of marketing messages corresponding to the target placement dimension.

[0021] Optionally, the selecting of the target delivery data from the historical delivery data according to the data statistics dimension and the data presentation dimension includes:

[0022] Determining the data statistics dimension according to a second filtering control, where the data statistics dimension indicates the category of the marketing message; according to the second filtering control, selecting a set category dimension from the candidate category dimensions of the marketing message, where the set category dimension includes grass planting marketing or push marketing;

[0023] The data presentation dimension includes the placement of the marketing message. According to the data presentation dimension, determining the target delivery data of the set marketing messages in the set category dimension corresponding to at least one placement.

[0024] Optionally, the determining of the marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data includes:

[0025] Determine the target marketing information of the target category corresponding to the target delivery position dimension;

[0026] Determine the first inflection point of the fitting curve corresponding to the target marketing information;

[0027] Determine the marketing information investment allocation strategy according to the comparison between the actual delivery data of the target marketing information and the inflection point delivery data of the first inflection point.

[0028] Optionally, the determining of the marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data includes:

[0029] Determine the set delivery position of the set marketing information;

[0030] Determine the second inflection point of the fitting curve corresponding to the set delivery position;

[0031] Determine the marketing information investment allocation strategy according to the comparison between the actual delivery data of the set delivery position and the inflection point delivery data of the second inflection point.

[0032] Optionally, determining the marketing information investment allocation strategy according to the comparison between the actual delivery data and the inflection point delivery data includes:

[0033] In the case where the actual investment cost is less than the investment cost reference value, add investment budget;

[0034] In the case where the actual investment cost is greater than or equal to the investment cost reference value, stop or reduce the investment budget. Optionally, the generating of the fitting curve by performing data fitting on the target delivery data and determining the inflection point of the fitting curve includes:

[0035] Obtain the discrete data points of the investment cost and the corresponding new user acquisition traffic;

[0036] Perform non-linear simulation on the discrete data points through a non-linear curve to obtain a fitting curve;

[0037] Perform inflection point calculation on the fitting curve to obtain the inflection point of the fitting curve.

[0038] Optionally, after generating the fitting curve by performing data fitting on the target delivery data, the method further includes:

[0039] Display the fitting curve on a visualization interface, where the abscissa of the fitting curve is the new user acquisition cost and the ordinate of the fitting curve is the new user acquisition traffic;

[0040] When a preset operation on the fitting curve or the inflection point is detected, display the inflection point delivery data of the inflection point, where the inflection point delivery data includes an investment cost reference value and a new user acquisition traffic reference value.

[0041] In a second aspect, an investment allocation device for marketing information is provided. The device includes:

[0042] An acquisition module, configured to acquire the historical delivery data of each piece of marketing information;

[0043] A selection module, configured to select target delivery data from the historical delivery data according to a preset selection method, where the target delivery data includes an investment cost and a new user acquisition traffic;

[0044] A generation module, configured to perform data fitting on the target delivery data to generate a fitting curve, and determine an inflection point of the fitting curve, where the inflection point corresponds to inflection point delivery data, and the inflection point delivery data indicates an investment cost reference value of the marketing information;

[0045] A determination module, configured to determine an investment allocation strategy for marketing information corresponding to the preset selection method according to the inflection point delivery data.

[0046] In a third aspect, an electronic device is provided, including a processor, a communication interface, a memory, and a communication bus. The processor, the communication interface, and the memory communicate with each other through the communication bus;

[0047] The memory is used for storing a computer program;

[0048] The processor is configured to implement the steps of any of the investment allocation methods for marketing information when executing the program stored on the memory.

[0049] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and the computer program implements the steps of any of the investment allocation methods for marketing information when executed by a processor.

[0050] Advantageous effects of the embodiments of the present application:

[0051] This application is applied to the technical field of data capabilities for data operation analysis. An embodiment of this application provides a method for investment allocation of marketing information. The terminal generates a fitting curve using target placement data selected by a preset selection method, determines the inflection point on the fitting curve, and then allocates the marketing information investment according to the inflection point placement data and a preset placement method. By determining the inflection point and then allocating the marketing information investment based on the investment cost reference value at the inflection point, the accuracy of the marketing information investment allocation can be improved compared with allocating investment according to manual experience.

[0052] Of course, it is not necessary for any product or method implementing this application to achieve all the above advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0054] Figure 1 Schematic diagram of the hardware environment for a method of investment allocation of marketing information provided by an embodiment of this application;

[0055] Figure 2 Flowchart of a method for investment allocation of marketing information provided by an embodiment of this application;

[0056] Figure 3 Schematic diagram of the fitting curve in the visualization interface provided by an embodiment of this application;

[0057] Figure 4 Schematic diagram of the inflection point placement data in the visualization interface provided by an embodiment of this application;

[0058] Figure 5 Schematic diagram of the structure of a device for investment allocation of marketing information provided by an embodiment of this application;

[0059] Figure 6 Schematic diagram of the structure of an electronic device provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0060] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts fall within the scope of protection of this application.

[0061] In the following description, suffixes such as "module", "component", or "unit" used to represent elements are only for facilitating the description of the present application and have no specific meaning in themselves. Therefore, "module" and "component" can be used interchangeably.

[0062] To solve the problems mentioned in the background art, according to an aspect of the embodiments of the present application, an embodiment of a method for allocating investment in marketing information is provided.

[0063] Optionally, in the embodiments of the present application, the above method for allocating investment in marketing information can be applied to a Figure 1 hardware environment composed of a terminal 101 and a server 103 as shown in the figure. As Figure 1 shown in the figure, the server 103 is connected to the terminal 101 through a network and can be used to provide services for the terminal or the client installed on the terminal. A database 105 can be set on the server or independently of the server to provide data storage services for the server 103. The above network includes but is not limited to: wide area network, metropolitan area network or local area network. The terminal 101 includes but is not limited to PC, mobile phone, tablet computer, etc.

[0064] A method for allocating investment in marketing information in the embodiments of the present application can be executed by the terminal 101 to determine an investment allocation plan for marketing information.

[0065] Next, in combination with specific implementation manners, a method for allocating investment in marketing information provided by the embodiments of the present application will be described in detail. As Figure 2 shown in the figure, the specific steps are as follows:

[0066] Step 201: Obtain the historical delivery data of each piece of marketing information.

[0067] In the embodiments of the present application, the terminal obtains the historical delivery data of each piece of marketing information. The marketing information can be a delivery post in a social delivery platform, such as a grass-planting post or a promoted post. A grass-planting post refers to an advertising-type grass-planting post on a social media platform. A promoted post refers to a post that has been promoted and marketed for a grass-planting post on various social media platforms. The promoted marketing operation can specifically be fan pass, information flow advertisement, feed flow, etc.

[0068] The historical delivery data includes basic delivery data and new user acquisition traffic. Among them, the basic delivery data is data obtained from social media platforms, e-commerce platforms, and marketing information providers. The new user acquisition traffic is obtained based on the traffic data in the e-commerce platform and the performance index data in the social media platform.

[0069] Step 202: Select target delivery data from the historical delivery data according to a preset selection method.

[0070] Among them, the target delivery data includes investment cost and new user acquisition traffic.

[0071] In the embodiment of the present application, the preset selection method is used to determine the data statistical dimension and the data presentation dimension, that is, to determine the target delivery data of at least one category of marketing information corresponding to the target delivery position dimension, or to set the target delivery data of the set marketing information of the category dimension corresponding to at least one delivery position. The terminal selects the target delivery data from the historical delivery data according to the data statistical dimension and the data presentation dimension, and the target delivery data includes investment cost and new user acquisition traffic.

[0072] Step 203: Generate a fitting curve according to the target delivery data and determine the inflection point of the fitting curve.

[0073] Among them, the inflection point corresponds to inflection point delivery data, and the inflection point delivery data indicates the investment cost reference value of the marketing information.

[0074] In the embodiment of the present application, after the terminal obtains the target delivery data of each piece of marketing information, the target delivery data (investment cost and corresponding new user acquisition traffic) is used as discrete data points, and then the discrete data points are non-linearly simulated by a non-linear curve to obtain a fitting curve of Y = a*ln(x) + b, and then the inflection point of the fitting curve is calculated to obtain the inflection point of the fitting curve. At this inflection point, the new user acquisition traffic brought by the unit investment cost is the largest. Therefore, the inflection point delivery data at this inflection point can be used as the investment cost reference value of the marketing information. Among them, the inflection point calculation method can adopt the discrete function inflection point algorithm, and the present application does not make specific limitations on the inflection point calculation method.

[0075] As an optional implementation manner, after generating a fitting curve according to the target delivery data, the method further includes: displaying the fitting curve on the visualization interface, where the abscissa of the fitting curve is the new user acquisition cost, and the ordinate of the fitting curve is the new user acquisition traffic; when a preset operation on the fitting curve or the inflection point is detected, displaying the inflection point delivery data of the inflection point, where the inflection point delivery data includes the investment cost reference value and the new user acquisition traffic reference value.

[0076] Figure 3 It is a schematic diagram of the interface of the fitting curve. As can be seen from the figure, after the terminal generates the fitting curve, it can display a plane rectangular coordinate system with the new user acquisition cost as the abscissa and the new user acquisition traffic as the ordinate on the visualization interface, and display the fitting curve in this plane rectangular coordinate system. If the terminal detects a preset operation on the fitting curve or the inflection point, it will display the inflection point delivery data of the inflection point at the inflection point, and the inflection point delivery data includes the investment cost reference value and the new user acquisition traffic reference value.

[0077] Among them, the ways for the terminal to display the inflection point delivery data according to the preset operations include, but are not limited to: when the mouse pointer hovers over or clicks on the inflection point, the inflection point delivery data will appear; when clicking on the fitted curve, the inflection point delivery data on this fitted curve will be displayed.

[0078] In addition, when the mouse pointer hovers over any discrete data point in the fitted curve, or clicks on any discrete data point, the discrete point delivery data of this discrete data point can also be displayed.

[0079] Step 204: Determine the marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data.

[0080] In the embodiments of the present application, if the preset selection methods are different, then the statistical dimension and presentation dimension of the fitted curve are also different. The statistical dimension can determine the category of marketing information or the delivery position of marketing information, and the presentation dimension can present the fitted curves of marketing information of a fixed category on different delivery platforms, or present the fitted curves of different categories of marketing information at a fixed delivery position.

[0081] The terminal can determine at least one fitted curve through the preset selection method. For any one fitted curve, the actual investment cost of a certain category of marketing information at a certain delivery position in the actual delivery process can be obtained.

[0082] If the actual investment cost is less than the investment cost reference value, then it is necessary to continue to add investment budget at this delivery position to bring higher new user acquisition traffic and achieve better marketing conversion effects; if the actual investment cost is greater than or equal to the investment cost reference value, then even adding investment budget will not bring a large increase in new user acquisition traffic, and it is necessary to stop or reduce the investment budget.

[0083] In the present application, the terminal uses the target delivery data selected by the preset selection method to generate a fitted curve, determines the inflection points on the fitted curve, and then conducts marketing information investment allocation according to the inflection point delivery data and the preset delivery method. By determining the inflection points in the present application and then conducting marketing information investment allocation based on the investment cost reference value at the inflection points, compared with investment allocation based on manual experience, the accuracy of marketing information investment allocation can be improved.

[0084] As an optional implementation method, obtaining the historical delivery data of each piece of marketing information includes: obtaining the basic delivery data of each piece of marketing information from each social media platform, each e-commerce platform, and each marketing information provider; determining the new user acquisition traffic of each piece of marketing information based on the basic delivery data; using the basic delivery data and the new user acquisition traffic as the historical delivery data of the marketing information.

[0085] In the embodiments of the present application, the basic delivery data of marketing information directly comes from social media platforms, e-commerce platforms, and marketing information providers. The basic delivery data includes, but is not limited to: information name, delivery platform, delivery address, delivery time, information category, investment cost, performance index, data traffic, etc. The terminal obtains all the data traffic in the e-commerce platform, then determines the performance index ratio based on the ratio of the performance index of this marketing information to the performance index of all marketing information, and then takes the product of the data traffic and the performance index ratio as the new user acquisition traffic of this marketing information on the social media platform. The terminal uses the basic delivery data and the new user acquisition traffic as the historical delivery data of the marketing information.

[0086] As an alternative implementation manner, selecting target delivery data from the historical delivery data according to a preset selection method includes: obtaining a data request, where the data request includes a data statistical dimension and a data presentation dimension; selecting the target delivery data from the historical delivery data according to the data statistical dimension and the data presentation dimension.

[0087] The user selects the statistical dimension and the presentation dimension of the data on the visual interface of the terminal, and the terminal selects the target delivery data from the historical delivery data according to the data statistical dimension and the data presentation dimension.

[0088] Among them, the terminal pre-constructs a delivery time sequence data table with an empty content. The terminal generates a structure relationship table according to the basic delivery data, and then establishes a data link between the structure relationship table, the new user acquisition traffic, and the delivery time sequence data table. In this way, as the basic delivery data is updated, the new user acquisition traffic will also be updated accordingly, and the data in the delivery time sequence data table will also be updated accordingly.

[0089] The data in the delivery time sequence data table can be historical delivery data (basic delivery data and new user acquisition traffic), or it can be target delivery data. If the data in the delivery time sequence data table is historical delivery data, then the terminal will determine the data statistical dimension and the data presentation dimension according to the preset selection method after obtaining the delivery time sequence data table. If the data in the delivery time sequence data table is target delivery data, then the terminal first selects the target delivery data through the preset selection method, and then obtains the delivery time sequence data table containing the target delivery data.

[0090] As an alternative implementation manner, selecting target delivery data from the historical delivery data according to the data statistical dimension and the data presentation dimension includes two embodiments.

[0091] In one embodiment, a data statistics dimension is determined according to a first filtering control, and the data statistics dimension indicates the placement location of marketing information; according to the first filtering control, a target placement location dimension is selected from the placement location dimension, where the target placement location dimension includes a target social media platform for placing marketing information, a target KOL (Key Opinion Leader) level in the target social media platform, or a target channel in the target social media platform; the data presentation dimension includes the category of marketing information, and according to the data presentation dimension, target placement data of at least one category of marketing information corresponding to the target placement location dimension is determined.

[0092] In an embodiment of the present application, there is a first filtering control on the visualization interface, and this first filtering control is used to determine the data statistics dimension, that is, the placement location dimension of marketing information. The placement location dimension includes at least one social media platform, at least one KOL level in the social media platform, or at least one channel in the social media platform. The terminal selects a target placement location dimension from the placement location dimension according to the user's filtering operation, and the target placement location dimension includes a target social media platform for placing marketing information, a target KOL level in the target social media platform, or a target channel in the target social media platform.

[0093] After the user determines the target placement location dimension, it is also necessary to determine the data presentation dimension, that is, the category of marketing information. In this way, the terminal can determine the target placement data of at least one category of marketing information placed in the target placement location dimension according to the user's operation.

[0094] Exemplarily, as Figure 3 shown, if the placement location dimension is a social media platform, the specific placement location is Platform A, and the categories of marketing information include influencer planting grass (planting grass posts) and traffic boost (boost posts), then the visualization interface will respectively display the target placement data of influencer planting grass and traffic boost on Platform A, that is, the shorter fitting curve is generated from the target placement data of traffic boost on a certain platform, and the longer fitting curve is generated from the target placement data of influencer planting grass on a certain platform. It can be seen that there is an inflection point (at the circle) in each fitting curve. When the mouse pointer hovers over the inflection point or clicks on the inflection point position, inflection point placement data will appear, as Figure 4 shown, there are two inflection points (a dark inflection point and a light inflection point) in the figure. The single post investment (investment cost reference value) at the investment drainage inflection point (dark inflection point) is 9208.66512534654 yuan, and the new user search volume (new user traffic reference value) is 264.0599283471511.

[0095] In this application, the terminal can determine the target delivery data and fitting curves of different categories of marketing information for the same delivery position according to the statistical dimension of the marketing information delivery position and the presentation dimension of the marketing information category, so as to adopt corresponding investment allocation strategies for different categories of marketing information in this delivery position.

[0096] As an optional implementation manner, determining the marketing information investment allocation strategy corresponding to the preset selection manner according to the inflection point delivery data includes: determining the target marketing information of the target category corresponding to the target delivery position dimension; determining the first inflection point of the fitting curve corresponding to the target marketing information; determining the marketing information investment allocation strategy according to the comparison between the actual delivery data of the target marketing information and the inflection point delivery data of the first inflection point.

[0097] In the embodiment of this application, for at least one category of marketing information corresponding to the target delivery position dimension, the terminal determines the target marketing information of the target category, then generates a corresponding fitting curve for the target delivery data of the target marketing information of the target delivery position, and determines the first inflection point on this fitting curve.

[0098] The terminal compares the actual delivery data of the target marketing information with the inflection point delivery data of the first inflection point, specifically by comparing the investment costs. If the actual investment cost in the actual delivery data is less than the investment cost reference value in the inflection point delivery data, the investment budget is increased; if the actual investment cost is greater than or equal to the investment cost reference value, the investment budget is reduced.

[0099] Exemplarily, Platform A corresponds to two types of marketing information, namely grass-planting posts and push posts. The terminal determines that the target marketing information is grass-planting posts, then the terminal determines the first inflection point of the fitting curve of the grass-planting posts on Platform A. The terminal compares the actual investment cost of the grass-planting posts on Platform A with the investment cost reference value of the grass-planting posts on Platform A, so as to determine whether to increase or reduce the investment budget.

[0100] In another embodiment, selecting the target delivery data from the historical delivery data according to the data statistical dimension and the data presentation dimension includes: determining the data statistical dimension according to the second screening control, and the data statistical dimension indicates the category of the marketing information; selecting the set category dimension from the candidate category dimensions of the marketing information according to the second screening control, where the set category dimension includes grass-planting marketing or push marketing; the data presentation dimension includes the marketing information delivery position, and according to the data presentation dimension, determining the target delivery data of the set marketing information of the set category dimension corresponding to at least one delivery position.

[0101] In the embodiments of the present application, a second filtering control is provided on the visualization interface. This second filtering control is used to determine the data statistical dimension, that is, the category of marketing information. The candidate category dimensions of the marketing information include grass-planting marketing and push marketing. The terminal selects a set category dimension from the candidate category dimensions according to the user's filtering operation. The set category dimension includes grass-planting marketing or push marketing.

[0102] After the user determines the set category dimension of the marketing information, it is also necessary to determine the data presentation dimension, that is, the placement location of the marketing information. In this way, the terminal can determine the target delivery data of the set marketing information of the set category in at least one placement location according to the user's operation.

[0103] Exemplarily, if the set category dimension is a grass-planting post and the placement locations include Platform A, Platform B, and Platform C, then the target delivery data of the grass-planting post on Platform A, Platform B, and Platform C will be displayed on the visualization interface, and the target delivery data of each platform corresponds to a fitting curve.

[0104] In the present application, the terminal can determine the target delivery data and fitting curves of different placement locations for the same category of marketing information according to the statistical dimension of the marketing information category and the presentation dimension of the placement location, so as to adopt corresponding investment allocation strategies for the marketing information of the same category in different placement locations.

[0105] As an alternative implementation, determining the marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data includes: determining the set placement location of the set marketing information; determining the second inflection point of the fitting curve corresponding to the set placement location; and determining the marketing information investment allocation strategy according to the comparison between the actual delivery data of the set placement location and the inflection point delivery data of the second inflection point.

[0106] In the embodiments of the present application, for at least one placement location corresponding to the set marketing information dimension, the terminal determines the set placement location, then determines the target delivery data for the set marketing information and the set placement location, generates a corresponding fitting curve, and determines the second inflection point on this fitting curve. The terminal compares the actual delivery data of the set placement location with the inflection point delivery data of the second inflection point, specifically according to the investment cost. If the actual investment cost in the actual delivery data is less than the investment cost reference value in the inflection point delivery data, the investment budget is increased; if the actual investment cost is greater than or equal to the investment cost reference value, the investment budget is reduced.

[0107] Exemplarily, set the marketing information as a promoted post. The promoted post corresponds to three placement positions on Platform A, Platform B, and Platform C. If the terminal determines that the set placement position is Platform B, then the terminal determines the second inflection point of the fitting curve of the promoted post on Platform B. The terminal compares the actual investment cost of the grass-planting post on Platform B with the reference value of the investment cost of the grass-planting post on Platform B, so as to determine whether to increase or decrease the investment budget.

[0108] As an alternative implementation, before the terminal obtains the historical placement data, it can filter the preset placement data within a preset time period according to the time filtering control on the data dashboard in the visualization interface. Among them, different filtering time dimensions result in different marketing information. The terminal then selects the target placement data from the preset placement data according to the preset selection method. Performing time period filtering can increase the filtering dimension, reduce the data volume calculation, and also make the data filtering more refined.

[0109] Optionally, the embodiment of the present application also provides a processing flow for the investment allocation method of marketing information, and the specific steps are as follows.

[0110] Step 1: Filter the marketing information according to the time filtering control.

[0111] Step 2: Obtain the basic placement data of the marketing information.

[0112] Step 3: Determine the new user acquisition traffic according to the basic placement data.

[0113] Step 4: Use the basic placement data and the new user acquisition traffic as the historical placement data.

[0114] Step 5: Perform secondary filtering according to the data statistical dimension and data presentation dimension corresponding to the preset selection method to obtain the target placement data.

[0115] Step 6: Obtain the fitting curve and the inflection point placement data according to the target placement data.

[0116] Step 7: Determine the investment allocation strategy for the inflection point placement data.

[0117] Based on the same technical concept, the embodiment of the present application also provides an investment allocation device for marketing information, as Figure 5 shown. The device includes:

[0118] An acquisition module 501, configured to acquire the historical placement data of each piece of marketing information;

[0119] A selection module 502, configured to select the target placement data from the historical placement data according to the preset selection method, where the target placement data includes the investment cost and the new user acquisition traffic;

[0120] A generation module 503, configured to perform data fitting on the basis of target placement data to generate a fitting curve, and determine an inflection point of the fitting curve, where the inflection point corresponds to inflection point placement data, and the inflection point placement data indicates a reference value of the investment cost of the marketing information;

[0121] A determination module 504, configured to determine a marketing information investment allocation strategy corresponding to a preset selection method according to the inflection point placement data.

[0122] Optionally, the acquisition module 501 is configured to:

[0123] Obtain the basic placement data of each piece of marketing information from each social media platform, each e-commerce platform, and each marketing information placer;

[0124] Determine the new user acquisition traffic of each piece of marketing information according to the basic placement data;

[0125] Use the basic placement data and the new user acquisition traffic as the historical placement data of the marketing information.

[0126] Optionally, the selection module 502 includes:

[0127] An acquisition unit, configured to acquire a data request, where the data request includes a data statistics dimension and a data presentation dimension;

[0128] A selection unit, configured to select target placement data from the historical placement data according to the data statistics dimension and the data presentation dimension.

[0129] Optionally, the selection unit is configured to:

[0130] Determine the data statistics dimension according to a first screening control, where the data statistics dimension indicates the placement position of the marketing information; select a target placement position dimension from the placement position dimension according to the first screening control, where the target placement position dimension includes a target social media platform for placing the marketing information, a target KOL level in the target social media platform, or a target channel in the target social media platform;

[0131] The data presentation dimension includes the category of the marketing information. According to the data presentation dimension, determine the target placement data of at least one category of marketing information corresponding to the target placement position dimension.

[0132] Optionally, the selection unit is further configured to:

[0133] Determine the data statistics dimension according to a second screening control, where the data statistics dimension indicates the category of the marketing information; select a set category dimension from the candidate category dimensions of the marketing information according to the second screening control, where the set category dimension includes grass planting marketing or push marketing;

[0134] The data presentation dimension includes the marketing information delivery position. According to the data presentation dimension, the target delivery data corresponding to the set marketing information of the set category dimension in at least one delivery position is determined.

[0135] Optionally, the determination module 504 is used to:

[0136] Determine the target marketing information of the target category corresponding to the target placement dimension;

[0137] Determine the first inflection point of the fitting curve corresponding to the target marketing information;

[0138] Determine the marketing information investment allocation strategy based on the comparison between the actual delivery data of the target marketing information and the inflection point delivery data of the first inflection point.

[0139] Optionally, the determination module 504 is further configured to:

[0140] Determine the intended placement of marketing information;

[0141] Determine the second inflection point of the fitting curve corresponding to the set placement position;

[0142] The marketing information investment allocation strategy is determined based on the comparison between the actual delivery data of the set delivery position and the inflection point delivery data of the second inflection point.

[0143] Optionally, the determination module 504 is further configured to:

[0144] When the actual investment cost is less than the reference value of investment cost, additional investment budget shall be added;

[0145] When the actual investment cost is greater than or equal to the investment cost reference value, the investment budget is stopped or reduced. Optionally, the generating module 503 is used to:

[0146] Obtain discrete data points of investment cost and corresponding new user traffic;

[0147] The nonlinear curve is used to perform nonlinear simulation on discrete data points to obtain a fitting curve;

[0148] The inflection point of the fitting curve is calculated to obtain the inflection point of the fitting curve.

[0149] Optionally, the device is further configured to:

[0150] The fitting curve is displayed on the visual interface, where the horizontal axis of the fitting curve is the new customer acquisition cost, and the vertical axis of the fitting curve is the new customer acquisition flow;

[0151] When a preset operation on a fitting curve or an inflection point is detected, inflection point delivery data of the inflection point is displayed, wherein the inflection point delivery data includes an investment cost reference value and a new traffic reference value.

[0152] According to another aspect of the embodiments of the present application, the present application provides an electronic device, such as Figure 6 shown, including a memory 603, a processor 601, a communication interface 602, and a communication bus 604. A computer program that can run on the processor 601 is stored in the memory 603. The memory 603 and the processor 601 communicate through the communication interface 602 and the communication bus 604. When the processor 601 executes the computer program, the steps of the above method are implemented.

[0153] The memory and the processor in the above electronic device communicate through the communication bus and the communication interface. The communication bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0154] The memory may include a Random Access Memory (RAM), or may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0155] The above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0156] According to yet another aspect of the embodiments of the present application, there is also provided a computer-readable medium having non-volatile program code executable by a processor.

[0157] Optionally, in the embodiments of the present application, the computer-readable medium is configured to store program code for the processor to execute the above method:

[0158] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and will not be elaborated herein.

[0159] In the specific implementation of the embodiments of the present application, reference may be made to the above respective embodiments, and corresponding technical effects are achieved.

[0160] It can be understood that the embodiments described herein can be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application, or a combination thereof.

[0161] For software implementation, the technologies described herein can be implemented by units that execute the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented within the processor or external to the processor.

[0162] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0163] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0164] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in electrical, mechanical or other forms.

[0165] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0166] In addition, in each embodiment of this application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0167] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of this application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs that can store program codes. It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitations, the element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0168] The above are only specific embodiments of the present application, enabling those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but rather will be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. An investment allocation method for marketing information, characterized in that, The method includes: Obtaining the historical delivery data of each marketing message; Selecting target delivery data from the historical delivery data according to a preset selection method, where the target delivery data includes investment cost and new user acquisition traffic; Performing data fitting on the target delivery data to generate a fitting curve, and determining the inflection point of the fitting curve, where the inflection point corresponds to inflection point delivery data, and the inflection point delivery data indicates the reference value of the investment cost of the marketing message; Determining a marketing message investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data; The new user acquisition traffic is: the terminal obtains all the data traffic in the e-commerce platform; determining a performance index ratio based on the ratio of the performance index of this marketing message to the performance indices of all marketing messages; taking the product of the data traffic and the performance index ratio as the new user acquisition traffic of this marketing message on the social media platform; Among them, the step of selecting target delivery data from the historical delivery data according to a preset selection method includes: obtaining a data request, where the data request includes a data statistics dimension and a data presentation dimension; selecting the target delivery data from the historical delivery data according to the data statistics dimension and the data presentation dimension; Among them, the step of selecting the target delivery data from the historical delivery data according to the data statistics dimension and the data presentation dimension includes: determining the data statistics dimension according to a first screening control, where the data statistics dimension indicates the placement position of the marketing message; selecting a target placement position dimension from the placement position dimension according to the first screening control, where the target placement position dimension includes the target social media platform for delivering the marketing message, the target KOL level in the target social media platform, or the target channel in the target social media platform; the data presentation dimension includes the category of the marketing message, and according to the data presentation dimension, determining the target delivery data of at least one category of marketing messages corresponding to the target placement position dimension; or determining the data statistics dimension according to a second screening control, where the data statistics dimension indicates the category of the marketing message; selecting a set category dimension from the candidate category dimensions of the marketing message according to the second screening control, where the set category dimension includes grass planting marketing or push marketing; the data presentation dimension includes the placement position of the marketing message, and according to the data presentation dimension, determining the target delivery data of the set marketing message corresponding to the set category dimension in at least one placement position.

2. The method according to claim 1, wherein The step of obtaining the historical delivery data of each marketing message includes: Obtaining the basic delivery data of each marketing message from each social media platform, each e-commerce platform, and each marketing message sender; Determining the new user acquisition traffic of each marketing message based on the basic delivery data; Taking the basic delivery data and the new user acquisition traffic as the historical delivery data of the marketing message.

3. The method according to claim 1, wherein The step of determining a marketing message investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data includes: Determining the target marketing messages of the target category corresponding to the target placement position dimension; Determine the first inflection point of the fitting curve corresponding to the target marketing information; Determine the marketing information investment allocation strategy based on the comparison between the actual delivery data of the target marketing information and the inflection point delivery data of the first inflection point.

4. The method according to claim 1, characterized in that The determining the marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data includes: Determine the set delivery position of the set marketing information; Determine the second inflection point of the fitting curve corresponding to the set delivery position; Determine the marketing information investment allocation strategy based on the comparison between the actual delivery data of the set delivery position and the inflection point delivery data of the second inflection point.

5. The method according to claim 3 or 4, characterized in that, Determining the marketing information investment allocation strategy based on the comparison between the actual delivery data and the inflection point delivery data includes: When the actual investment cost is less than the investment cost reference value, increase the investment budget; When the actual investment cost is greater than or equal to the investment cost reference value, stop or reduce the investment budget.

6. The method according to claim 1, wherein The generating a fitting curve by performing data fitting on the target delivery data and determining the inflection point of the fitting curve includes: Obtain the discrete data points of the investment cost and the corresponding new user acquisition traffic; Perform non-linear simulation on the discrete data points through a non-linear curve to obtain a fitting curve; Perform inflection point calculation on the fitting curve to obtain the inflection point of the fitting curve.

7. The method according to claim 1, wherein After generating a fitting curve by performing data fitting on the target delivery data, the method further includes: Display the fitting curve on a visualization interface, where the abscissa of the fitting curve is the new user acquisition cost, and the ordinate of the fitting curve is the new user acquisition traffic; When a preset operation on the fitting curve or the inflection point is detected, display the inflection point delivery data of the inflection point, where the inflection point delivery data includes an investment cost reference value and a new user acquisition traffic reference value.

8. An investment allocation device for marketing information, characterized in that, The device includes: An acquisition module, configured to acquire the historical delivery data of each marketing information; A selection module, configured to select target delivery data from the historical delivery data according to a preset selection method, where the target delivery data includes an investment cost and a new user acquisition traffic; A generation module, configured to generate a fitting curve by performing data fitting on the target delivery data and determine the inflection point of the fitting curve, where the inflection point corresponds to inflection point delivery data, and the inflection point delivery data indicates an investment cost reference value of the marketing information; A determination module, configured to determine the marketing information investment allocation strategy corresponding to the preset selection method according to the inflection point delivery data; The new user acquisition traffic is: the terminal obtains all the data traffic in the e-commerce platform; determine the performance index ratio based on the ratio of the performance index of this marketing information to the performance indexes of all marketing information; use the product of the data traffic and the performance index ratio as the new user acquisition traffic of this marketing information in the social media platform; Wherein, the selection module is configured to: obtain a data request, where the data request includes a data statistics dimension and a data presentation dimension; select the target delivery data from the historical delivery data according to the data statistics dimension and the data presentation dimension; Among them, the selection module is specifically configured to: determine a data statistics dimension according to a first filtering control, where the data statistics dimension indicates a marketing information placement location; select a target placement location dimension from the placement location dimension according to the first filtering control, where the target placement location dimension includes a target social media platform for placing marketing information, a target KOL level in the target social media platform, or a target channel in the target social media platform; the data presentation dimension includes categories of marketing information, and according to the data presentation dimension, determine target placement data of at least one category of marketing information corresponding to the target placement location dimension; or determine a data statistics dimension according to a second filtering control, where the data statistics dimension indicates categories of marketing information; select a set category dimension from the candidate category dimensions of marketing information according to the second filtering control, where the set category dimension includes grass planting marketing or push marketing; the data presentation dimension includes a marketing information placement location, and according to the data presentation dimension, determine target placement data of the set marketing information corresponding to the set category dimension in at least one placement location.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus; The memory is used to store computer programs; The processor is configured to implement the method steps of any one of claims 1-7 when executing the program stored on the memory.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements the method steps of any one of claims 1-7.

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