Advertisement placement effectiveness estimation device

Abstract

To provide an advertisement placement effectiveness estimation device for estimating effectiveness of advertising placements with easy operations compared to conventional technologies.SOLUTION: In an advertisement placement effectiveness estimation device 100, a selection unit 130 selects a multiple regression analysis formula and / or a simple regression analysis formula for which a goodness of fit index for the multiple regression analysis formula and / or the simple regression analysis formula is equal to or greater than a prescribed goodness of fit. A path route generation unit 140 generates path routes between each item such that explanatory variables of the selected multiple regression analysis formula and / or simple regression analysis formula are items of an indirect effect source and an objective variable is an item of an indirect effect destination, and further that the explanatory variables of the multiple regression analysis formula and / or simple regression analysis formula selected by the selection unit are items of a direct effect source and the objective variable is an item of a direct effect destination.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an advertising effectiveness estimation device. [Background technology]

[0002] Patent Document 1 (Republished Publication No. 2005-64511) describes a mode in which one or more types of analysis engines, either a Bayesian network or MTS, are applied to individual consumer data stored in a first storage means and a second storage means that store media plans, the dependency of each advertising plan on the response result is quantified, an advertising plan that is estimated to be effective for the response based on the quantified dependency is extracted, and the media plan stored in the first storage means is updated to match the advertising plan determined to be effective. In other words, Patent Document 1 describes that an effective media plan is obtained by performing a regression analysis based on performance information.

[0003] Patent Document 2 (JP 2021-89485 A) describes a mode in which attribute information of users of a first user group and information on contact with advertisements for a product are used as explanatory variables, and values ​​based on the actions taken by users of the first user group with respect to the product are used as objective variables to generate a trained model by machine learning, and attribute information of users of a second user group and information on contact with advertisements for the product are input to the trained model, and an index value evaluating the possibility that users of the second user group will take the action of the objective variable with respect to the product is output, the index value is associated with users of the second user group, and an advertisement for the product is notified to at least some users of the second user group based on the index value. That is, Patent Document 2 describes that a trained model for predicting a user's response to an advertisement by regression analysis is generated, and an index value is obtained using this model.

[0004] Patent Document 3 (Patent Publication No. 7186316) describes an embodiment of an estimation device that estimates the effect of placing an advertisement for a target product in an information transmission medium, which specifies the degree of contact with the information transmission medium, calculates the appeal of the information transmission medium to the consciousness of the contactee regarding the same type of product as the target product based on the results of a questionnaire from survey subjects including those who contact the information transmission medium, and when a plurality of consciousnesses are set according to the stages until a predetermined action is taken for the same type of product as the target product, sets a weighting coefficient for regression analysis for the consciousness of each stage, calculates the product of the appeal of the consciousness of each stage and the weighting coefficient set for the consciousness of each stage, and estimates the effect for each medium based on the degree of contact and the product calculated for the consciousness of each stage. That is, Patent Document 3 describes that the advertising effect for each medium is estimated by performing regression analysis.

[0005] Patent Document 4 (JP Patent Publication 2002-24692A) describes a mode in which, for advertisements that have already been published or distributed, information indicating individual media in which the advertisements have been specifically published or distributed, the contents of the advertisements, advertising costs, and user reactions to the advertisements are stored in a database, and an advertising plan including advertising periods and budgets for selected individual media is created based on a manuscript from an advertiser and / or advertising agency to which information including advertising periods and budgets has been added so as to maximize user reactions. In other words, Patent Document 4 describes that the advertising effect of each medium is estimated based on performance information.

[0006] Patent Document 5 (JP Patent Publication 2005-190340A) describes a mode in which multiple advertisements are posted on multiple interactive media, reaction parameters related to the target's reaction are measured for each of the multiple advertisements, cognitive parameters related to the recognition of each advertisement are measured for the target, the correlation between the reaction parameters and the cognitive parameters expressed as a function that is a power regression equation is analyzed, and the effectiveness of the advertisement to be placed is predicted based on the correlation obtained in advance. That is, Patent Document 5 describes that the effectiveness of placing an interactive medium is estimated by performing a regression analysis based on performance information. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Republished Publication No. 2005-64511 [Patent Document 2] Patent Publication No. 2021-89485 [Patent Document 3] Patent No. 7186316 [Patent Document 4] JP 2002-24692 A [Patent Document 5] JP 2005-190340 A Summary of the Invention [Problem to be solved by the invention]

[0008] An object of the present invention is to make it possible to estimate the effectiveness of advertising placement with easier operations than in the prior art. [Means for solving the problem]

[0009] The first aspect includes a performance value acquisition unit that acquires a performance value of an advertising medium-specific advertising volume indicating an advertising volume for each advertising medium, a performance value of a response for each advertising medium indicating a response for each advertising medium, and a performance value of a total response obtained by adding up the performance values ​​of the responses for each advertising medium, a regression analysis processing unit that performs analysis processing of a multiple regression analysis formula and / or a simple regression analysis formula having either the total response or the response for each advertising medium as a target variable and one or more advertising medium-specific advertising volumes as explanatory variables based on the performance values ​​acquired by the performance value acquisition unit, and a regression analysis processing unit that performs analysis processing of a multiple regression analysis formula and / or a simple regression analysis formula having an index of goodness of fit of the multiple regression analysis formula and / or the simple regression analysis formula being equal to or greater than a predetermined goodness of fit. the explanatory variables of the multiple regression analysis formula and / or the simple regression analysis formula selected by the selection unit become items of indirect effect sources and the objective variable becomes an item of indirect effect destination, and the explanatory variables of the multiple regression analysis formula and / or the simple regression analysis formula selected by the selection unit become items of direct effect sources and the objective variable becomes an item of direct effect destination, and a path coefficient calculation unit calculates path coefficients between the items of the path routes based on the actual values ​​acquired by the actual value acquisition unit.

[0010] A second aspect is an advertising placement effectiveness estimation device in which, in the first aspect, the regression analysis processing unit analyzes and processes a multiple regression analysis equation and / or a simple regression analysis equation using explanatory variables whose number is limited to a predetermined number that is less than the number of all advertising media.

[0011] A third aspect is an advertising advertising effectiveness estimation device in which, in the first aspect, the total response and the response by advertising medium used in the regression analysis processing unit, the path route generation unit, and the path coefficient calculation unit are subjected to correction processing to remove seasonal influences.

[0012] A fourth aspect is an advertising advertising effectiveness estimation device in which, in the first aspect, the advertising volume by advertising medium used in the regression analysis processing unit, the path route generation unit, and the path coefficient calculation unit is subjected to a correction process to add residual effects.

[0013] A fifth aspect includes a performance value acquisition unit that acquires a performance value of an advertisement volume for each advertisement medium, a performance value of a response for each advertisement medium, and a total performance value of a response obtained by adding up the performance values ​​of the responses;

[0014] The advertising advertising effectiveness estimation device includes a path coefficient output unit that outputs path coefficients between each item, each item being the advertising volume for each advertising medium and the total response, based on the performance values ​​acquired by the performance value acquisition unit; an advertising volume ratio performance value output unit that outputs an advertising volume ratio performance value indicating the ratio of the advertising volume for each advertising medium, based on the performance values ​​acquired by the performance value acquisition unit; an advertising volume ratio change receiving unit that accepts a change to the advertising volume ratio relative to the advertising volume ratio performance value; and a total response increase / decrease output unit that outputs the increase / decrease amount or increase / decrease rate of the total response using the change to the advertising volume ratio accepted by the advertising volume ratio change receiving unit and the path coefficients.

[0015] A sixth aspect is an advertising advertisement effectiveness estimation device according to the fifth aspect, wherein the path coefficient, the advertising volume ratio actual value, and the increase / decrease amount or the increase / decrease rate of the total response are displayed on a screen.

[0016] A seventh aspect is an advertising advertising effectiveness estimation device in which, in the fifth aspect, the total response used in the path coefficient output unit and the total response increase / decrease output unit is subjected to a correction process to remove seasonal influences.

[0017] An eighth aspect is an advertising placement effectiveness estimation device according to the fifth aspect, wherein the placement volume of each advertising medium used in the placement volume ratio actual value output unit is subjected to a correction process that adds a residual effect. Effect of the Invention

[0018] According to the first to eighth aspects, the effectiveness of advertising placement can be estimated with simple operations as compared with the conventional techniques. [Brief description of the drawings]

[0019] [Figure 1]FIG. 1 is a block diagram showing a functional configuration of an advertising effectiveness estimation device according to the first embodiment. [Diagram 2] FIG. 2 is a block diagram showing a functional configuration of an advertising effectiveness estimation device according to the second embodiment. [Diagram 3] FIG. 3 is a configuration diagram of one or more personal computer terminals, a server, and a network that communicatively connects the personal computer terminals and the server according to the embodiment. [Figure 4] FIG. 4 is a diagram showing a hardware configuration for realizing the functional configuration of the embodiment. [Diagram 5] FIG. 5 is a flowchart showing a processing procedure of a program for estimating the effectiveness of advertising, which realizes the functions of the advertising effectiveness estimation device of the first embodiment. [Figure 6] FIG. 6 is a flowchart showing a processing procedure of a program for estimating the effectiveness of advertising, which realizes the functions of the advertising effectiveness estimation device according to the second embodiment. [Figure 7A] FIG. 7A is a diagram illustrating an example of a performance value acquisition screen displayed on the display screen of the display device of the terminal. [Figure 7B] FIG. 7B is a diagram illustrating an example of a performance value acquisition screen displayed on the display screen of the display device of the terminal. [Figure 8] FIG. 8 is a diagram illustrating an example of a path route screen displayed on the display screen of the display device of the terminal. [Figure 9] 9(A) and (B) are diagrams illustrating examples of path coefficient screens displayed on the display screen of the display device of a terminal. [Figure 10] 10(A) and 10(B) are diagrams illustrating an example of an information contact path evaluation screen displayed on the display screen of a display device of a terminal. [Figure 11A] FIG. 11A is a diagram illustrating an example of an advertising volume ratio change acceptance screen displayed on the display screen of a display device of a terminal, showing an initial state in which no change in the advertising volume ratio has been accepted. [Figure 11B] FIG. 11B is a diagram illustrating an example of an advertisement volume ratio change acceptance screen displayed on the display screen of the display device of the terminal, showing a state in which a change in the advertisement volume ratio has been accepted. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0021] (Functional configuration of the advertising effectiveness estimation device)

[0022] FIG. 1 is a block diagram showing a functional configuration of an advertising effectiveness estimation device 100 according to the first embodiment.

[0023] The advertising placement effect estimation device 100 of the first embodiment includes a performance value acquisition unit 110, a regression analysis processing unit 120, a selection unit 130, a path route generation unit 140, and a path coefficient calculation unit 150.

[0024] FIG. 2 is a block diagram showing a functional configuration of an advertising placement effect estimation device 200 according to the second embodiment.

[0025] The advertising placement effect estimation device 200 of the second embodiment is configured to include a performance value acquisition unit 110, a path coefficient output unit 160, an advertising placement volume ratio performance value output unit 170, an advertising placement volume ratio change receiving unit 180, and a total response increase / decrease output unit 190.

[0026] 1 and 2 can be realized by a combination of one or more personal computer terminals 60, a server 70, and a network 80 that communicatively connects the personal computer terminals 60 and the server 70, as shown in Fig. 3. Alternatively, the functions of the personal computer terminal 60 alone can be realized.

[0027] (Hardware configuration)

[0028] Fig. 4 is a diagram showing a hardware configuration for realizing the functional configuration of the embodiment shown in Fig. 1 and Fig. 2. The hardware configuration of the personal computer terminal 60 or the server 70 is illustrated.

[0029] As shown in FIG. 4, a personal computer terminal 60 or a server 70 includes a CPU (Central Processing Unit) 61, a ROM (Read Only Memory) 62, a RAM (Random Access Memory) 63, storage 64, an input device 66, a display device 67, a communication I / F 68, and an external storage device 69, which are connected to each other so as to be able to communicate with each other via a system bus 65.

[0030] The CPU 61 is a central processing unit, and executes various programs and controls each device connected to the system bus 65. That is, the CPU 61 reads a program from the ROM 62 or the storage 64, and executes the program using the RAM 63 as a working area. The CPU 61 controls each device connected to the system bus 65 and performs various arithmetic processing according to the program recorded in the ROM 62 or the storage 64. The ROM 62 or the storage 64 holds a BIOS (Basic Input / Output System) and an OS (Operating System), which are control programs executed by the CPU 61, as well as various computer-readable and executable programs and various necessary data for realizing this embodiment.

[0031] The ROM 62 stores various control programs and various data. The RAM 63 functions as a main memory, work area, etc. for the CPU 61 and temporarily stores programs or data as a working area. The storage 64 is configured with an HDD (Hard Disk Drive) or SSD (Solid State Drive) and stores various programs including the BIOS and OS, and various data.

[0032] The input device 66 includes a pointing device such as a mouse, a keyboard, and a reading device such as a scanner, and is used to perform various input operations.

[0033] The display device 67 is, for example, a liquid crystal display, and displays various information. The display device 67 may function as the input device 66 by adopting a touch panel system.

[0034] The communication interface 68 is an interface for communicating with other devices such as the server 70 and the terminal 60, and uses standards such as Ethernet (registered trademark), FDDI, and Wi-Fi (registered trademark). The communication interface 68 connects to a network 80 and controls the transmission and reception of data.

[0035] The external storage device 69 is composed of various types of memory cards such as a USB memory, an HDD, an SSD, or other external storage media that can be detachably connected.

[0036] (Program for estimating advertising effectiveness)

[0037] 5 is a flowchart showing the processing procedure of the program PB1 for estimating the effectiveness of advertising, which realizes the functions of the advertising effectiveness estimation device 100 of the first embodiment. The program PB1 for estimating the effectiveness of advertising causes a computer to execute a performance value acquisition process S11, a regression analysis process S12, a selection process S13, a path route generation process S14, and a path coefficient calculation process S15. The performance value acquisition process S11 corresponds to the process performed by the performance value acquisition unit 110. The regression analysis process S12 corresponds to the process performed by the regression analysis processing unit 120. The selection process S13 corresponds to the process performed by the selection unit 130. The path route generation process S14 corresponds to the process performed by the path route generation unit 140. The path coefficient calculation process S15 corresponds to the process performed by the path coefficient calculation unit 150.

[0038] FIG. 6 is a flowchart showing the processing procedure of the program PB2 for estimating the effect of advertising, which realizes the function of the advertising effect estimation device 200 of the second embodiment. The program PB2 for estimating the effect of advertising causes a computer to execute a result value acquisition process S11, a path coefficient output process S16, an advertising volume ratio result value output process S17, an advertising volume ratio change acceptance process S18, and a total response increase / decrease output process S19. The result value acquisition process S11 corresponds to the process performed by the result value acquisition unit 110. The path coefficient output process S16 corresponds to the process performed by the path coefficient output unit 160. The advertising volume ratio result value output process S17 corresponds to the process performed by the advertising volume ratio result value output unit 170. The advertising volume ratio change acceptance process S18 corresponds to the process performed by the advertising volume ratio change acceptance unit 180. The total response increase / decrease output process S19 corresponds to the process performed by the total response increase / decrease output unit 190.

[0039] The programs PB1 and PB2 are stored in the ROM 62, the storage 64, or the external storage device 69. The personal computer terminal 60 or the server 70 reads out the programs PB1 and PB2 from the ROM 62, the storage 64, or the external storage device 69 and executes the above-mentioned processes.

[0040] Whether the above processes S11 to S19 are performed by the personal computer terminal 60 or the server 70 can be determined arbitrarily depending on the system configuration. For example, the programs PB1 and PB2 may be installed in the personal computer terminal 60, and the programs PB1 and PB2 may be executed by the personal computer terminal 60 alone. Also, for example, the server 70 may be accessed from the personal computer terminal 60 via the network 80, and the processes of the programs PB1 and PB2 may be executed by both the personal computer terminal 60 and the server 70.

[0041] Each embodiment will be described below.

[0042] (First embodiment)

[0043] The advertising placement effect estimation device 100 of the first embodiment includes a performance value acquisition unit 110, a regression analysis processing unit 120, a selection unit 130, a path route generation unit 140, and a path coefficient calculation unit 150, and executes a program PB1 having the processing procedure shown in FIG.

[0044] (Actual value acquisition process S11 in the actual value acquisition unit 110)

[0045] The actual value acquisition unit 110 acquires actual values ​​W1, W2, W3, W4, W5, W6, W7, W8, and W9 of advertising volume by advertising medium indicating the advertising volume for each advertising medium 1, 2, 3, 4, 5, 6, 7, 8, and 9, an actual value W0 of total advertising volume obtained by adding up the actual values ​​W1 to W9 of advertising volume by advertising medium, actual values ​​Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9 of response by advertising medium indicating the response for each advertising medium, and an actual value Z0 of total response obtained by adding up the actual values ​​Z1 to Z9 of response by advertising medium (S11).

[0046] 7A and 7B respectively show examples of performance value acquisition screens 51A and 51B displayed on the display screen of the display device 67 of the personal computer terminal (hereinafter referred to as the terminal) 10. The performance value acquisition screens 51A and 51B are configured as interface screens equipped with the function of the performance value acquisition unit 110. For example, by performing an operation on the performance value acquisition screen 51A shown in FIG. 7A to acquire the performance values ​​W1, W2, W3, W4, W5, W6, W7, W8, and W9 of the advertising volume by advertising medium and the performance value W0 of the total advertising volume, the acquired performance values ​​W1, W2, W3, W4, W5, W6, W7, W8, and W9 of the advertising volume by advertising medium and the numerical value of the total advertising volume W0 (indicated by "···" on the screen) are displayed by year and month on the performance value acquisition screen 51A. For example, the numerical values ​​W1, W2, W3, W4, W5, W6, W7, W8, and W9 of monthly advertising volume by advertising medium for the past few years (3 years (36 months)) and the numerical value W0 of the total advertising volume are read from a database (not shown) in the server 70 and displayed on the actual value acquisition screen 51A. Note that "..." in the cells in the table in Fig. 7A indicates a specific numerical value. The same applies to the other drawings.

[0047] Similarly, by performing an operation to acquire the actual response values ​​Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9 by advertising medium and the actual response value Z0 of the total on the actual value acquisition screen 51B shown in Fig. 7B, the acquired actual response values ​​Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9 by advertising medium and the numerical value of the actual response value Z0 of the total (indicated by "···" on the screen) are displayed by year and month on the actual value acquisition screen 51B. For example, the actual response values ​​Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9 by advertising medium for each month for the past several years (3 years (36 months)) and the numerical value of the actual response value Z0 of the total are read from a database (not shown) of the server 70 and displayed on the actual value acquisition screen 51B.

[0048] Here, the variables of the amount of advertising for each advertising medium 1, 2, 3, 4, 5, 6, 7, 8, and 9 are defined as X1, X2, X3, X4, X5, X6, X7, X8, and X9, respectively. The response variables of the products and services targeted for advertising are defined as Y1, Y2, Y3, Y4, Y5, Y6, Y7, Y8, and Y9. The amount of advertising is used to mean the number of advertisements and the amount of advertising. The response is used to mean the amount of orders, the number of orders, the amount of orders, the number of site referrals, and the number of searches. The response may also be set to the number of clicks, the number of registrations, and other user actions that lead to profits from the target of advertising, known as conversions. The unit of the amount of orders is, for example, Japanese yen.

[0049] Each of the advertising media 1, 2, 3, 4, 5, 7, 8, and 9 is, for example, television, newspaper, radio, magazine, flyer, enclosed, listing advertisement, display advertisement, and other measures. These are only examples, and the advertising media can be arbitrarily selected and combined as long as they are media capable of placing advertisements. For example, when the advertising media is newspaper advertisements, advertisements from different newspapers or different regions may be selected and combined, and different publication formats such as publication size, monochrome advertisement, and color advertisement may be selected and combined. Also, for example, when the advertising media is television broadcast advertisements, advertisements in different broadcast formats such as terrestrial television broadcasts, satellite broadcasts, and cable broadcasts may be selected and combined, and specific or arbitrary television commercials or television programs may be selected and combined. Also, for example, when the advertising media is radio broadcast advertisements, for example, arbitrary radio commercials or radio programs may be selected and combined. Also, for example, when the advertising media is Internet advertisements, for example, specific or arbitrary digital advertisements, websites, SNS, and application software installed on information terminals such as smartphones and personal computers may be selected and combined. Also, for example, when the advertising medium is outdoor advertising, it is possible to select and combine billboards, digital signage, and in-vehicle advertising in various mobile media such as trains, buses, and automobiles. Any one of newspaper advertising, television broadcast advertising, radio broadcast advertising, Internet advertising, and outdoor advertising may be selected, or two or more may be selected and combined.

[0050] The actual values ​​W1, W2, W3, W4, W5, W6, W7, W8, and W9 of advertising volume by advertising medium respectively show the values ​​obtained by substituting the past advertising volumes into the variables X1, X2, X3, X4, X5, X6, X7, X8, and X9 of advertising volume for advertising medium 1, 2, 3, 4, 5, 6, 7, 8, and 9. The actual values ​​Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9 of response by advertising medium respectively show the values ​​obtained by substituting the past response count and volume into the response variables Y1, Y2, Y3, Y4, Y5, Y6, Y7, Y8, and Y9 for advertising medium 1, 2, 3, 4, 5, 6, 7, 8, and 9. The actual value Z0 of total response shows the value obtained by substituting the past total response count and volume into the total response variable Y0.

[0051] (Regression analysis process S12 in regression analysis processing unit 120)

[0052] Based on the actual values ​​acquired by the actual value acquisition unit 110, the regression analysis processing unit 120 performs analysis processing using a multiple regression analysis equation and / or a simple regression analysis equation with either the total response or the response by advertising medium as the objective variable and one or more advertising volumes by advertising medium as the explanatory variables (S12).

[0053] For example, the multiple regression analysis formula and the simple regression analysis formula can be analyzed under the following conditions.

[0054] Condition 1) The explanatory variables are the advertising volume by advertising medium corresponding to up to three of advertising media 1 to 9, and a multiple regression analysis equation and a simple regression analysis equation are obtained for all combinations in which the total response or the response by advertising medium corresponding to any advertising medium is used as the objective variable.

[0055] Although the number of explanatory variables used in the multiple regression analysis formula is limited to 3 or less, the number of explanatory variables used in the multiple regression analysis formula may be limited to any predetermined number less than the total number of advertising media (9).

[0056] A multiple regression analysis equation is generally expressed by the following equation (1), with β as the objective variable and α1, α2, and α3 as explanatory variables.

[0057] β=b0+b1·α1+b2·α2+b3·α3···(1)

[0058] A simple regression analysis equation is generally expressed by the following equation (2), with β as the dependent variable and α1 as the explanatory variable.

[0059] β = b0 + b1 α1 (2)

[0060] The regression coefficients b0, b1, b2, and b3 are calculated by applying the least squares method to the data of the actual advertising volume values ​​by advertising medium W1, W2, W3, W4, W5, W6, W7, W8, and W9, the actual response values ​​by advertising medium Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, and Z9, and the total response value Z0. For example, the regression coefficients b0, b1, b2, and b3 that minimize the average squared error between the actually observed value of the objective variable and the estimated value (theoretical value) calculated by applying the multiple regression analysis formula are calculated.

[0061] For example, as shown in equation (3) below, a multiple regression analysis equation can be derived in which the advertising volume by advertising medium X4 corresponding to advertising medium 4 (magazines) and the advertising volume by advertising medium X8 corresponding to advertising medium 8 (display advertising) are used as explanatory variables, and the response by advertising medium Y1 corresponding to advertising medium 1 (television) is used as the objective variable.

[0062] Y1 = b0 + b1 · X4 + b2 · Y8 · (3)

[0063] Also, for example, as shown in equation (4) below, a multiple regression analysis equation can be derived in which the advertising volume by advertising medium X1 corresponding to advertising medium 1 (television), the advertising volume by advertising medium X2 corresponding to advertising medium 2 (newspapers), and the advertising volume by advertising medium X3 corresponding to advertising medium 3 (radio) are used as explanatory variables, and the total response Y0 is used as the objective variable.

[0064] Y0=b0+b1·X1+b2·X2+b3·X3 (4)

[0065] Also, for example, as in equation (5) below, a simple regression analysis equation can be obtained with the advertising medium-specific advertising volume X3 corresponding to advertising medium 3 (radio) as the explanatory variable and the total response Y0 as the objective variable.

[0066] Y0 = b0 + b1 · X3 · (5)

[0067] (Selection process S13 in the selection unit 130)

[0068] The selection unit 130 selects the multiple regression analysis formula and / or the simple regression analysis formula for which the index of goodness of fit of the multiple regression analysis formula and / or the simple regression analysis formula is equal to or greater than a predetermined goodness of fit (S13).

[0069] The index of goodness of fit here is an index for evaluating the degree of agreement between the predicted value of the dependent variable obtained by regression analysis and the actual value of the dependent variable, and for example, the coefficient of determination R2 can be used.

[0070] For example, among the multiple regression analysis formula and the simple regression analysis formula obtained in the regression analysis process S12,

[0071] Coefficient of determination R2 ≧ 0.45 (6)

[0072] A multiple regression analysis formula and a simple regression analysis formula in which the above formulas are satisfied are extracted, and advertising media corresponding to the explanatory variables in the extracted multiple regression analysis formula and simple regression analysis formula are selected. The coefficient of determination R2 being equal to or greater than the threshold value of 0.45 indicates that the multiple regression analysis formula and the simple regression analysis formula can explain 45% or more of the objective variable with the explanatory variables. The coefficient of determination R2 is calculated by dividing the regression variation by the total variation. As an index of goodness of fit, in addition to the coefficient of determination R2, the coefficient of determination adjusted for the degrees of freedom (coefficient of determination corrected for the degrees of freedom) R2f or the multiple correlation coefficient R may also be used.

[0073] For example, if the multiple regression analysis formulas shown in (3) and (4), and the simple regression analysis formula shown in (5) satisfy the condition shown in (6), these multiple regression analysis formulas shown in (3), (4), and the simple regression analysis formula shown in (5) will be selected for generating a path route.

[0074] (Path route generation process S14 in the path route generation unit 140)

[0075] The path route generation unit 140 generates path routes between each item so that the explanatory variables of the multiple regression analysis equation and / or the simple regression analysis equation selected by the selection unit 130 become the items of the indirect effect source and the objective variable becomes the item of the indirect effect destination, and the explanatory variables of the multiple regression analysis equation and / or the simple regression analysis equation selected by the selection unit 130 become the items of the direct effect source and the objective variable becomes the item of the direct effect destination (S14).

[0076] FIG. 8 illustrates an example of a path route screen 52 displayed on the display screen of the display device 67 of the terminal 10. As shown in FIG.

[0077] The path route screen 52 displays the path route PA generated by the path route generation process S14.

[0078] In FIG. 8, paths in the path route PA are indicated by arrows "→" and items (variables) are indicated by "□".

[0079] The multiple regression analysis formulas shown in (3) and (4) and the simple regression analysis formula shown in (5) will be taken as examples for explanation.

[0080] The advertising volume by advertising medium corresponding to the explanatory variables in equation (3) (Y1=b0+b1·X4+b2·Y8) are X4 (magazines) and X8 (display advertising), and the response by advertising medium corresponding to the objective variable is Y1 (television). Therefore, an indirect path P1 is generated with advertising volume by advertising medium X4 (magazines) and X8 (display advertising) as the indirect effect source items, and advertising volume by advertising medium X1 (television) as the indirect effect destination item. As shown in Figure 8, an indirect path P1 is generated with the start point of the path arrow "→" being the indirect effect source items X4 (magazines) and X8 (display advertising), and the end point of the path arrow "→" being the indirect effect destination item X1 (television).

[0081] Similarly, the advertising volumes by advertising medium corresponding to the explanatory variables in equation (4) (Y0=b0+b1·X1+b2·X2+b3·X3) are X1 (television), X2 (newspapers), and X3 (radio), while the total response Y0 corresponds to the objective variable. Therefore, a direct path P2 is generated with the advertising volumes by advertising medium X1 (television), X2 (newspapers), and X3 (radio) as the direct effect source items, and the total response Y0 as the direct effect destination item. As shown in Figure 8, a direct path P2 is generated with the start point of the path arrow "→" being the direct effect source items X1 (television), X2 (newspapers), and X3 (radio), and the end point of the path arrow "→" being the direct effect destination item Y0 (total response).

[0082] Similarly, the advertising volume by advertising medium that corresponds to the explanatory variable in equation (5) (Y0 = b0 + b1 · X3) is X3 (radio), and the total response Y0 corresponds to the objective variable. Therefore, a direct path P3 is generated in which the advertising volume by advertising medium X3 (radio) is the direct effect source item and the total response Y0 is the direct effect destination item. As shown in Figure 8, a direct path P3 is generated in which the start point of the path arrow "→" is the direct effect source item X3 (radio) and the end point of the path arrow "→" is the direct effect destination item Y0 (total response).

[0083] Similarly, paths are formed according to the multiple regression analysis formula and / or the simple regression analysis formula selected by the selection unit 130 .

[0084] Furthermore, in this embodiment, a path is generated on the assumption that the path route includes an item for unknown factor U. Note that an implementation in which the item for unknown factor U is omitted is also possible.

[0085] (Path coefficient calculation process S15 in the path coefficient calculation unit 150)

[0086] The path coefficient calculation unit 150 calculates path coefficients for paths between each item of the path route PA based on the performance values ​​acquired by the performance value acquisition unit 110 (S15).

[0087] For example, the path coefficients are calculated by SEM. The path coefficients may be standard partial regression coefficients or partial regression coefficients from multiple regression analysis.

[0088] 9(A) and (B) show an example of the pass coefficient screen 53 displayed on the display screen of the display device 67 of the terminal 10. FIG.

[0089] The path coefficient screen 53 includes a path coefficient display section 53A and a path coefficient detail display section 53B.

[0090] As shown in FIG. 9(A), path coefficient display section 53A displays, for each advertising medium 1 (television), 2 (newspaper), 3 (radio), 4 (magazine), 5 (flyer), 6 (enclosed), 7 (listing ad), 8 (display ad), 9 (other measures), and for each unknown factor U, the numerical value of the path coefficient (direct effect) of the direct path, the numerical value of the path coefficient (indirect effect) of the indirect path, and the numerical value of the path coefficient (total effect) obtained by adding the path coefficient of the direct path and the path coefficient of the indirect path.

[0091] As shown in Fig. 9(B), the path coefficient detail display section 53B displays the numerical values ​​of the path coefficients in the paths between the items of the path route PA. The column items in Fig. 9(B) correspond to the items at the start points of the path arrows "→", and the row items in Fig. 9(B) correspond to the items at the end points of the path arrows "→".

[0092] For example, the path coefficient (direct effect) of the direct path P4 of the advertising medium 4 (magazine) is EN1 (-0.077). The path coefficient (indirect effect) of the indirect path P5 of the advertising medium 4 (magazine) is EN2 (0.320) for the indirect path P41 from the item of the advertising medium-specific advertising amount X4 (magazine) to the item of the advertising medium-specific advertising amount X1 (television), and the path coefficient of the direct path P10 from the item of the advertising medium-specific advertising amount X1 (television) to the item of the total response Y0 is EN3 (0.148), so that it can be calculated as EN4 (0.047) by multiplying these path coefficients EN2 (0.320) and EN3 (0.148). The direct effect and indirect effect of each of the other advertising media are calculated in the same manner and displayed in the path coefficient display section 53A.

[0093] 10(A) and (B) show an example of an information contact path evaluation screen 54 displayed on the display screen of the display device 67 of the terminal 10. FIG.

[0094] The information contact path evaluation screen 54 includes an influence degree upper path display section 54A and an influence degree lower path display section 54B.

[0095] As shown in FIG. 10(A), the top influence path display section 54A displays the top (e.g., top 10 paths) with the highest influence (direct effect or indirect effect) among the information contact paths leading to the items of the total response Y0.

[0096] As shown in FIG. 10(B), the influence lower-level path display section 54B displays the top information contact paths (e.g., the bottom 10 paths) with the lowest influence (direct effect or indirect effect) among the information contact paths leading to the items of the total response Y0.

[0097] For example, as shown in Figure 10(A), the influence (indirect effect) of information contact path P5 from the item of advertising volume by advertising medium X4 (magazines) through the item of advertising volume by advertising medium X1 (television) to the item of total response Y0 is EN4 (0.047), and the influence is evaluated to be in the top five.

[0098] Also, as shown in Figure 10 (B), the influence (direct effect) of the information contact path P4 from the item of advertising volume by advertising medium X4 (magazines) to the item of total response Y0 is EN1 (-0.077), and the influence is evaluated to be third in the bottom.

[0099] Generally, when performing path analysis, it is necessary to make a hypothesis of the causal relationship between each item (variable) of the path route. However, according to the first embodiment, it is possible to estimate the direct effect, indirect effect, and total effect of each advertising medium simply by performing an operation to obtain the past advertising volume and response performance value of each advertising medium.

[0100] Since the total response Y0 and the responses by advertising medium Y1 to Y9 are seasonal, seasonal adjustments may be made.

[0101] That is, the total response Y0 and the responses Y1 to Y9 by advertising medium used in the regression analysis processing unit 120, the path route generating unit 140, and the path coefficient calculating unit 15 may be corrected to remove seasonal influences.

[0102] For example, the seasonal influence can be removed by calculating the seasonal index Si using an analytical method based on the EPA (Economic Planning Agency) method and multiplying the total response Y0 and the responses by advertising medium Y1 to Y9 by this seasonal index Si.

[0103] The total response Y0 and the responses Y1 to Y9 by advertising medium may be influenced more by the residual effect of the advertising medium-specific advertising amounts X1 to X9 than by the advertising medium-specific advertising amounts X1 to X9 themselves. Therefore, a correction process may be performed to add the residual effect to the advertising medium-specific advertising amounts X1 to X9 used by the regression analysis processing unit 120, the path route generation unit 140, and the path coefficient calculation unit 15.

[0104] The residual effect size Amt for advertising medium m (= 1, 2, 3, 4, 5, 6, 7, 8, 9) in period t is expressed by the following equation (7).

[0105] Amt= λ·Xmt +(1-λ)·Am(t-1) ···(7)

[0106] In the above formula (7), t is

[0107] t=1, 2,..., n...(8)

[0108] and indicates the number of periods. Xmt indicates the amount of advertising for advertising medium m in period t. λ indicates the survival rate (forgetting rate, decay rate) and takes the following range.

[0109] 0≦λ≦1 (9)

[0110] The residual rate λ can be calculated as a value that maximizes the time-series correlation between the total response Y0, the responses Y1 to Y9 by advertising medium, and the residual effect amount Amt, for example.

[0111] When performing multiple regression analysis taking residual effects into account, for example, the above formula (3) (Y1=b0+b1·X4+b2·Y8) can be rewritten as the following formula (3´):

[0112] Y1t=b0+b1·A4t +b2·A8t ···(3)´

[0113] In equation (3), Y1t represents the response by advertising medium 1 (television) in period t. The same applies to simple regression analysis.

[0114] Second embodiment

[0115] The advertising effectiveness estimation device 200 of the second embodiment includes a performance value acquisition unit 110, a path coefficient output unit 160, an advertising volume ratio performance value output unit 170, an advertising volume ratio change reception unit 180, and a total response increase / decrease output unit 190, and executes a program PB2 having the processing procedure shown in Figure 6.

[0116] In the following, the description of processes that overlap with the processes in the first embodiment will be omitted as appropriate.

[0117] (Actual value acquisition process S11 in the actual value acquisition unit 110)

[0118] The same process as the result value acquisition process S11 in the first embodiment is executed.

[0119] That is, as shown in Figures 7A and 7B, when an operation is performed on the display screen of the display device 67 of the terminal 10 to obtain the past advertising volume and actual response values ​​of each advertising medium, the past advertising volume and actual response values ​​of each advertising medium are displayed.

[0120] (Path coefficient output process S16 in the path coefficient output unit 160)

[0121] The path coefficient output unit 160 outputs path coefficients between each item, the items being the advertising volume and the total response for each advertising medium, based on the performance values ​​acquired by the performance value acquisition unit 110 (S16).

[0122] For example, the same processes as the regression analysis process S12, the selection process S13, the path route generation process S14, and the path coefficient calculation process S15 in the first embodiment are executed to calculate the path coefficients between each item, which is the amount of advertising for each advertising medium and the total number of responses. The calculated path coefficients are displayed on the display screen of the display device 67 of the terminal 10.

[0123] For example, as shown in FIGS. 9(A) and (B), the path coefficients between each item, with the advertising volume and the total response for each advertising medium being the items, are displayed on the display screen of the display device 67 of the terminal 10.

[0124] (Advertising volume ratio result value output process S17 in the advertising volume ratio result value output unit 170)

[0125] The advertising volume ratio actual value output unit 170 outputs an advertising volume ratio actual value indicating the ratio of advertising volumes of the advertising media based on the actual values ​​acquired by the actual value acquisition unit 110 (S17).

[0126] FIG. 11A illustrates an example of an advertising volume ratio change acceptance screen 55 displayed on the display screen of the display device 67 of the terminal 10. As shown in FIG.

[0127] The advertising volume ratio change reception screen 55 includes an advertising volume ratio actual value display section 55A, an advertising volume ratio change reception section 55B, and a total response increase / decrease display section 55C.

[0128] The advertising volume ratio result value display section 55A functions as an advertising volume ratio result value output section 170.

[0129] The advertising volume ratio actual value display section 55A displays the current advertising volume (actual value) ratios MR1, MR2, MR3, MR4, MR5, MR6, MR7, MR8, and MR9 for each advertising medium 1 (television), 2 (newspaper), 3 (radio), 4 (magazine), 5 (flyer), 6 (enclosed), 7 (listing advertisement), 8 (display advertisement), and 9 (other measures). The current advertising volume (actual value) ratios MR1 ​​to MR9 are calculated as the ratio to the total advertising volume M1+M2+···+M9, for example, by calculating the average advertising volume M1 to M9 for the past three years for each advertising medium 1 to 9, as shown in the following formula (7).

[0130] MRi=100%×Mi / (M1+M2+···+M9)···(10)

[0131] Here, i corresponds to advertising media 1, 2, 3, 4, 5, 6, 7, 8, and 9.

[0132] The current advertising volume (performance value) ratios MR1 ​​to MR9 can be used as a reference when changing the advertising volume ratios.

[0133] (Advertising volume ratio change acceptance process S18 in the advertising volume ratio change acceptance unit 180)

[0134] The advertising volume ratio change receiving unit 180 receives a change to the advertising volume ratio with respect to the advertising volume ratio result value (S18).

[0135] The advertising volume ratio change receiving unit 55B functions as an advertising volume ratio change receiving unit 180.

[0136] The advertisement volume ratio change receiving unit 55B receives changes to advertisement volume ratios NR1, NR2, NR3, NR4, NR5, NR6, NR7, NR8, and NR9 for each of the advertisement media 1 (television), 2 (newspapers), 3 (radio), 4 (magazines), 5 (flyers), 6 (enclosed), 7 (listing advertisements), 8 (display advertisements), and 9 (other measures) in response to input operations. The advertisement volume ratio change receiving unit 55B can be configured as a text box in which a numerical value can be entered as text, for example, with the unit being %. The operator can input a realistic change ratio (%) into the advertisement volume ratio change receiving unit 55B as a text box, using the ratios MR1 ​​to MR9 of the current advertisement volume (actual values) as reference values ​​so that the sum of the advertisement volume ratios NR1 to NR9 is 100 (%). The operator can determine the advertisement volume ratio change value by referring to the information contact path evaluation screen 54 shown in Figs. 10(A) and (B).

[0137] In the advertising volume ratio change receiving section 55B, the current advertising volume (actual value) ratios MR1, MR2, MR3, MR4, MR5, MR6, MR7, MR8, and MR9 are displayed as initial values ​​for reference.

[0138] 11A shows an initial state in which no change to the advertising volume ratio has been accepted. In advertising volume ratio change acceptance section 55B, the current advertising volume (performance value) ratios MR1, MR2, MR3, MR4, MR5, MR6, MR7, MR8, and MR9 are displayed.

[0139] 11B shows a state in which a change to the advertising volume ratio has been accepted. The changed advertising volume ratios NR1, NR2, NR3, NR4, NR5, NR6, NR7, NR8, and NR9 are displayed in advertising volume ratio change accepting section 55B.

[0140] (Response total increase / decrease output process S19 in response total increase / decrease output unit 190)

[0141] The total response increase / decrease output unit 190 uses the change in the advertising volume ratio accepted by the advertising volume ratio change acceptance unit 180 and the path coefficient to output the increase / decrease amount or the increase / decrease rate of the total response (S19).

[0142] The response total increase / decrease display section 55C functions as a response total increase / decrease output section 190.

[0143] When the advertising volume ratio change receiving unit 55B receives a change to the advertising volume ratios NR1, NR2, NR3, NR4, NR5, NR6, NR7, NR8, and NR9, the total response increase / decrease display unit 55C displays the advertising volume ratios NR1, NR2, NR3, NR4, NR5, NR6, NR7, NR8, and NR9 and the increase / decrease rate SN of the total response using the path coefficient. The unit of the increase / decrease rate SN of the total response is %, and is expressed as a ratio (%) to the initial value SM of the total response, with the initial value SM of the total response being 100%. Therefore, when there is no increase or decrease in the total response, the increase / decrease rate SN of the total response is 100 (%), the same as the initial value SM of the total response.

[0144] 11A shows an initial state in which no change in advertising volume ratio has been accepted. The initial value SM (100%) of the total response according to the current advertising volume (performance value) ratios MR1, MR2, MR3, MR4, MR5, MR6, MR7, MR8, and MR9 is displayed in the total response increase / decrease display section 55C.

[0145] 11B shows a state in which a change in the advertising volume ratio has been accepted. The response total increase / decrease display section 55C displays the increase / decrease rate SN (e.g., 150%) of the response total according to the changed advertising volume ratios NR1, NR2, NR3, NR4, NR5, NR6, NR7, NR8, and NR9.

[0146] In the second embodiment, the rate of increase or decrease of the total response is displayed, but the amount of increase or decrease of the total response may be displayed instead of the rate of increase or decrease of the total response.

[0147] According to the second embodiment, the rate or amount of increase / decrease in the total response can be estimated simply by performing an operation to obtain the past advertising volume and actual response values ​​of each advertising medium and then performing an operation to change the advertising volume ratio based on the actual advertising volume ratio value.

[0148] In the second embodiment, similarly to the first embodiment, the response total Y0 used in the path coefficient output unit 160 and the response total increase / decrease output unit 190 may be corrected to remove seasonal influences.

[0149] Also in the second embodiment, similarly to the first embodiment, a correction process may be performed to add a residual effect to the advertisement volumes X1 to X9 of the advertisement media used in the advertisement volume ratio actual value output unit 170. [Explanation of symbols]

[0150] 100 Advertising effectiveness estimation device 110 Actual value acquisition section 120 Regression analysis processing section 130 Selection section 140 Path Route Generation Unit 150 Path Coefficient Calculation Unit 200 Advertising effectiveness estimation device 160 Path coefficient output section 170 Advertising volume ratio actual value output section 180 Advertising Volume Ratio Change Reception Department 190 Response total increase / decrease output section

Claims

1. a performance value acquiring unit that acquires a performance value of an advertising medium-by-advertising volume indicating an advertising volume for each advertising medium, a performance value of a response for each advertising medium indicating a response for each advertising medium, and a total performance value of a response obtained by adding up the performance values ​​of the response for each advertising medium; a regression analysis processing unit that performs analysis processing of a multiple regression analysis formula and / or a simple regression analysis formula with either the total response or the response by advertising medium as a response variable and one or more advertising amounts by advertising medium as explanatory variables based on the performance values ​​acquired by the performance value acquisition unit; a selection unit that selects a multiple regression analysis formula and / or a simple regression analysis formula having a fitness index of the multiple regression analysis formula and / or the simple regression analysis formula that is equal to or greater than a predetermined fitness index; a path route generating unit that generates a path route between each item so that the explanatory variables of the multiple regression analysis formula and / or the simple regression analysis formula selected by the selection unit become indirect effect source items and the objective variable becomes an indirect effect destination item, while the explanatory variables of the multiple regression analysis formula and / or the simple regression analysis formula selected by the selection unit become direct effect source items and the objective variable becomes a direct effect destination item; a path coefficient calculation unit that calculates a path coefficient between each item of the path route based on the performance value acquired by the performance value acquisition unit; An advertising placement effectiveness estimation device comprising:

2. The regression analysis processing unit performs analysis processing of a multiple regression analysis formula and / or a simple regression analysis formula using explanatory variables whose number is limited to a predetermined number or less that is smaller than the number of all advertisement media. The advertising effectiveness estimation device according to claim 1 .

3. The total response and the response by advertising medium used in the regression analysis processing unit, the path route generation unit, and the path coefficient calculation unit are corrected to remove seasonal influences. The advertising effectiveness estimation device according to claim 1 .

4. The amount of advertising by advertising medium used in the regression analysis processing unit, the path route generation unit, and the path coefficient calculation unit is corrected by adding a residual effect. The advertising effectiveness estimation device according to claim 1 .

5. a performance value acquiring unit that acquires a performance value of the amount of advertisement for each advertising medium, a performance value of the response for each advertising medium, and a total performance value of the response obtained by adding up the performance values ​​of the responses; a path coefficient output unit that outputs a path coefficient between each item, the items being the advertising volume and the total response for each advertising medium, based on the performance value acquired by the performance value acquisition unit; an advertising volume ratio result value output unit that outputs an advertising volume ratio result value indicating a ratio of advertising volumes of the advertising media based on the result values ​​acquired by the result value acquisition unit; an advertising volume ratio change receiving unit that receives a change in the advertising volume ratio with respect to the advertising volume ratio performance value; a total response increase / decrease output unit that outputs the amount of increase / decrease or the rate of increase / decrease of the total response by using the change in the advertising volume ratio accepted by the advertising volume ratio change acceptance unit and a path coefficient; An advertising placement effectiveness estimation device comprising:

6. 6. The advertising effectiveness estimation device according to claim 5, wherein the path coefficient, the actual advertising ratio value, and the increase / decrease amount or the increase / decrease rate of the total response are displayed on a screen.

7. The response total used in the path coefficient output unit and the response total increase / decrease output unit is corrected to remove seasonal influences. The advertising effectiveness estimation device according to claim 5 .

8. The amount of advertising for each advertising medium used in the advertising amount ratio performance value output unit is corrected by adding a residual effect. The advertising effectiveness estimation device according to claim 5 .

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