Information processing method, information processing system, and program

Abstract

An information processing method, an information processing system, and a program for analyzing the effectiveness of an advertisement are provided. [Solution] In an information processing system in which an information processing device and multiple terminals are connected via a network, the control unit of the information processing device has an acquisition unit that acquires first time series data, which is time series data of a KPI related to advertising for a product or service, and the delivery time of the advertisement, a creation unit that creates second time series data by missing a calculation period KPI, which is a KPI within a predetermined time after the delivery time of the advertisement, from the first time series data, an estimation unit that estimates third time series data by interpolating the missing portion based on the second time series data and first reference information, a calculation unit that calculates a confidence interval in the third time series data based on the third time series data and the second reference information, and calculates the effectiveness of the advertisement based on the confidence interval and the calculation period KPI, and a generation unit that generates display information for displaying information regarding the effectiveness of the advertisement.

Description

[Technical field]

[0001] The present invention relates to an information processing method, an information processing system, and a program. [Background technology]

[0002] Patent Document 1 discloses an information processing device, method, and program for evaluating the value of a material used in a commercial and the value of a program linked to the commercial.

[0003] In the information processing system, the control unit of the information processing device has an acquisition unit that acquires data related to key performance indicators related to a currently ongoing product or service, a prediction unit that uses reference information indicating the relationship between past time trends and trends of key performance indicators corresponding to the past time trends to predict trends of key performance indicators from the present onwards based on time trends from the present onwards, a calculation unit that calculates an estimated CM effect indicating the difference between a currently ongoing key performance indicator and a key performance indicator derived from the predicted trends of key performance indicators corresponding to the currently ongoing key performance indicators, and calculates a material CM effect related to materials used in a commercial for the product or service and a program CM effect related to a program linked to the CM based on the estimated CM effect, and an output unit that outputs the material CM effect and the program CM effect. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2023-086624 A Summary of the Invention [Problem to be solved by the invention]

[0005] Meanwhile, new technology was needed to analyze the effectiveness of advertisements (including commercials).

[0006] In view of the above circumstances, the present invention provides an information processing method, an information processing system, a program, and the like, as new technology capable of analyzing the effectiveness of advertising. [Means for solving the problem]

[0007] According to one aspect of the present invention, an information processing method includes an acquisition step, a creation step, an estimation step, a calculation step, and a generation step. In the acquisition step, first time series data, which is time series data of a KPI related to an advertisement of a product or service, and a distribution time of the advertisement are acquired. In the creation step, second time series data is created by removing a calculation period KPI, which is a KPI within a predetermined time after the distribution time of the advertisement, from the first time series data. In the estimation step, the removed portion is interpolated based on the second time series data and first reference information. an information processing method is provided, comprising: estimating third time series data based on the third time series data interpolated using the first reference information; the first reference information being information indicating a relationship between the time series data before and the time series data after the interpolation; a calculation step calculating a confidence interval for the third time series data based on the third time series data and the second reference information; the second reference information being information indicating a relationship between the time series data and the confidence interval; a calculation step calculating an advertising effectiveness based on the confidence interval and a calculation period KPI; and a generation step generating display information for displaying information regarding the advertising effectiveness.

[0008] The method of the above embodiment captures the KPI immediately after the delivery of the advertisement, and calculates the effectiveness of the advertisement using the time series data of the KPI and the KPI immediately after the delivery. That is, the method of this embodiment reflects the trend of the KPI and does not assume the apportionment of the residual effectiveness of the advertisement over a long period of time, so that it is possible to analyze the effectiveness of the advertisement itself (e.g., the suitability of the material) without being excessively affected by the advertisement's viewer rating. In addition, the method of this embodiment does not necessarily require the time series data of the KPI before the advertisement is delivered, so that the configuration is accordingly simple.

[0009] Therefore, the method of this aspect can improve the functionality of a computer to achieve at least one of the following (1) to (4): (1) The computer's processing speed can be increased. (2) Power consumption of the computer can be reduced. (3) The communication speed of the computer can be increased. (4) The resources saved in the computer can be used for other core functions.

[0010] According to this embodiment, a new technique capable of analyzing the effectiveness of an advertisement can be provided. [Brief description of the drawings]

[0011] [Figure 1] 1 is a configuration diagram illustrating an information processing system 100. [Diagram 2] FIG. 2 is a block diagram showing a hardware configuration of an information processing device 200. [Diagram 3] FIG. 2 is a block diagram showing a hardware configuration of a terminal 300. [Figure 4] FIG. 2 is a block diagram showing functions realized by an information processing device 200 (a control unit 210). [Diagram 5] 2 is an activity diagram showing the flow of an information processing method executed by information processing device 200. FIG. [Figure 6] FIG. 13 is a diagram illustrating an example of KPI time-series data by granularity. [Figure 7] FIG. 13 is a diagram illustrating an example of a state in which a calculation period KPI is omitted from the first time-series data. [Figure 8] FIG. 1 is a diagram showing two KPI time series with different periodic fluctuations. [Figure 9] FIG. 13 is a diagram illustrating an example of a state in which a 95% confidence interval is set for a KPI time series. [Figure 10] FIG. 13 is a diagram illustrating an example of a state in which a calculation period KPI is applied to a KPI time series. [Figure 11] This is a diagram showing the advertising effect 470 in a table format, calculated by CM broadcast unit. [Figure 12] FIG. 1 is a diagram showing an example (1) of an analysis result of the effectiveness of an advertisement. [Figure 13] FIG. 13 is a diagram showing an example (2) of an analysis result of the effectiveness of advertising. [Figure 14] FIG. 13 is a diagram showing an example (3) of an analysis result of the effectiveness of advertising. [Figure 15] 1 shows an example of a table for pivot analysis. [Figure 16] FIG. 13 is a diagram showing an example of information processing when two types of advertisements for the same product are aired consecutively within a predetermined time period. [Figure 17] FIG. 13 is a diagram showing an example of an ad stock used for allocating the effect of an advertisement. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to the drawings. Various characteristic features shown in the following embodiments can be combined with each other.

[0013] Incidentally, a program for realizing the software appearing in one embodiment may be provided as a non-transitory computer-readable recording medium, or may be provided so as to be downloadable from an external server, or may be provided so that the program is launched on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0014] In addition, in various information processing according to an embodiment, an input and an output according to the input can be realized. Here, as long as an output is obtained as a result of the input, the form of information referenced in such information processing (hereinafter referred to as reference information) is not limited. The reference information may be, for example, rule-based information such as a database, a lookup table, or a predetermined function (including a judgment formula such as a regression formula constructed by a statistical method), or may be a trained model that has previously trained the correlation between the input and the output, or may be a large-scale language model that can output a desired result by inputting a prompt.

[0015] In one embodiment, the term "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In one embodiment, various information is handled, and this information is represented by, for example, physical values ​​of signal values ​​representing voltage and current, high and low signal values ​​as a binary bit collection consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculation can be performed on the circuit in the broad sense.

[0016] Furthermore, a circuit in the broad sense is a circuit realized by at least appropriately combining a circuit, circuitry, a processor, and a memory. The processor may be a general-purpose processor or a dedicated circuit. In other words, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0017] 1. Hardware Configuration In the first section, the hardware configuration of this embodiment will be described.

[0018] 1-1. Information processing system 100 FIG. 1 is a configuration diagram showing an information processing system 100. The information processing system 100 includes an information processing device 200 and a terminal 300, which are connected via a network. These components will be further described. Here, a system exemplified as the information processing system 100 is composed of one or more devices or components. Therefore, for example, even the information processing device 200 alone can become a system exemplified as the information processing system 100.

[0019] 1-2. Information processing device 200 2 is a block diagram showing a hardware configuration of the information processing device 200. The information processing device 200 has a control unit 210, a storage unit 220, and a communication unit 250, and these components are electrically connected via a communication bus 260 inside the information processing device 200. The information processing device 200 may be, for example, a server. Each component will be further described.

[0020] The control unit 210 performs processing and control of the overall operation related to the information processing device 200. The control unit 210 is, for example, a central processing unit (CPU) not shown. The control unit 210 realizes various functions related to the information processing device 200 by reading out a predetermined program stored in the storage unit 220. That is, information processing by software stored in the storage unit 220 can be specifically realized by the control unit 210, which is an example of hardware, and executed as each functional unit included in the control unit 210. These will be further described in Section 2. Note that the control unit 210 is not limited to being single, and may be implemented to have multiple control units 210 for each function. Also, a combination of these may be used.

[0021] The storage unit 220 stores various information necessary for information processing of the information processing device 200. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs related to the information processing device 200 executed by the control unit 210, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the calculation of the program. Also, it may be a combination of these.

[0022] The communication unit 250 is preferably a wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), wired LAN network communication, etc., but may also include wireless LAN network communication, mobile communication such as 5G / LTE / 3G, Bluetooth (registered trademark) communication, etc. as necessary. In other words, it is more preferable to implement it as a collection of multiple communication means. In other words, the information processing device 200 communicates various information with the terminal 300 via the communication unit 250 and the network.

[0023] 1-3. Terminal 300 3 is a block diagram showing a hardware configuration of the terminal 300. The terminal 300 has a control unit 310, a storage unit 320, a display unit 330, an input unit 340, and a communication unit 350, and these components are electrically connected inside the terminal 300 via a communication bus 360. The terminal 300 may be, for example, a desktop personal computer, a notebook computer, a tablet terminal, or a smartphone terminal. The explanation of the control unit 310, the storage unit 320, and the communication unit 350 is omitted because they are substantially the same as the explanation of the control unit 210, the storage unit 220, and the communication unit 250 in the information processing device 200.

[0024] The display unit 330 may be included in the housing of the terminal 300 or may be externally attached. The display unit 330 displays a screen of a graphical user interface (GUI) that can be operated by a user. This is preferably implemented by using display devices such as a CRT display, a liquid crystal display, an organic EL display, and a plasma display depending on the type of the terminal 300. In the following, the display unit 330 will be described as being included in the housing of the terminal 300.

[0025] The input unit 340 may be included in the housing of the terminal 300, or may be externally attached. For example, the input unit 340 may be implemented as a touch panel integrated with the display unit 330. If it is a touch panel, the user can input a tap operation, a swipe operation, or the like. Of course, a switch button, a mouse, a QWERTY keyboard, or the like may be adopted instead of the touch panel. That is, the input unit 340 accepts an operation input made by the user. The input is transferred to the control unit 310 via the communication bus 360 as a command signal. Then, the control unit 310 can execute a predetermined control or calculation as necessary.

[0026] 2. Functional configuration The functional configuration of this embodiment will be described in Section 2. As described above, information processing by software stored in the storage unit 220 is specifically realized by the control unit 210, which is an example of hardware, and can be executed as each functional unit included in the control unit 210.

[0027] 4 is a block diagram showing functions realized by the information processing device 200 (control unit 210). As described above, the information processing device 200 (information processing system 100) includes the control unit 210. Specifically, the information processing device 200 (control unit 210) is configured to execute each step in the information processing method of this embodiment. The information processing device 200 (control unit 210) includes an acquisition unit 211, a creation unit 212, an estimation unit 213, a calculation unit 214, and a generation unit 215 corresponding to each step of the information processing method of this embodiment. Each unit and each step will be described below in association with each other.

[0028] The acquisition unit 211 is configured to acquire various information. The acquisition unit 211 is configured to execute an acquisition step. For example, the acquisition unit 211 acquires first time-series data that is time-series data of KPIs related to advertisements of products or services, and distribution times of the advertisements.

[0029] The creation unit 212 is configured to create various information. The creation unit 212 is configured to execute a creation step. For example, the creation unit 212 creates second time-series data by removing a calculation period KPI, which is a KPI within a predetermined time after the distribution time of an advertisement, from the first time-series data.

[0030] The estimation unit 213 is configured to estimate various information. The estimation unit 213 is configured to execute an estimation step. For example, the estimation unit 213 estimates third time series data obtained by interpolating a missing portion based on the second time series data and the first reference information. Here, the first reference information is information indicating a relationship between the time series data before the interpolation and the time series data after the interpolation.

[0031] The calculation unit 214 is configured to calculate various information. The calculation unit 214 is configured to execute a calculation step. For example, the calculation unit 214 calculates a confidence interval in the third time series data based on the third time series data and the second reference information. Here, the second reference information is information indicating a relationship between the time series data and the confidence interval. In addition, the calculation unit 214 calculates the effect of the advertisement based on the confidence interval and the calculation period KPI.

[0032] The generating unit 215 is configured to generate various information. The generating unit 215 is configured to execute a generating step. For example, the generating unit 215 generates display information for displaying information related to the effectiveness of an advertisement.

[0033] 3. Information processing method In Section 3, we will explain the flow of the information processing method of the information processing device 200 described above. This information processing method includes an acquisition step, a creation step, an estimation step, a calculation step, and a generation step. Each of these steps is executed by the control unit 210 in the information processing device 200, as described in Section 2.

[0034] 5 is an activity diagram showing the flow of an information processing method executed by information processing device 200. The following will explain each activity in this activity diagram. Here, it is assumed that terminal 300 is connected to information processing device 200 via a network and uses software running on information processing device 200. It is also assumed that the advertisement analyzed by information processing device 200 is a TV commercial for product A (hereinafter also referred to as "advertisement B"). In this embodiment, unless otherwise specified, the advertisement refers to a TV commercial.

[0035] First, the control unit 310 in the terminal 300 identifies advertisement B to be analyzed, and transmits an analysis request signal to the information processing device 200 requesting that advertisement B be analyzed (activity A110). In activity A110, for example, the following three-stage information processing is executed. (1) The input unit 340 accepts an input operation to identify advertisement B. (2) The control unit 310 generates an analysis request signal based on the input operation. (3) The control unit 310 transmits the analysis request signal to the information processing device 200 via the communication unit 350.

[0036] Next, the control unit 210 in the information processing device 200 receives an analysis request signal from the terminal 300 (activity A120). The information processing device 200 executes the following activities using the analysis request signal as a trigger. In activity A120, for example, the following two-stage information processing is executed. (1) The communication unit 250 receives the analysis request signal from the terminal 300. (2) The control unit 210 stores the analysis request signal in the memory unit 220.

[0037] Next, the control unit 210 in the information processing device 200 accesses a server (not shown) and acquires time series data of KPI (Key Performance Indicator) of product A (hereinafter also referred to as "first time series data") and the broadcast time of advertisement B (corresponding to "distribution time" in the claims) (activity A130). In other words, in the acquisition step, the first time series data, which is time series data of KPI related to advertisement of the product or service, and the broadcast time of the advertisement are acquired.

[0038] Here, KPIs, also known as key performance indicators, are a set of metrics that help define the achievement of organizational goals. The KPIs in this embodiment indicate the number of accesses to a website associated with Product A. The first time series data is obtained, for example, from a server owned by an advertiser. The broadcast time of Advertisement B is obtained, for example, from a server that manages advertisement statistical data. The advertisement statistical data includes various data corresponding to the advertisement (for example, station, program, material, broadcast time, viewer rating, number of impressions, etc.). The first time series data is KPI time series data obtained at time intervals of minutes or seconds. According to this embodiment, the effectiveness can be divided for each advertisement.

[0039] In activity A130, for example, the following three-stage information processing is executed. (1) The control unit 210 accesses various servers via the communication unit 250. (2) The control unit 210 acquires the first time-series data and the broadcast time of advertisement B. (3) The control unit 210 stores the first time-series data and the broadcast time of advertisement B in the memory unit 220.

[0040] FIG. 6 is a diagram showing an example of KPI time series data by granularity. FIG. 6(A) shows an example of KPI time series data by hourly granularity. FIG. 6(B) shows an example of KPI time series data by minutely granularity. For example, consider a case where CM airing C at 10:15, CM airing D at 10:30, and CM airing E at 10:45. In this case, as shown in FIG. 6(A), the KPI time series data by hourly granularity expresses each CM airing as being performed in the same time period (CM airing C, CM airing D, and CM airing E all at 10:00), so the effect of each CM airing cannot be captured with high resolution. On the other hand, as shown in FIG. 6(B), the KPI time series data by minutely granularity expresses each CM airing as being performed in different time periods (CM airing C at 10:15, CM airing D at 10:30, and CM airing E at 10:45), so the effect of each CM airing can be captured with high resolution.

[0041] Next, the control unit 210 in the information processing device 200 creates second time series data by removing the KPI (hereinafter also referred to as the "calculation period KPI") for 10 minutes after the airing of advertisement B from the first time series data (activity A140). In other words, in the creation step, second time series data is created by removing the calculation period KPI, which is the KPI for a predetermined time after the airing time of the advertisement, from the first time series data. Here, the predetermined time is a time expressed in minutes or seconds. In this embodiment, the predetermined time is 10 minutes as an example.

[0042] In activity A140, for example, the following three-stage information processing is executed. (1) The control unit 210 reads out the KPI time series and the broadcast time from the storage unit 220. (2) The control unit 210 executes a creation process to create second time series data. (3) The control unit 210 stores the second time series data in the storage unit 220.

[0043] Fig. 7 is a diagram showing an example of a state in which the calculation period KPI is omitted from the first time series data. In Fig. 7, time series data 410 is displayed as an example of the second time series data. Advertisement B is assumed to have been aired seven times in one day, and intervals 441, 442, 443, 444, 445, 446, and 447 are displayed as intervals of 10 minutes after the airing of advertisement B. Here, the KPI (calculation period KPI) in each interval is omitted.

[0044] Next, the control unit 210 in the information processing device 200 estimates third time series data by interpolating the missing part based on the second time series data and a time series model (corresponding to "first reference information" in the claims) (activity A150). In other words, in the estimation step, the third time series data by interpolating the missing part is estimated based on the second time series data and the first reference information. Here, the first reference information is information indicating the relationship between the time series data before the interpolation and the time series data after the interpolation. In the activity A150, for example, the following three-stage information processing is executed. (1) The control unit 210 reads out the second time series data and the time series model from the storage unit 220. (2) The control unit 210 executes an estimation process to estimate the third time series data. (3) The control unit 210 stores the third time series data in the storage unit 220.

[0045] In this embodiment, a time series model having elements of trend terms and periodic terms is used to interpolate the missing parts by curve fitting. Details of the time series model will be described below. Note that the following formulas are explained in a paper titled "Taylor, SJ, & Letham, B., Forecasting at scale, The American Statistician, 2018, Vol.72, No.1, p.37-45". Therefore, the paper is incorporated by reference in its entirety in this embodiment.

[0046] Fig. 8 is a diagram showing two KPI time series with different periodic fluctuations. Fig. 8(A) shows a KPI time series 510, a trend 511, and a periodic component 512. The range of periodic fluctuation of the KPI time series 510 is approximately constant when compared with the periodic component 512, regardless of the trend 511. When dealing with the KPI time series 510, for example, an additive model shown in equation (1) is selected. This additive model is an example of the first reference information.

[0047]

number

[0048] 8(B) shows a KPI time series 520, a trend 521, and a periodic component 522. The periodic fluctuation range of the KPI time series 520 changes in proportion to the trend 521 when compared with the periodic component 522. When handling the KPI time series 520, for example, a multiplicative model shown in equation (2) is selected. This multiplicative model is an example of the first reference information.

[0049]

number

[0050] Next, the trend terms in formulas (1) and (2) will be explained. A nonlinear trend or a linear trend is selected as the trend term depending on the KPI time series being handled. For example, when expressing a saturated trend, the nonlinear trend shown in the following formula (3) is selected.

[0051]

number

[0052] The nonlinear trend of equation (3) can be expressed as an extended model of equation (4) below.

[0053]

number

[0054] On the other hand, when dealing with a KPI time series that does not show a saturated trend, the linear trend shown in (5) below is selected.

[0055]

number

[0056] The linear trend in equation (5) can be expressed as an extended model of equation (6) below.

[0057]

number

[0058] The nonlinear trend in equation (3) and the linear trend in equation (5) are expressed as models that allow for changes in the growth rate k. That is, S j If (j=1,...,S) is the jth time of the transition point, the following formula (7) expresses that the growth rate k changes as shown in the following formula (8). The following formula (8) expresses that δ j This means that the growth rate increases by a(t). Τ The term δ is a term that corrects the growth rate k so that the trend becomes continuous at the above-mentioned turning point, a(t) Τ The term γ is a term that corrects the offset m so that the trend becomes continuous at the above-mentioned conversion point.

[0059]

number

[0060]

number

[0061] Next, the periodic terms in the formulas (1) and (2) will be described. The periodic terms are approximated by a Fourier series shown in the following formula (9).

[0062]

number

[0063] Since the broadcast period of a TV commercial is often one week to one month for a spot commercial, it was thought that expressing a one-week cycle would be sufficient when analyzing a TV commercial. Therefore, in this embodiment, P in formula (9) was set to 7. Also, if the truncation order M is too large, components containing noise will be analyzed, so it is necessary to set an appropriate value. Therefore, when the periodic components contained in any KPI time series to be analyzed were examined by Fourier transform, it was found that there was almost no effect on components with a cycle shorter than 1 / 4 (day). Therefore, in this embodiment, M in formula (9) was set to 28. That is, (P=7) / (M=28) was used, and the cycle was set to 1 / 4.

[0064] That is, in the creating step, the first reference information is applied depending on the type of KPI. According to this embodiment, the accuracy of the third time-series data can be improved.

[0065] Next, the control unit 210 in the information processing device 200 calculates a 95% confidence interval from the third time series data (activity A160). In other words, in the calculation step, a confidence interval in the third time series data is calculated based on the third time series data and the second reference information. Here, the second reference information is information indicating the relationship between the time series data and the confidence interval. In the activity A160, for example, the following three-stage information processing is executed. (1) The control unit 210 reads out the third time series data and the statistical model from the storage unit 220. (2) The control unit 210 executes a calculation process and calculates the 95% confidence interval. (3) The control unit 210 stores the 95% confidence interval in the storage unit 220.

[0066] 9 is a diagram showing an example of a state in which a 95% confidence interval is set for a KPI time series. Time series data 420 is data in which a 95% confidence interval is set for time series data 410. First, virtual KPIs are interpolated for each of intervals 441, 442, 443, 444, 445, 446, and 447 of the time series data 410. Next, a 95% confidence interval 460 is set.

[0067] Next, the control unit 210 in the information processing device 200 calculates the effectiveness of advertisement B based on the 95% confidence interval and the calculation period KPI (activity A170). In other words, in the calculation step, the effectiveness of the advertisement is calculated based on the confidence interval and the calculation period KPI. In activity A170, for example, the following three-stage information processing is executed. (1) The control unit 210 reads out the 95% confidence interval and the calculation period KPI from the storage unit 220. (2) The control unit 210 executes a calculation process to calculate the effectiveness of advertisement B. (3) The control unit 210 stores the effectiveness of advertisement B in the storage unit 220.

[0068] 10 is a diagram showing an example of a state in which a calculation period KPI is applied to a KPI time series. Time series data 430 is data obtained by applying a calculation period KPI to time series data 420. The effect of advertisement B is the portion exceeding an upper confidence limit 461. Advertising effect 470 indicates the effect of advertisement B.

[0069] FIG. 11 is a diagram showing the advertising effect 470 in a table format, tabulated by CM broadcast unit. As shown in FIG. 10, the advertising effect 470 is detected in a total of three broadcasts, namely, broadcasts at 11:26, 21:43, and 21:58. As described above, the effect of advertisement B is calculated as the portion where the calculation period KPI exceeds the upper confidence limit 461. For example, the effect of advertisement B for broadcast C, which was broadcast at 11:26, "21.093988", is the sum of the KPIs that occurred in the 10 minutes from 11:26 that exceeded the upper confidence limit 461. Therefore, the effect of advertisement B is calculated as max(calculation period KPI-upper confidence limit 461,0).

[0070] According to activity A170, the predetermined time in activity A140 is expressed in minutes or seconds, so that it is possible to analyze the effectiveness of advertisements without being excessively affected by the viewer ratings.

[0071] Next, the control unit 210 in the information processing device 200 transmits reception information for receiving an analysis axis for analyzing advertisement B to the terminal 300 (activity A180). The analysis axis is appropriately selected from, for example, the number of effects of an advertisement, the number of impressions, the number of effects of an advertisement per unit number of impressions (or unit audience rating) (hereinafter also referred to as "index"), program name, material, area, broadcasting station, series, broadcast date, broadcast day of the week, broadcast time, program category, etc. In activity A180, for example, the following two-stage information processing is executed. (1) The control unit 210 reads out the reception information from the storage unit 220. (2) The control unit 210 transmits the reception information to the terminal 300 via the communication unit 250.

[0072] Next, the control unit 310 in the terminal 300 receives the reception information from the information processing device 200 (activity A190). In activity A190, for example, the following two-stage information processing is executed. (1) The communication unit 350 receives the reception information from the information processing device 200. (2) The control unit 310 causes the display unit 330 to display a screen for receiving the analysis axis of advertisement B based on the reception information.

[0073] Next, the control unit 310 in the terminal 300 waits until the analysis axis of advertisement B is received (NO in activity A200). When the control unit 310 determines that the analysis axis of advertisement B has been received (YES in activity A200), it proceeds to processing of activity A210. In activity A200, for example, the following three stages of information processing are executed. (1) The control unit 310 waits until the analysis axis of advertisement B is received. (2) When information on the analysis axis is input to the input unit 340, the control unit 310 receives the information on the analysis axis via the communication bus 360. (3) The control unit 310 stores the information on the analysis axis in the memory unit 320.

[0074] Next, the control unit 310 in the terminal 300 transmits the analysis axis of advertisement B to the information processing device 200 (activity A210). In activity A210, for example, the following two-stage information processing is executed. (1) The control unit 310 reads out the analysis axis of advertisement B from the storage unit 320. (2) The control unit 310 transmits the analysis axis to the information processing device 200 via the communication unit 350.

[0075] Next, the control unit 210 in the information processing device 200 receives the analysis axis of advertisement B from the terminal 300 (activity A220). In activity A220, for example, the following two-stage information processing is executed. (1) The communication unit 250 receives the analysis axis of advertisement B from the terminal 300. (2) The control unit 210 stores the analysis axis in the storage unit 220.

[0076] Next, the control unit 210 in the information processing device 200 generates display information for displaying the effectiveness of advertisement B on the display unit 330 in the terminal 300 (activity A230). In other words, in the generation step, display information for displaying information related to the effectiveness of the advertisement is generated. Here, the display information is information for displaying the effectiveness of advertisement B along the set analysis axis. In activity A230, for example, the following three-stage information processing is executed. (1) The control unit 210 reads out the effectiveness and analysis axis of advertisement B from the storage unit 220. (2) The control unit 210 executes a generation process to generate display information for displaying the effectiveness of advertisement B along the analysis axis. (3) The control unit 210 stores the display information in the storage unit 220.

[0077] Next, the control unit 210 in the information processing device 200 transmits the display information to the terminal 300 (activity A240). In activity A240, for example, the following two-stage information processing is executed. (1) The control unit 210 reads out the display information from the storage unit 220. (2) The control unit 210 transmits the display information to the terminal 300 via the communication unit 250.

[0078] Next, the control unit 310 in the terminal 300 receives the display information from the terminal 300 (activity A250). In the activity A250, for example, the following two-stage information processing is executed. (1) The communication unit 350 receives the display information from the information processing device 200. (2) The control unit 310 stores the display information in the storage unit 320.

[0079] Next, the control unit 310 in the terminal 300 causes the display unit 330 to display the effect of advertisement B (activity A260). In activity A260, for example, the following three-stage information processing is executed. (1) The control unit 310 reads out the display information from the storage unit 320. (2) The control unit 310 inputs the display information to the display unit 330 via the communication bus 360. (3) The display unit 330 displays the effect of advertisement B along the set analysis axis.

[0080] Next, the control unit 310 in the terminal 300 receives a signal as to whether or not to analyze advertisement B along a different analysis axis (activity A270). If the control unit 310 receives information on reanalysis (YES in activity A270), it proceeds to the processing of activity A200. If the control unit 310 does not receive information on reanalysis (NO in activity A270), it ends the information processing method of this embodiment.

[0081] According to the information processing method of the present embodiment, it is possible to analyze the effectiveness of advertisements while taking into account the trend of KPIs. In addition, because of the simple configuration, the saved resources can be used for other core functions.

[0082] 4. Example of analysis results Section 4 explains examples of displaying analysis results.

[0083] FIG. 12 is a diagram showing an example (1) of the analysis results of the effectiveness of advertising. Here, the analysis results are shown when different materials (material A, material B) are used in an advertisement for the same product. For the advertisement using material A, the advertising effectiveness was 100, the number of impressions was 5,000,000, and the index converted to unit impressions was 20. For the advertisement using material B, the advertising effectiveness was 200, the number of impressions was 2,000,000, and the index converted to unit impressions was 100. Comparing material A and material B, it was found that material B was more effective. In this way, the display example in FIG. 12 makes it possible to analyze the acquisition efficiency for each material.

[0084] Fig. 13 is a diagram showing an example (2) of the analysis results of advertising effectiveness. This shows the cumulative advertising effectiveness (acquisition efficiency) relative to the cumulative number of impressions when different materials (material A, material B, material C) are used in advertising the same product. Fig. 13 shows that the advertising effectiveness is highest when material A is used, and although there is not much difference between material B and material C, material B has a higher acquisition efficiency.

[0085] FIG. 14 is a diagram showing an example (3) of the analysis result of the effectiveness of advertising. The analysis result in FIG. 14 corresponds to the entire broadcast area. In FIG. 14, the vertical axis is the time period and the horizontal axis is the day of the week, and an index (for example, "1.90" at 11pm on Tuesday) is entered in each box. Then, the index is visualized as a heat map according to the size of the index. This heat map makes it possible to compare various purchasing patterns (for example, all-day, square-shaped, U-shaped, inverted L-shaped).

[0086] Fig. 15 shows an example of a table for pivot analysis. For example, the acquired advertisement statistical data is processed into a format having columns as shown in Fig. 15 and stored in the storage unit 220. With such a table, advertisements can be analyzed along various axes such as "program x material", "program category x material", "program category", etc.

[0087] 5. Second embodiment Section 5 describes a second embodiment of the present invention. In the second embodiment, information processing will be described for a case where there are multiple advertisements for the same product, and another advertisement is aired within a predetermined time (e.g., 10 minutes) following the airing of one advertisement.

[0088] 16 is a diagram showing an example of information processing when two types of advertisements for the same product are aired consecutively within a predetermined time. Here, a case is shown in which an advertisement is aired at 20:43 (airing A), followed by an advertisement for the same product at 20:44 (airing B). The advertisements here are not limited to different advertisements, and may be the same advertisement.

[0089] When advertisements are aired consecutively, there is an overlap in the first 10 minutes, making it difficult to determine which advertisement caused the resulting effect. Therefore, ad stock is applied as the residual effect of the advertisement to apportion the effect of the advertisement and estimate the effect of each airing A and B. Ad stock refers to the sustained effect that appears after the airing of, for example, a television commercial as an advertisement. Figure 17 is a diagram showing an example of ad stock used to apportion the effect of an advertisement. The ad stock 610 used here for the nth minute after airing is expressed, for example, by the following formula (10).

[0090]

number

[0091] Since the ADS 610 in equation (10) is not expressed as the commonly used geometric damping, tuning of the damping rate is not required.

[0092] In other words, the information processing in the second embodiment can be expressed as steps. In the calculation step, when advertisements for the same product or service are distributed multiple times within a predetermined time, the effectiveness of each advertisement is calculated by apportioning the effectiveness of the distributed advertisements. According to this aspect, the effectiveness of each advertisement can be analyzed even when advertisements are distributed consecutively.

[0093] Although the embodiment of the present invention has been described above, the present invention is not limited to this, and can be modified as appropriate without departing from the technical concept of the invention.

[0094] 6. Variations Modifications of this embodiment will be described in Section 6. The following modifications can be combined as appropriate.

[0095] An aspect of the present embodiment may be a program. The program is configured to cause a computer to execute each step of the information processing method of the present embodiment.

[0096] The control unit 210 performs write (storage) and read processes for various data and information in the memory unit 220, but this is not limited to this, and for example, information processing for each activity may be performed using a register or cache memory within the control unit 210.

[0097] In this embodiment, the advertisement has been described as a TV commercial, but is not limited to this. The advertisement is not limited to one distributed by airwaves from a television broadcasting station or a radio broadcasting station, and may be, for example, a digital advertisement (an advertisement through an online channel such as a website or streaming content). The information processing device 200 can be applied to the analysis of various advertisements without being limited to the type of media or medium.

[0098] In this embodiment, the server owned by the advertiser is accessed to acquire the time series data of the KPI of the product A, but the present invention is not limited to this. For example, the time series data may be stored in the storage unit 220 of the information processing device 200, and the time series data may be acquired by reading the data.

[0099] In this embodiment, the server that manages the advertisement statistical data is accessed to acquire the broadcast time of advertisement B, but this is not limited to the above. For example, the broadcast time may be stored in the storage unit 220 in the information processing device 200 and may be acquired by reading out the broadcast time, or the advertisement statistical data itself may be received and the broadcast time of advertisement B may be extracted from the advertisement statistical data.

[0100] In this embodiment, the number of accesses to a website associated with the advertised product has been described as an example of a KPI, but the KPI is not limited to this. If the product is an application, the KPI may be the number of installations of the application or the number of searches using a specific keyword.

[0101] In this embodiment, the time series data is acquired at intervals of minutes or seconds, but is not limited to this. Each piece of time series data may be acquired at time intervals of hours.

[0102] In this embodiment, the predetermined time is 10 minutes as an example, but is not limited to this. The predetermined time is, for example, 1 second to 60 minutes, preferably 1 minute to 30 minutes, and more preferably 3 minutes to 20 minutes. Specifically, for example, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 seconds, and may be within a range between any two of the numerical values ​​exemplified here. It may also be 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, or 60 minutes, or may be within a range between any two of the numerical values ​​exemplified here.

[0103] In this embodiment, the confidence interval is described as a 95% confidence interval, but is not limited to this. The confidence interval may be appropriately set depending on how the effectiveness of the advertisement is analyzed, and may be, for example, an 80% confidence interval or a 68% confidence interval. The higher the confidence level, the more difficult it is to detect the effectiveness of the advertisement, but the more difficult it is to detect noise.

[0104] In this embodiment, Fig. 14 has been described as an analysis result corresponding to the entire broadcast area, but is not limited to this. The analysis result of Fig. 14 may be visualized for each area or each station, for example.

[0105] In this embodiment, an index is input to each box in Fig. 14, but this is not limited to this. The numerical value input in Fig. 14 may be, for example, the number of impressions or the effectiveness of the advertisement.

[0106] In the present embodiment, the activities A110 to A270 are executed in this order, but the present invention is not limited to this. The activities may be executed in any order, or may be executed simultaneously in any combination.

[0107] In activities A200 and A270, it is not an essential condition that control unit 310 in terminal 300 transitions to the next activity using an input operation (e.g., a click operation, a tap operation, etc.) on input unit 340 as a trigger. For example, in activity A200 or A270, control unit 310 may transition to the next activity if input unit 340 does not accept an input operation within a predetermined time.

[0108] 7.Other It may be provided in any of the following ways:

[0109] (1) An information processing method comprising an acquisition step, a creation step, an estimation step, a calculation step, and a generation step, in which the acquisition step acquires first time series data that is time series data of a KPI related to an advertisement of a product or service and a distribution time of the advertisement, the creation step creates second time series data by removing a calculation period KPI that is the KPI within a predetermined time after the distribution time of the advertisement from the first time series data, and the estimation step creates a third time series data by interpolating the removed portion based on the second time series data and first reference information. an information processing method comprising: estimating data based on the third time series data and the second reference information, the first reference information being information indicating a relationship between the time series data before interpolation and the time series data after interpolation; calculating a confidence interval for the third time series data based on the third time series data and the second reference information, the second reference information being information indicating the relationship between the time series data and the confidence interval; calculating an effectiveness of the advertisement based on the confidence interval and the calculation period KPI; and generating display information for displaying information regarding the effectiveness of the advertisement.

[0110] According to this embodiment, it is possible to analyze the effectiveness of advertisements while taking into account the trend of KPIs. In addition, because of the simple configuration, the saved resources can be used for other core functions.

[0111] (2) The information processing method according to (1) above, wherein the predetermined time is expressed in minutes or seconds.

[0112] According to this embodiment, it is possible to analyze the effectiveness of an advertisement without being excessively affected by the viewer rating.

[0113] (3) The information processing method according to (1) or (2) above, wherein the time series data is data acquired at time intervals of minutes or seconds.

[0114] According to this embodiment, the effect can be differentiated for each advertisement.

[0115] (4) The information processing method according to any one of (1) to (3) above, wherein in the creating step, the first reference information is applied depending on a type of the KPI.

[0116] According to this embodiment, the accuracy of the third time series data can be improved.

[0117] (5) In the information processing method described in any one of (1) to (4) above, in the calculation step, when the advertisement for the same product or service is delivered multiple times within the specified time period, the effectiveness of each of the delivered advertisements is apportioned to calculate the effectiveness of each of the advertisements.

[0118] According to this embodiment, even when advertisements are delivered consecutively, it is possible to analyze the effectiveness of each advertisement.

[0119] (6) An information processing system comprising a control unit, the control unit being configured to execute each step of the information processing method according to any one of (1) to (5) above.

[0120] According to this embodiment, it is possible to analyze the effectiveness of an advertisement while taking into consideration the trend of KPIs. Also, because of the simple configuration, it is possible to increase the processing speed of a computer.

[0121] (7) A program configured to cause a computer to execute each step of the information processing method according to any one of (1) to (5) above.

[0122] According to this embodiment, it is possible to analyze the effectiveness of an advertisement while taking into consideration the trend of KPIs. Also, because of the simple configuration, it is possible to conserve power of a computer. Of course, this is not the case. [Explanation of symbols]

[0123] 100: Information processing systems 200: Information processing device 210: Control section 211: Acquisition Department 212: Creation Department 213: Estimation section 214: Calculation section 215 :Generation part 220: Storage section 250: Communications Department 260: Communication bus 300: Terminal 310: Control section 320: Storage section 330: Display section 340: Input section 350: Communications Department 360: Communication bus 410: Time series data 420: Time series data 430: Time series data 441: Section 442: Section 443: Section 444: Section 445: Section 446: Section 447: Section 460: Confidence interval 461: Upper confidence limit 470: Advertising effectiveness 510: KPI Time Series 511: Trends 512: Periodic component 520: KPI Time Series 521: Trends 522: Periodic component 610: Adstock

Claims

1. An information processing method implemented by a computer, comprising: The method includes an acquisition step, a creation step, an estimation step, a calculation step, and a generation step, In the acquiring step, first time-series data, which is time-series data of a KPI related to an advertisement of a product or service, and a distribution time of the advertisement are acquired; In the creating step, second time series data is created by deleting a calculation period KPI, which is the KPI within a predetermined time after the distribution time of the advertisement, from the first time series data; In the estimation step, third time series data is estimated by interpolating a missing portion based on the second time series data and first reference information; the first reference information is information indicating a relationship between the time series data before interpolation and the time series data after interpolation, In the calculation step, a confidence interval in the third time series data is calculated based on the third time series data and second reference information; the second reference information is information indicating a relationship between the time-series data and the confidence interval; In the calculation step, an effect of the advertisement is calculated based on the confidence interval and the calculation period KPI; In the generating step, display information for displaying information regarding the effectiveness of the advertisement is generated. Information processing methods.

2. 2. The information processing method according to claim 1, The predetermined time is a time expressed in minutes or seconds. Information processing methods.

3. 2. The information processing method according to claim 1, The time series data is data acquired at time intervals of minutes or seconds. Information processing methods.

4. 2. The information processing method according to claim 1, In the creating step, the first reference information is applied depending on the type of the KPI. Information processing methods.

5. 2. The information processing method according to claim 1, In the calculation step, when the advertisement for the same product or service is distributed multiple times within the predetermined time period, the effectiveness of each of the advertisements is calculated by dividing the effectiveness of the advertisements distributed proportionally. Information processing methods.

6. An information processing system, A control unit is provided, The control unit is configured to execute each step of the information processing method according to any one of claims 1 to 5. Information processing system.

7. A program, A method for processing information according to any one of claims 1 to 5, program.

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