Information processing methods, information processing systems, and programs

Abstract

This invention provides an information processing method, information processing system, and program for analyzing the effectiveness of advertising. [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 includes an acquisition unit that acquires first time series data, which is time series data of KPIs related to advertising of goods or services, and the time of delivery of the advertisement; a creation unit that creates second time series data by omitting calculation period KPIs, which are KPIs within a predetermined time period after the time of delivery 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 second reference information, and calculates the effect of the advertisement based on the confidence interval and calculation period KPIs; and a generation unit that generates display information for displaying information related to the effect of the advertisement.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses an information processing apparatus, method, and program for evaluating the value of a material used in a CM and the value of a program associated with the CM.

[0003] In an information processing system, a control unit of an information processing apparatus includes an acquisition unit that acquires data related to important performance evaluation indicators related to a currently ongoing product or service, a prediction unit that uses reference information indicating the relationship between the past time transition and the transition of the important performance evaluation indicators corresponding to the past time transition, and predicts the transition of the important performance evaluation indicators after the current time based on the time transition after the current time, and an estimation unit that calculates an estimated CM effect indicating the difference between the currently ongoing important performance evaluation indicator and the important performance evaluation indicator derived from the predicted transition of the important performance evaluation indicator corresponding to the currently ongoing important performance evaluation indicator, and based on the estimated CM effect, a calculation unit that calculates a material CM effect related to a material used in the CM of the product or service and a program CM effect related to a program associated with the CM, and an output unit that outputs the material CM effect and the program CM effect.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] By the way, a new technology has been demanded for analyzing the effect of advertisements (including CM).

[0006] In view of the above circumstances, the present invention aims to provide a novel information processing method, information processing system, and program, etc., that can analyze the effectiveness of advertising. [Means for solving the problem]

[0007] According to one aspect of the present invention, an information processing method comprising an acquisition step, a creation step, an estimation step, a calculation step, and a generation step, wherein the acquisition step acquires first time-series data, which is time-series data of KPIs related to advertising of goods or services, and the delivery time of the advertisement; the creation step creates second time-series data by omitting calculation period KPIs, which are KPIs within a predetermined time period after the delivery time of the advertisement, from the first time-series data; and the estimation step interpolates the missing portion based on the second time-series data and first reference information. An information processing method is provided which estimates a third time series data, the first reference information is information showing the relationship between the time series data before interpolation and the time series data after interpolation, the calculation step calculates a confidence interval in the third time series data based on the third time series data and the second reference information, the second reference information is information showing the relationship between the time series data and the confidence interval, the calculation step calculates the effectiveness of the advertisement based on the confidence interval and the calculation period KPI, and the generation step generates display information for displaying information regarding the effectiveness of the advertisement.

[0008] The method described in one embodiment captures KPIs immediately after ad delivery and uses the time-series data of the KPIs and the KPIs immediately after delivery to determine the effectiveness of the ad. In other words, this method reflects the trend of KPIs and does not assume the allocation of residual effects of the ad over a long period of time, so it can analyze the effectiveness of the ad itself (e.g., the suitability of the material) without being excessively influenced by the ad's viewership ratings. Furthermore, this method does not necessarily require time-series data of KPIs before ad delivery, so it has a simpler structure.

[0009] Therefore, the method of this embodiment 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) The computer's power consumption can be reduced. (3) The computer's communication speed can be increased. (4) The resources saved in the computer can be used for other core functions.

[0010] In this manner, it is possible to provide a novel technology that enables the analysis of the effectiveness of advertising. [Brief explanation of the drawing]

[0011] [Figure 1] This is a diagram showing the configuration of information processing system 100. [Figure 2] This is a block diagram showing the hardware configuration of the information processing device 200. [Figure 3] This is a block diagram showing the hardware configuration of terminal 300. [Figure 4] This is a block diagram showing the functions realized by the information processing device 200 (control unit 210). [Figure 5] This is an activity diagram showing the flow of the information processing method executed by the information processing device 200. [Figure 6] This figure shows an example of KPI time series data at different levels of granularity. [Figure 7] This figure shows an example of the first time-series data with the calculation period KPI missing. [Figure 8] This figure shows two KPI time series with different periodic fluctuations. [Figure 9] This figure shows an example of setting a 95% confidence interval for a KPI time series. [Figure 10] This figure shows an example of applying the calculation period KPI to a KPI time series. [Figure 11] This chart shows the advertising effectiveness (470) aggregated per TV commercial broadcast, presented in a table format. [Figure 12] This figure shows an example of the results of an analysis of the effectiveness of an advertisement (1). [Figure 13] It is a diagram showing an example (2) of the analysis result of the advertisement effect. [Figure 14] It is a diagram showing an example (3) of the analysis result of the advertisement effect. [Figure 15] An example of a table for pivot analysis is shown. [Figure 16] It is a diagram showing an example of information processing when two types of advertisements for the same product are continuously broadcast within a predetermined time. [Figure 17] It is a diagram showing an example of an adstock used for apportioning the advertisement effect.

Embodiments for Carrying Out the Invention

[0012] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Various characteristic matters shown in the embodiments described below can be combined with each other.

[0013] By the way, a program for realizing the software appearing in one embodiment may be provided as a non-temporary computer-readable medium (Non-Transitory Computer-Readable Medium) readable by a computer, may be provided so as to be downloadable from an external server, or may be provided so as to start the program on an external computer and realize its function on a client terminal (so-called cloud computing).

[0014] Also, in various information processes according to one embodiment, an input and an output corresponding to the input can be realized. Here, if an output is obtained as a result of the input, the mode of information (hereinafter referred to as reference information) referred to in such information processing is not limited. The reference information may be, for example, rule-based information such as a database, a lookup table, a predetermined function (including a judgment formula such as a regression formula constructed by a statistical method), a learned model in which the correlation between the input and the output has been learned in advance, or a large language model capable of outputting a desired result by inputting a prompt.

[0015] Furthermore, in one embodiment, "part" may include, for example, hardware resources implemented by a circuit in a broad sense, and the information processing of software that can be specifically realized by these hardware resources. Also, in one embodiment, various types of information are handled, and this information can be represented, for example, by the physical values ​​of signal values ​​representing voltage and current, the high or low values ​​of signal values ​​as a set of binary bits composed of 0s or 1s, or by quantum superposition (so-called qubits), and communication and calculations can be performed on a circuit in a broad sense.

[0016] Furthermore, a circuit in a broad sense is a circuit realized by combining at least a suitable combination of circuits, circuits, processors, and memory. The processor may be a general-purpose processor or a dedicated circuit. In other words, it includes application-specific integrated circuits (ASICs), programmable logic devices (for example, simple programmable logic devices (SPLDs), complex programmable logic devices (CPLDs), and field programmable gate arrays (FPGAs)), etc.

[0017] 1. Hardware Configuration Section 1 describes the hardware configuration of this embodiment.

[0018] 1-1. Information Processing System 100 Figure 1 is a diagram illustrating the configuration of the information processing system 100. The information processing system 100 comprises an information processing device 200 and a terminal 300, which are connected via a network. These components will be further explained. Here, the system exemplified in the information processing system 100 consists of one or more devices or components. Therefore, for example, even the information processing device 200 alone can be a system exemplified in the information processing system 100.

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

[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 predetermined programs stored in the storage unit 220. That is, information processing by software stored in the storage unit 220 is concretely 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. These will be explained further in Section 2. Note that the control unit 210 is not limited to being a single unit, and may be implemented with multiple control units 210 for each function, or a combination thereof.

[0021] The storage unit 220 stores various information necessary for information processing by the information processing device 200. This can be done, 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 memory such as random access memory (RAM) that stores temporarily necessary information (arguments, arrays, etc.) related to program calculations. A combination of these may also be used.

[0022] The communication unit 250 preferably uses wired communication methods such as USB, IEEE1394, Thunderbolt®, and wired LAN network communication, but may also include wireless LAN network communication, mobile communication such as 5G / LTE / 3G, and Bluetooth® communication as needed. In other words, it is more preferable to implement it as a collection of these multiple communication methods. That is, the information processing device 200 communicates various information with the terminal 300 via the network through the communication unit 250.

[0023] 1-3. Terminal 300 Figure 3 is a block diagram showing the hardware configuration of terminal 300. Terminal 300 includes 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 within terminal 300 via a communication bus 360. Terminal 300 may be, for example, a desktop computer, a notebook computer, a tablet terminal, or a smartphone terminal. The descriptions of the control unit 310, storage unit 320, and communication unit 350 are substantially the same as the descriptions of the control unit 210, storage unit 220, and communication unit 250 in the information processing device 200, and are therefore omitted.

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

[0025] The input unit 340 may be included in the casing of the terminal 300 or it may be an external component. For example, the input unit 340 may be integrated with the display unit 330 and implemented as a touch panel. If it is a touch panel, the user can input tap operations, swipe operations, etc. Of course, instead of a touch panel, a switch button, mouse, QWERTY keyboard, etc., may be used. In other words, the input unit 340 receives operation input made by the user. This input is transmitted as a command signal to the control unit 310 via the communication bus 360. The control unit 310 can then perform predetermined controls and calculations as needed.

[0026] 2. Functional Configuration Section 2 will describe the functional configuration of this embodiment. As mentioned above, the information processing by the software stored in the memory 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] Figure 4 is a block diagram showing the functions realized by the information processing device 200 (control unit 210). As described above, the information processing device 200 (information processing system 100) includes a 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 in the information processing method of this embodiment. The following will describe each unit in relation to each step.

[0028] The acquisition unit 211 is configured to acquire various types of information. The acquisition unit 211 is configured to perform acquisition steps. For example, the acquisition unit 211 acquires first time-series data, which is time-series data of KPIs related to advertising for a product or service, and the delivery time of the advertisement.

[0029] The creation unit 212 is configured to create various types of information. The creation unit 212 is configured to execute creation steps. For example, the creation unit 212 creates a second time series data from the first time series data, omitting the calculation period KPI, which is a KPI for a predetermined time period after the advertisement delivery time.

[0030] The estimation unit 213 is configured to estimate various types of information. The estimation unit 213 is configured to perform estimation steps. For example, the estimation unit 213 estimates a third time series data by interpolating the missing parts based on a second time series data and first reference information. Here, the first reference information is information that shows the relationship between the time series data before interpolation and the time series data after interpolation.

[0031] The calculation unit 214 is configured to calculate various types of information. The calculation unit 214 is configured to perform calculation steps. For example, the calculation unit 214 calculates a confidence interval in the third time series data based on the third time series data and second reference information. Here, the second reference information is information that shows the relationship between the time series data and the confidence interval. The calculation unit 214 also calculates the effectiveness of the advertisement based on the confidence interval and the calculation period KPI.

[0032] The generation unit 215 is configured to generate various types of information. The generation unit 215 is configured to perform generation steps. For example, the generation unit 215 generates display information to display information about the effectiveness of an advertisement.

[0033] 3. Information Processing Methods Section 3 describes the flow of the information processing method of the information processing device 200 mentioned above. This information processing method comprises 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 of the information processing device 200, as described in Section 2.

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

[0035] First, the control unit 310 in terminal 300 identifies advertisement B to be analyzed and sends 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 stages of information processing are performed: (1) The input unit 340 receives 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 sends 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 uses the analysis request signal as a trigger to execute the following activities. In activity A120, for example, the following two-stage information processing is performed: (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 storage 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 the Key Performance Indicator (KPI) of product A (hereinafter also referred to as "first time-series data") and the broadcast time of advertisement B (corresponding to "delivery time" in the claims) (Activity A130). To put this in terms of steps, the acquisition step acquires the first time-series data, which is time-series data of KPI related to the advertisement of the product or service, and the broadcast time of the advertisement.

[0038] Here, KPIs, also known as Key Performance Indicators, are a set of quantitative criteria that help define the achievement of an organization's goals. In this embodiment, the KPIs represent the number of accesses to the website associated with product A. The first time-series data is obtained, for example, from a server owned by the advertiser. The airtime of advertisement B is obtained, for example, from a server that manages advertising statistics data. Advertising statistics data includes various data corresponding to the advertisement (e.g., station, program, material, airtime, viewership rating, number of impressions, etc.). The first time-series data is also KPI time-series data obtained at time intervals of minutes or seconds. With this configuration, the effect can be differentiated for each advertisement.

[0039] In Activity A130, for example, the following three stages of information processing are performed: (1) The control unit 210 accesses various servers via the communication unit 250. (2) The control unit 210 obtains 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 storage unit 220.

[0040] Figure 6 shows an example of KPI time series data at different levels of granularity. Figure 6(A) shows an example of KPI time series data at hourly granularity. Figure 6(B) shows an example of KPI time series data at minutely granularity. For example, consider the case where commercial C is broadcast at 10:15, commercial D at 10:30, and commercial E at 10:45. In this case, as shown in Figure 6(A), the hourly granular KPI time series data represents each commercial broadcast as occurring at the same time (all of commercials C, D, and E at 10:00), making it difficult to capture the effect of each commercial broadcast with high resolution. On the other hand, as shown in Figure 6(B), the minutely granular KPI time series data represents each commercial broadcast as occurring at different time periods (commercial C at 10:15, commercial D at 10:30, and commercial E at 10:45), making it possible to capture the effect of each commercial broadcast with high resolution.

[0041] Next, the control unit 210 in the information processing device 200 creates a second time series data by omitting the KPIs for the 10 minutes after the broadcast of advertisement B (hereinafter also referred to as "calculation period KPIs") from the first time series data (Activity A140). To put this in terms of steps, the creation step creates a second time series data by omitting the calculation period KPIs, which are KPIs for a predetermined time period after the broadcast time of the advertisement, from the first time series data. Here, the predetermined time is 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 stages of information processing are performed: (1) The control unit 210 reads the KPI time series and broadcast time from the storage unit 220. (2) The control unit 210 performs 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] Figure 7 shows an example of the first time series data with the calculation period KPIs removed. In Figure 7, time series data 410 is shown as an example of the second time series data. Advertisement B is assumed to have been broadcast 7 times a day, and sections 441, 442, 443, 444, 445, 446, and 447 are shown as 10-minute intervals after the broadcast of advertisement B. In this example, the KPIs (calculation period KPIs) for each interval have been removed.

[0044] Next, the control unit 210 in the information processing device 200 estimates a third time series data by interpolating the missing parts based on the second time series data and the time series model (corresponding to the "first reference information" in the claim) (Activity A150). To put this in terms of steps, the estimation step estimates a third time series data by interpolating the missing parts based on the second time series data and the first reference information. Here, the first reference information is information that shows the relationship between the time series data before interpolation and the time series data after interpolation. In Activity A150, for example, the following three stages of information processing are executed: (1) The control unit 210 reads the second time series data and the time series model from the storage unit 220. (2) The control unit 210 performs estimation processing and estimates 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 trend and periodic terms is used, and the missing parts are interpolated by curve fitting. The details of the time series model are described below. The following equations are explained in the paper "Taylor, SJ, & Letham, B., Forecasting at scale, The American Statistician, 2018, Vol.72, No.1, p.37-45". Therefore, this paper is incorporated into this embodiment by referring to its entire disclosure.

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

[0047]

number

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

[0049]

number

[0050] Next, we will explain the trend terms in equations (1) and (2). Depending on the KPI time series being treated, either a nonlinear or linear trend is selected for the trend term. For example, when representing a saturating trend, the nonlinear trend shown in equation (3) is selected.

[0051]

number

[0052] The nonlinear trend in equation (3) is shown as an extended model of equation (4).

[0053]

number

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

[0055]

number

[0056] The linear trend in equation (5) is shown as an extended model of equation (6).

[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 time of the j-th transformation point, then equation (7) shows that the growth rate k changes as shown in equation (8). Equation (8) shows that each time the above transformation point occurs, δ j This means that the growth rate increases by a certain amount. Τ The δ term is a term that corrects the growth rate k so that the trend is continuous at the above transformation point, a(t) Τ The γ term is a term that corrects the offset m so that the trend is continuous at the above transformation point.

[0059]

number

[0060]

number

[0061] Next, we will explain the periodic terms in equations (1) and (2). The periodic terms are approximated by the Fourier series shown in equation (9).

[0062]

number

[0063] Since the broadcast period for TV commercials is often one week to one month for spot commercials, we considered it sufficient to express a one-week cycle when analyzing TV commercials. Therefore, in this embodiment, P in equation (9) was set to 7. Also, if the censoring order M is too large, it will result in the analysis of components containing noise, so it is necessary to set an appropriate value. Therefore, when we examined the periodic components contained in an arbitrary KPI time series to be analyzed using Fourier transform, we found that components with a period shorter than 1 / 4 (day) had almost no effect. Therefore, in this embodiment, M in equation (9) was set to 28. That is, (P=7) / (M=28), and the period was set to 1 / 4.

[0064] In other words, in the creation step, the first reference information is applied according to the type of KPI. This configuration can improve the accuracy of the third time series data.

[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, the confidence interval for 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 that shows the relationship between the time series data and the confidence interval. In Activity A160, for example, the following three stages of information processing are performed: (1) The control unit 210 reads the third time series data and statistical model from the storage unit 220. (2) The control unit 210 performs the calculation process and calculates the 95% confidence interval. (3) The control unit 210 stores the 95% confidence interval in the storage unit 220.

[0066] Figure 9 shows an example of setting a 95% confidence interval for a KPI time series. Time series data 420 is data for which a 95% confidence interval has been set for time series data 410. First, a hypothetical KPI was interpolated for each of the intervals 441, 442, 443, 444, 445, 446, and 447 for time series data 410. Next, a 95% confidence interval 460 was set.

[0067] Next, the control unit 210 in the information processing device 200 calculates the effect of advertisement B based on the 95% confidence interval and the calculation period KPI (Activity A170). In other words, in the calculation step, the effect of the advertisement is calculated based on the confidence interval and the calculation period KPI. In Activity A170, for example, the following three stages of information processing are performed: (1) The control unit 210 reads the 95% confidence interval and the calculation period KPI from the storage unit 220. (2) The control unit 210 performs the calculation process and calculates the effect of advertisement B. (3) The control unit 210 stores the effect of advertisement B in the storage unit 220.

[0068] Figure 10 shows an example of applying the calculation period KPI to a KPI time series. Time series data 430 is the data obtained by applying the calculation period KPI to time series data 420. The effect of ad B is the portion that exceeds the upper confidence limit 461. Ad effect 470 shows the effect of ad B.

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

[0070] According to Activity A170, by expressing the predetermined time in Activity A140 in minutes or seconds, it becomes possible to analyze the effectiveness of advertising without being excessively influenced by viewership ratings.

[0071] Next, the control unit 210 of the information processing device 200 transmits reception information to the terminal 300 for receiving analysis axes to analyze advertisement B (Activity A180). The analysis axes are appropriately selected from, for example, the number of advertising effects, the number of impressions, the number of advertising effects per unit impression (or unit viewership) (hereinafter also referred to as "index"), program name, material, area, broadcasting station, network, broadcast date, broadcast day of the week, broadcast time, program category, etc. In Activity A180, for example, the following two stages of information processing are performed: (1) The control unit 210 reads 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 terminal 300 receives reception information from the information processing device 200 (Activity A190). In Activity A190, for example, the following two stages of information processing are performed: (1) The communication unit 350 receives reception information from the information processing device 200. (2) Based on the reception information, the control unit 310 displays a screen on the display unit 330 for receiving the analysis axis of advertisement B.

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

[0074] Next, the control unit 310 in 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 stages of information processing are performed: (1) The control unit 310 reads 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 stages of information processing are performed: (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 effect 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 about the effect of the advertisement is generated. Here, the display information is information that displays the effect of advertisement B along the set analysis axis. In Activity A230, for example, the following three stages of information processing are executed: (1) The control unit 210 reads the effect of advertisement B and the analysis axis from the storage unit 220. (2) The control unit 210 executes the generation process and generates display information for displaying the effect 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 stages of information processing are performed: (1) The control unit 210 reads 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 terminal 300 receives display information from terminal 300 (activity A250). In activity A250, for example, the following two stages of information processing are performed: (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 terminal 300 displays the effect of advertisement B on the display unit 330 (activity A260). In activity A260, for example, the following three stages of information processing are performed: (1) The control unit 310 reads 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 terminal 300 receives a signal indicating whether or not to analyze advertisement B using a different analysis axis (activity A270). If the control unit 310 receives information for re-analysis (activity A270 YES), it proceeds to the processing of activity A200. If the control unit 310 does not receive information for re-analysis (activity A270 NO), it terminates the information processing method of this embodiment.

[0081] According to the information processing method of this embodiment, the effectiveness of advertising can be analyzed while taking into account the trends of KPIs. Furthermore, due to its simple configuration, the resources saved can be used for other core functions.

[0082] 4. Example of displaying analysis results Section 4 will explain examples of how to display analysis results.

[0083] Figure 12 shows an example of the results of an advertising effectiveness analysis (1). Here, we show the analysis results when different materials (Material A and 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 example shown in Figure 12 allows for the analysis of the acquisition efficiency of each material.

[0084] Figure 13 shows an example (2) of the results of an analysis of the effectiveness of an advertisement. Here, it shows the cumulative effectiveness of the advertisement (acquisition efficiency) relative to the cumulative number of impressions when different materials (material A, material B, and material C) are used in advertisements for the same product. In Figure 13, it was found that the advertisement was most effective when using material A, and although there was no significant difference between material B and material C, material B had a higher acquisition efficiency.

[0085] Figure 14 shows an example (3) of the results of an advertising effectiveness analysis. The analysis results in Figure 14 are assumed to apply to the entire broadcast area. In Figure 14, the vertical axis is set to time of day and the horizontal axis to day of the week, with an index (for example, "1.90" for 11 PM on Tuesday) entered in each box. The size of the index is then visualized as a heat map. This heat map allows for the comparison of various purchasing patterns (for example, all day, square shape, square shape, inverted L shape).

[0086] Figure 15 shows an example of a table for pivot analysis. This table stores acquired advertising statistics in the storage unit 220, processed into a format with columns as shown in Figure 15. Such a table allows for analysis of advertisements along various axes, such as "program x material," "program category x material," and "program category."

[0087] 5. Second Embodiment Section 5 describes a second embodiment of the present invention. In the second embodiment, when there are multiple advertisements for the same product, the information processing when another advertisement is broadcast within a predetermined time period (for example, 10 minutes) after the broadcast of one advertisement will be described.

[0088] Figure 16 shows an example of information processing when two different advertisements for the same product are broadcast consecutively within a predetermined time frame. Here, we show a case where one advertisement is broadcast at 8:43 PM (Broadcast A), followed by another advertisement for the same product at 8:44 PM (Broadcast B). The advertisements here are not limited to different advertisements; they could also be the same advertisement.

[0089] When advertisements are broadcast consecutively, there is an overlap of 10 minutes immediately following each broadcast, making it difficult to determine which advertisement is responsible for the resulting effect. Therefore, ad stock is applied as a residual effect of the advertisements to apportion the effects and estimate the effects of broadcast A and broadcast B. Ad stock refers to the sustained effect that appears after an advertisement, such as a television commercial, is broadcast. Figure 17 shows an example of ad stock used to apportion the effects of advertisements. The ad stock 610 at the nth minute after broadcast used here can be expressed, for example, by the following equation (10).

[0090]

number

[0091] Since the adstock 610 in equation (10) is not expressed as a commonly used geometric attenuation, tuning of the attenuation rate is unnecessary.

[0092] To put the information processing in the second embodiment into steps, in the calculation step, if an advertisement for the same product or service is delivered multiple times within a predetermined time, the effect of each delivered advertisement is allocated proportionally to calculate the effect of each advertisement. With this configuration, even when advertisements are delivered consecutively, the effect of each advertisement can be analyzed.

[0093] Although embodiments of the present invention have been described above, the present invention is not limited thereto and can be modified as appropriate without departing from the technical spirit of the invention.

[0094] 6. Variations Section 6 describes modifications of this embodiment. The following modifications can be combined as appropriate.

[0095] An embodiment of this design may be a program. This program is configured to cause a computer to execute each step of the information processing method of this design.

[0096] The control unit 210 writes (stores) and reads various data and information to the storage unit 220, but is not limited to this. For example, it may also use registers or cache memory within the control unit 210 to perform information processing for each activity.

[0097] In this embodiment, the advertisement is described as a TV commercial, but it is not limited to this. The advertisement is not limited to those delivered using broadcast waves from television or radio broadcasting stations, etc., but may also be, for example, digital advertisements (advertisements delivered through online channels such as websites and streaming content). The information processing device 200 can be applied to the analysis of various advertisements without being limited by the type of media or medium.

[0098] In this embodiment, time-series data of product A's KPIs was obtained by accessing a server owned by the advertiser, but this is not the only method. For example, the time-series data could be stored in the storage unit 220 of the information processing device 200 and obtained by reading that time-series data.

[0099] In this embodiment, the broadcast time of advertisement B was obtained by accessing a server that manages advertising statistics data, but this is not the only method. For example, the broadcast time may be stored in the storage unit 220 of the information processing device 200 and obtained by reading the broadcast time, or the advertising statistics data itself may be received and the broadcast time of advertisement B may be extracted from the advertising statistics data.

[0100] In this embodiment, the number of website visits associated with the advertised product was described as an example of a KPI, but it 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 specific keywords.

[0101] In this embodiment, the acquisition interval for time-series data is set to minutes or seconds, but is not limited to these units. Each time-series data may be acquired at time intervals of hours.

[0102] In this embodiment, 10 minutes was used as an example of a predetermined time, but it 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, it is 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 the range of any two of the numerical values ​​exemplified here. Furthermore, the duration is 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, and may be within the range of any two of the values ​​exemplified here.

[0103] In this embodiment, the confidence interval was described as a 95% confidence interval, but it is not limited to this. The confidence interval may be set appropriately depending on how the effectiveness of the advertisement is analyzed, for example, it may be 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 less likely it is to detect noise.

[0104] In this embodiment, Figure 14 is described as the analysis result corresponding to the entire broadcast area, but it is not limited to this. The analysis results in Figure 14 may be visualized for each area, or for each broadcasting station, for example.

[0105] In this embodiment, an index is entered in each frame of Figure 14, but this is not the only way. The numerical values ​​entered in Figure 14 may be, for example, the number of impressions or the number of ad effectiveness.

[0106] In this embodiment, an example has been described in which activities A110 to A270 are executed in this order, but the example is not limited to this. Each activity may be executed in any order, or in any combination and simultaneously.

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

[0108] 7. Other The product may be provided in any of the following embodiments.

[0109] (1) An information processing method comprising an acquisition step, a creation step, an estimation step, a calculation step, and a generation step, wherein the acquisition step acquires first time series data which is time series data of KPIs related to advertising of goods or services and the delivery time of the advertisement; the creation step creates second time series data which is calculation period KPIs which are KPIs within a predetermined time after the delivery time of the advertisement from the first time series data; and the estimation step generates a third time series which interpolates the missing portion based on the second time series data and first reference information. An information processing method comprising: estimating data; the first reference information being information showing the relationship between the time series data before interpolation and the time series data after interpolation; the calculation step calculating a confidence interval in the third time series data based on the third time series data and the second reference information; the second reference information being information showing the relationship between the time series data and the confidence interval; the calculation step calculating the effectiveness of the advertisement based on the confidence interval and the calculation period KPI; and the generation step generating display information for displaying information regarding the effectiveness of the advertisement.

[0110] This configuration allows for the analysis of advertising effectiveness while taking KPI trends into consideration. Furthermore, its simple structure allows for the use of saved resources for other core functions.

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

[0112] This approach allows for the analysis of advertising effectiveness without being overly influenced by viewership ratings.

[0113] (3) An 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] This approach allows for differentiating the effectiveness of each advertisement.

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

[0116] This configuration makes it possible to improve the accuracy of the third time-series data.

[0117] (5) An information processing method described in any one of (1) to (4) above, wherein in the calculation step, if the advertisement for the same product or service is delivered multiple times within the predetermined time, the effect of the delivered advertisement is apportioned and the effect of each advertisement is calculated.

[0118] This configuration allows for the analysis of the effectiveness of each advertisement, even when advertisements are delivered consecutively.

[0119] (6) An information processing system comprising a control unit, wherein the control unit is configured to perform each step of the information processing method described in any one of (1) to (5) above.

[0120] This configuration allows for the analysis of advertising effectiveness while taking KPI trends into consideration. Furthermore, its simple structure allows for faster computer processing speeds.

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

[0122] This configuration allows for the analysis of advertising effectiveness while taking KPI trends into consideration. Furthermore, its simple configuration contributes to reduced power consumption on the computer. Of course, this is not always the case. [Explanation of Symbols]

[0123] 100: Information Processing Systems 200: Information Processing Device 210: Control Unit 211: Acquisition Department 212: Creation Department 213: Estimation section 214: Calculation Unit 215 :Generation part 220: Storage section 250: Communications Department 260: Communications bus 300: Terminal 310: Control Unit 320: Storage section 330: Display section 340: Input section 350: Communications Department 360: Communications 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. Information processing method, It comprises an acquisition step, a creation step, an estimation step, a calculation step, and a generation step, In the acquisition step, the first time series data, which is time series data of KPIs related to the advertisement of the product or service, and the delivery time of the advertisement are acquired. In the creation step described above, a second time series data is created by omitting the calculation period KPI, which is the KPI within a predetermined time period after the delivery time of the advertisement, from the first time series data. In the estimation step described above, a third time series data is estimated by interpolating the missing portion based on the second time series data and the first reference information. The first reference information is information that shows the relationship between the time series data before interpolation and the time series data after interpolation. In the calculation step described above, a confidence interval for the third time series data is calculated based on the third time series data and the second reference information. The second reference information is information showing the relationship between the time series data and the confidence interval, In the calculation step described above, the effect of the advertisement is calculated based on the confidence interval and the calculation period KPI, In the generation step, display information is generated to display information regarding the effectiveness of the advertisement. Information processing methods.

2. In the information processing method described in claim 1, The predetermined time is expressed in minutes or seconds. Information processing methods.

3. In the information processing method described in claim 1, The aforementioned time-series data is data acquired at time intervals of minutes or seconds. Information processing methods.

4. In the information processing method described in claim 1, In the creation step, the first reference information is applied according to the type of KPI. Information processing methods.

5. In the information processing method described in claim 1, In the calculation step, if the advertisement for the same product or service is delivered multiple times within the predetermined time, the effect of each delivered advertisement is allocated proportionally to calculate the effect of each advertisement. Information processing methods.

6. An information processing system, Equipped with a control unit, The control unit is configured to perform each step in the information processing method described in any one of claims 1 to 5. Information processing system.

7. It is a program, The information processing method described in any one of claims 1 to 5 is configured to cause a computer to perform each step of the information processing method, program.

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