Advertising analysis device

Abstract

When multiple advertisements are run concurrently for a single product, the effectiveness of each individual advertisement can be analyzed separately. [Solution] The system includes a purchase information storage means that stores as time-series data the following in association: product identification information that identifies the target product; excess sales obtained by subtracting the base sales from the sales of the target product; advertising identification information that identifies each advertisement implemented for the promotion of the target product; and the date on which the sales were recorded and the advertisement was implemented; and an advertising effectiveness analysis means that calculates the excess sales for each piece of advertising identification information by performing notification analysis on different pieces of information on the same product identification information for different dates.

Description

Technical Field

[0001] The present disclosure relates to advertisement technology.

Background Art

[0002] An advertisement refers to actively and widely disseminating information related to products and services to the public, and is carried out to promote the sales of the products and services. Conventionally, advertisements related to products and services have been frequently implemented, but it has been a difficult situation to implement effective advertisements and verify the effects of the advertisements with high accuracy.

[0003] Under such circumstances, technology development for verifying advertisement effects has been actively carried out. For example, Patent Document 1 proposes a technology that notifies advertisements considered to have high effects in consideration of the user's current situation and the user's preference tendency, and verifies the effects of the advertisements.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, the above-described conventional technology has a problem that when a plurality of advertisements for a single product are implemented in an overlapping manner, the effect of each individual implemented advertisement cannot be separately grasped.

[0006] In view of the above problems, the present invention aims to provide an advertisement analysis apparatus that can separately grasp the effect of each individual implemented advertisement when a plurality of advertisements for a single product are implemented in an overlapping manner.

Means for Solving the Problems

[0007] One form of the disclosed advertising analysis device is characterized by having a purchase information storage means that stores as time-series data, associating product identification information that identifies a target product, excess sales obtained by subtracting base sales from sales related to the target product, advertising identification information that identifies each advertisement implemented for the promotion of the target product, and the date on which the sales were recorded and the advertisement was implemented; and an advertising effectiveness analysis means that calculates the excess sales for each piece of advertising identification information by performing numerical analysis on the information for different dates relating to a single piece of product identification information.

[0008] Another form of the disclosed advertising analysis device is characterized by having a purchase information storage means that stores as time-series data the following in association: product identification information that identifies a target product; excess sales obtained by subtracting base sales from sales related to the target product; advertising identification information that identifies each advertisement implemented for the promotion of the target product; the degree of exposure in each advertisement; and the date on which the sales were recorded and the advertisement was implemented; and an advertising effectiveness analysis means that calculates the excess sales for each advertising identification information, taking into account the degree of exposure, by performing numerical analysis on the information for different dates relating to a single piece of product identification information. [Effects of the Invention]

[0009] The disclosed advertising analysis device can separate and understand the effect of each individual advertisement when multiple advertisements are run concurrently for a single product. [Brief explanation of the drawing]

[0010] [Figure 1] This diagram shows an overview of the advertising analysis device according to this embodiment. [Figure 2] This is a functional block diagram of the advertising analysis device according to this embodiment. [Figure 3] This figure shows an example of a purchase information storage means according to this embodiment. [Figure 4] This figure shows an example of a purchase information storage means according to this embodiment. [Figure 5]This figure shows an example of the hardware configuration of the advertising analysis device according to this embodiment. [Figure 6] This flowchart shows an example of processing using the advertising analysis device according to this embodiment (without considering exposure level 280). [Figure 7] This flowchart shows an example of processing using the advertising analysis device according to this embodiment (considering an exposure level of 280). [Modes for carrying out the invention]

[0011] The embodiments for carrying out the present invention will be described with reference to the drawings. (Operating principle of the advertising analysis device according to this embodiment)

[0012] The operating principle of the advertising analysis device (hereinafter simply referred to as "this device") 100 according to this embodiment will be explained using Figures 1 to 4. Figure 1 is a diagram showing the connection relationship between this device 100 and other devices, and Figure 2 is a functional block diagram of this device 100. Figures 3 and 4 are diagrams showing an example of the purchase information storage means 110, which will be described later.

[0013] As shown in Figure 1, the device 100 is connected to a user terminal 310 operated by a user 300 via a communication network 320. The communication network 320 may be either wired or wireless. The user terminal 310 may be a mobile information terminal such as a smartphone, or a desktop or notebook personal computer. As shown in Figure 2, the device 100 includes a purchase information storage means 110, a target information receiving means 120, and an advertising effectiveness analysis means 130.

[0014] The purchase information storage means 110 stores, as time-series data in association with one another: product identification information 220 for identifying the target product 210, excess sales 250 obtained by subtracting reference sales 240 from the sales 230 related to the product 210, advertisement identification information 270 for identifying each advertisement 260 implemented for sales promotion of the product 210, the exposure degree 280 of each advertisement 260, and the date 290 on which the sales 230 are recorded and the advertisement 260 is implemented.

[0015] The sales 230 are, for example, daily sales of the product 210, which are sales matching the period of the date 290. The reference sales 240 can be appropriately determined for each product 210, and share the same unit as the sales 230. The excess sales 250 are information representing so-called added value.

[0016] The advertisements 260 are, for example, digital advertisements, advertisements using newspapers, magazines, radio, and television as media, transit advertisements, and the like, and may be advertisements using other media. The exposure degree 280 is, for example, the number of displays of the advertisement 260, or the amount (cost) invested in the advertisement 260.

[0017] FIG. 3 is an example of data that does not include the exposure degree 280. As shown in FIG. 3, the purchase information storage means 110 associates, for example, date 290: April 1, product identification information 270: Detergent A, excess sales 250: 500 (unit is arbitrary), advertisement identification information 270: Advertisement B, Advertisement C, Advertisement D, Advertisement E, and stores them as time-series data. In addition, the purchase information storage means 110 associates, for example, date 290: April 2, product identification information 270: Detergent A, excess sales 250: 400 (unit is arbitrary), advertisement identification information 270: Advertisement C, Advertisement D, Advertisement E, and stores them as time-series data.

[0018] Figure 4 is an example of data including the exposure degree 280. As shown in Figure 4, the purchase information storage unit 110 stores, as time-series data in association with each other, for example, date 290: April 1, product identification information 270: Detergent A, excess sales 250: 500 (unit is arbitrary), (advertisement identification information 270, exposure degree 280) = (Advertisement B, 10 (unit is arbitrary)), (Advertisement C, 10 (unit is arbitrary)), (Advertisement D, 10 (unit is arbitrary)), (Advertisement E, 10 (unit is arbitrary)). In addition, the purchase information storage unit 110 stores, as time-series data in association with each other, for example, date 290: April 3, product identification information 270: Detergent A, excess sales 250: 300 (unit is arbitrary), (advertisement identification information 270, exposure degree 280) = (Advertisement B, 15 (unit is arbitrary)), (Advertisement D, 10 (unit is arbitrary)), (Advertisement E, 10 (unit is arbitrary)). Note that (advertisement identification information 270, exposure degree 280) = (Advertisement C, 0 (unit is arbitrary)) may be added for consideration. The target information reception unit 120 receives, from the user terminal 310, product identification information 220 related to the product 210 for which the present apparatus 100 is to perform analysis from now on.

[0019] The advertisement effect analysis unit 130 calculates the excess sales 250 for each piece of advertisement identification information 270 by performing numerical analysis on the information stored in the purchase information storage unit 110, which is the information of different dates 290 related to the product identification information 220 received by the target information reception unit 120. Note that the method of numerical analysis is not limited.

[0020] The advertisement effect analysis unit 130, for example, appropriately calculates differences for data of different dates 290 related to product identification information 220: Detergent A with respect to the information shown in Figure 3, so as to calculate the combinations of (advertisement identification information 270, excess sales 250) = (Advertisement B, 100), (Advertisement C, 200), (Advertisement D, 150), (Advertisement E, 50).

[0021] Furthermore, the advertising effectiveness analysis means 130 may also be configured to calculate excess sales 250 for each advertising identification information 270, taking into account the degree of exposure 280, by performing numerical analysis on information for different dates 290 relating to product identification information 220 received by the target information receiving means 120, which is stored in the purchase information storage means 110. The method of numerical analysis is not limited.

[0022] The advertising effectiveness analysis means 130 calculates the following combinations for the information shown in Figure 4, for example, by taking the difference appropriately for data on different dates 290 related to product identification information 220: detergent A, considering the degree of exposure 280, and taking the difference accordingly: (advertising identification information 270, excess sales 250) = (advertising B, 300), (advertising C, 50), (advertising D, 50), (advertising E, 100).

[0023] Based on the operating principle described above, the device 100 can separately determine the effect of each advertisement 260 when multiple advertisements 260 are superimposed for a single product 210. (Hardware configuration of the advertising analysis device according to this embodiment)

[0024] An example of the hardware configuration of the device 100 will be explained using Figure 5. Figure 5 is a diagram showing an example of the hardware configuration of the device 100. As shown in Figure 5, the device 100 has a CPU (Central Processing Unit) 510, ROM (Read-Only Memory) 520, RAM (Random Access Memory) 530, auxiliary storage device 540, communication I / F 550, input device 560, display device 570, and storage medium I / F 580.

[0025] The CPU 510 is a device that executes programs stored in the ROM 520. It processes data loaded into the RAM 530 according to program instructions and controls the entire device 100. The ROM 520 stores the programs and data that the CPU 510 will execute. When the CPU 510 executes a program stored in the ROM 520, the RAM 530 loads the programs and data to be executed and temporarily holds the calculation data during the calculation.

[0026] The auxiliary storage device 540 is a device that stores the operating system (OS), which is the basic software, and application programs related to this embodiment, along with related data. The auxiliary storage device 540 is, for example, an HDD (Hard Disk Drive) or flash memory, and includes the purchase information storage means 110.

[0027] The communication interface 550 is an interface for exchanging data with other devices 310 that provide communication functions, by connecting to a communication network 320 such as a wired or wireless LAN (Local Area Network) or the Internet.

[0028] The input device 560 is a device for inputting data into the main device 100, such as a keyboard. The display device (output device) 570 is a device consisting of an LCD (Liquid Crystal Display) or the like, and functions as a user interface for the user to use the functions of the main device 100 and to make various settings. The storage medium I / F 580 is an interface for sending and receiving data with storage media 590 such as CD-ROMs, DVD-ROMs, and USB memory.

[0029] Each of the means of this device 100 may be realized by the CPU 510 executing a program corresponding to each means stored in the ROM 520 or auxiliary storage device 540. Alternatively, each of the means of this device 100 may be realized by the processing related to each means being implemented as hardware. Furthermore, the program according to the present invention may be read from an external server device via a communication I / F 550, or read from a storage medium 590 via a storage medium I / F 580, and the device 100 may execute the program. (Example of processing by the advertising analysis device according to this embodiment) (1) Example of processing when the exposure level is not set to 280 The flow of a processing example using this device 100 will be explained using Figure 6. Figure 6 is a flowchart showing the flow of a processing example using this device 100.

[0030] In S10, the target information receiving means 120 receives product identification information 220 from the user terminal 310 regarding the product 210 that the device 100 is about to analyze. For example, the target information receiving means 120 receives "detergent A" as product identification information 220.

[0031] In S20, the advertising effectiveness analysis means 130 performs numerical analysis on information stored in the purchase information storage means 110, specifically on information for different dates 290 relating to the product identification information 220 received in S10, thereby calculating the excess sales revenue 250 for each piece of advertising identification information 270. The method of numerical analysis is not limited.

[0032] The advertising effectiveness analysis means 130 calculates the following combinations (advertising identification information 270, excess sales 250) = (advertising B, 100), (advertising C, 200), (advertising D, 150), (advertising E, 50) by taking the difference between data for different dates 290 related to product identification information 220: detergent A, and the information shown in Figure 3.

[0033] By performing the above-described process, the device 100 can separately determine the effect of each advertisement 260 when multiple advertisements 260 are superimposed on a single product 210. (2) Example of processing when exposure level is 280 The flow of a processing example using this device 100 will be explained using Figure 7. Figure 7 is a flowchart showing the flow of a processing example using this device 100.

[0034] In S110, the target information receiving means 120 receives product identification information 220 from the user terminal 310 regarding the product 210 that the device 100 is about to analyze. For example, the target information receiving means 120 receives "detergent A" as product identification information 220.

[0035] In S120, the advertising effectiveness analysis means 130 performs numerical analysis on information stored in the purchase information storage means 110, specifically on information for different dates 290 relating to the product identification information 220 received in S110, to calculate excess sales 250 for each advertising identification information 270, taking into account the degree of exposure 280. The method of numerical analysis is not limited.

[0036] The advertising effectiveness analysis means 130 calculates the following combinations for the information shown in Figure 4, for example, by taking into account the degree of exposure 280, and taking the difference between data for different dates 290 regarding product identification information 220: detergent A: (advertising identification information 270, excess sales 250) = (advertising B, 300), (advertising C, 50), (advertising D, 50), (advertising E, 100).

[0037] By performing the above-described process, the device 100 can separately determine the effect of each advertisement 260 when multiple advertisements 260 are superimposed on a single product 210. ru.

[0038] Although embodiments of the present invention have been described in detail above, the present invention is not limited to these specific embodiments, and various modifications and changes are possible within the scope of the gist of the present invention as described in the claims. [Explanation of Symbols]

[0039] 100 Advertising Analysis Device 110 Purchasing information storage means 120 Target Information Reception Method 130 Methods for analyzing advertising effectiveness 210 products 220 Product Identification Information 230 Sales 240 Base Sales 250 sales exceeding 250 260 Advertisements 270 Ad Identifiers 280 Exposure level in advertising Date 290 300 users 310 User Terminals 320 Communication Networks 510 CPU 520 ROM 530 RAM 540 Auxiliary storage 550 Communication Interfaces 560 Input Device 570 Output device 580 Storage Media Interface 590 Storage medium

Claims

1. A purchase information storage means stores, as time-series data, product identification information that identifies the target product, excess sales obtained by subtracting the base sales from the sales of the target product, advertising identification information that identifies each advertisement implemented for the promotion of the target product, and the date on which the sales were recorded and the advertisements were implemented. An advertising analysis device characterized by having an advertising effectiveness analysis means that calculates the excess sales for each piece of advertising identification information by performing numerical analysis on different date information relating to one piece of product identification information.

2. A purchase information storage means stores, as time-series data, the following in association: product identification information that identifies the target product; excess sales obtained by subtracting the base sales from the sales of the target product; advertising identification information that identifies each advertisement implemented for the promotion of the target product; the degree of exposure in each advertisement; and the date on which the sales were recorded and the advertisement was implemented. An advertising analysis device characterized by having an advertising effectiveness analysis means that calculates excess sales for each advertising identification information, taking into account the degree of exposure, by performing numerical analysis on different date information relating to one of the aforementioned product identification information.

3. An advertising analysis method performed by a computer equipped with a purchase information storage means that stores as time-series data the following in association: product identification information that identifies the target product; excess sales obtained by subtracting the base sales from the sales of the target product; advertising identification information that identifies each advertisement implemented for the promotion of the target product; and the date on which the sales were recorded and the advertisements were implemented. An advertising analysis method characterized in that the advertising effectiveness analysis means includes the step of calculating the excess sales for each piece of advertising identification information by performing numerical analysis on different date information relating to a single piece of product identification information.

4. An advertising analysis method performed by a computer equipped with a purchase information storage means that stores, as time-series data, product identification information that identifies the target product, excess sales obtained by subtracting the base sales from the sales of the target product, advertising identification information that identifies each advertisement implemented for the promotion of the target product, the degree of exposure in each advertisement, and the date on which the sales were recorded and the advertisement was implemented. An advertising analysis method characterized in that the advertising effectiveness analysis means includes the step of calculating excess sales for each advertising identification information, taking into account the degree of exposure, by performing numerical analysis on different date information relating to a single product identification information.

5. An advertising analysis program for causing a computer to perform the method described in claim 3 or 4.

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