JP2024058374A - Kpi measurement system and kpi measurement method - Google Patents

Abstract

To provide a technique for measuring KPI for evaluating the business performance of a retail store or the like to be evaluated, on the basis of image data captured by a mobile body.SOLUTION: In a KPI measurement system, a server device 1 includes: a transmitting/receiving control unit 11a which communicates with a self-propelled robot; a travel control unit 11b which controls travel of the self-propelled robot 2; an imaging control unit 11c which controls imaging; an image analysis unit 11d which analyzes image data from the self-propelled robot 2; a KPI measurement unit 11e which measures KPI on the basis of a result analyzed by the image analysis unit 11 and sales information from a management server 4; and an output unit 11g which outputs the KPI. The image analysis unit 111d analyzes at least one of: a visual recognition rate and a visual recognition place of a customer for an evaluation target; a travel direction and travel speed of the customer; a visual recognition rate and a stop rate of the customer stopping in front of the evaluation target; a visual recognition rate and a pick-up rate of the customer picking up a commodity to be evaluated.SELECTED DRAWING: Figure 2

Description

The present invention relates to a KPI measurement system and a KPI measurement method using a self-propelled robot.

Traditionally, retail stores and other businesses have sought to improve the efficiency of product promotions, such as through product displays and POP displays, in order to promote product sales and ultimately increase sales. Key performance indicators (KPIs, hereafter abbreviated as "KPIs") are measured as indicators for evaluating the performance of these efforts, and are used to further improve operations.

Nowadays, service robots are also penetrating the market, and service robots equipped with various functions are being used for sales promotion in stores.

Patent document 1 discloses a robot control device that moves a robot to a customer's stopping position based on the area and stay time recorded in a customer movement table, and has the robot, once it has reached the customer, make product suggestions based on product categories related to the area where the customer has most recently stayed.

JP 2019-49785 A

However, Patent Document 1 does not disclose the calculation of, for example, the direction and speed of a customer's walking movement, the rate at which the customer stops, etc., based on image data captured by a self-propelled robot in order to measure KPIs for evaluating the performance of a retail store or the like.

The present invention was made in consideration of these problems, and its purpose is to provide a technology that measures KPIs that evaluate the performance of the target retail store or the like, based on image data captured by a self-propelled robot.

In order to solve the above problem, a KPI measurement system according to one aspect of the present invention is a KPI measurement system including a server device and a self-propelled robot, the server device including a transmission/reception control unit that communicates with the self-propelled robot, a travel control unit that controls the travel of the self-propelled robot, a photography control unit that controls photography by the self-propelled robot, an image analysis unit that analyzes image data from the self-propelled robot received by the transmission/reception control unit, and a KPI measurement unit that measures KPIs based on the analysis results by the image analysis unit and sales information from a management server received by the transmission/reception control unit. The self-propelled robot has a camera unit, a drive unit, and a control unit that controls the camera unit to take pictures and the drive unit to move based on the control of the server device, and controls the image data obtained by taking pictures to be sent to the server device, and the image analysis unit analyzes at least one of the customer's visibility rate and viewing location of the evaluation target, the customer's approach direction and retreat direction and their walking speed, the customer's visibility rate and stopping rate in front of the evaluation target, and the customer's visibility rate and pick-up rate of the evaluation target product.

In another aspect of the present invention, a KPI measurement method using a server device and a self-propelled robot, the server device controls the travel of the self-propelled robot and controls the self-propelled robot to take pictures, and the self-propelled robot controls the photography by a camera unit and the travel by a drive unit based on the control of the server device, and transmits image data obtained by photography to the server device, and the server device analyzes the image data from the self-propelled robot, measures KPIs based on the results of the analysis and sales information from a management server, and outputs the measured KPIs, and in analyzing the image data, at least one of the customer's visibility rate and viewing location of the evaluation target, the customer's traveling direction and traveling speed, the customer's visibility rate and stopping rate in front of the evaluation target, and the customer's visibility rate and pick-up rate of the evaluation target product is analyzed.

The present invention provides a technology that measures KPIs that evaluate the performance of a retail store or other business that is being evaluated, based on image data captured by a self-propelled robot.

FIG. 1 is a configuration diagram of a KPI measurement system according to an embodiment of the present invention. 2A and 2B are diagrams showing the configuration of the server device. FIG. 3 is a configuration diagram of the self-propelled robot. FIG. 4 is a configuration diagram of a terminal device. FIG. 5 is a flowchart showing a processing procedure performed by the KPI measurement system. FIG. 6 is a flowchart showing the process of S4 in FIG. 5 in detail. 7A and 7B are diagrams showing the relationship between the sales floor visibility rate and the visibility location. 8(a) and 8(b) are diagrams showing a comparison of conversions. 9(a) and 9(b) are diagrams showing walking direction and walking speed. 10(a) and 9(b) are diagrams showing a comparison of conversions. FIG. 11 is a diagram showing the relationship between the visibility rate and the stopping rate. FIG. 12 is a diagram showing the relationship between the visibility rate and the pick-up rate. 13(a) and 13(b) are diagrams showing the relationship between walking speed and purchase rate.

The following describes an embodiment of the present invention with reference to the drawings.

Figure 1 shows and explains the configuration of a KPI measurement system according to an embodiment of the present invention.

As shown in the figure, the KPI measurement system according to this embodiment is configured by connecting a server device 1, a self-propelled robot 2, a POS register system 3, a management server 4, and a store manager or consultant terminal device 6 so that they can communicate freely via a communication network 5 such as the Internet.

In this configuration, server device 1 remotely controls the self-propelled robot 2's travel and photography within the store based on predetermined travel route information, photography timing information, etc. Self-propelled robot 2 travels within the store under the control of server device 1, taking photographs at predetermined times while stopping at fixed points, etc., and transmits the obtained image data to server device 1. When server device 1 receives this image data, it performs image analysis. More specifically, it analyzes the congestion situation, the amount of items displayed on the shelves, the stopping rate, which is the probability that customers will stop, the pick-up rate, which is the probability that products will be picked up, the customers' visual targets, and walking (direction, speed, etc.).

The management server 4 acquires sales information from the POS register in real time, and transmits the sales information to the server device 1 in response to a request from the server device 1, or periodically. When the server device 1 receives the sales information from the management server device 4, it measures KPIs based on the sales information and the image analysis results. The server device 1 generates and outputs the measured KPIs or a report that processes the measured KPIs. The server device 1 generates display data for the analysis results (KPIs) or the report that processes the measured KPIs, and transmits the display data to the terminal device 6 of the store manager or consultant for display.

In this way, with the KPI measurement system according to this embodiment, the locations within the store where performance should be evaluated can be set in advance using the driving route, fixed points, and timing of photography, etc., and the self-propelled robot can be remotely controlled based on these settings to take photographs, thereby acquiring image data, which can then be analyzed to measure KPIs, making it possible to carry out the performance evaluation desired by the store.

Figures 2(a) and 2(b) show and explain the detailed configuration of the server device. In detail, Figure 2(a) is a diagram showing the configuration of the entire server device, and Figure 2(b) is a diagram showing the detailed functions of the image analysis unit in the control unit.

As shown in these figures, the server device 1 has a control unit 11, a communication unit 12, and a storage unit 13. The control unit 11, the communication unit 12, and the storage unit 13 are communicatively connected via a control bus. In addition to these components, the server device 1 may also have input units such as a keyboard and a mouse, and a display unit such as a liquid crystal display that displays various information.

The communication unit 12 is realized, for example, by a network interface card (NIC) or the like, and is a communication interface that is connected to a communication network 5 such as the Internet via a wired or wireless connection and communicates with the self-propelled robot 2, the management server 4, etc.

The storage unit 13 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, a hard disk drive (HDD), an optical disk device, or the like, and stores in advance the programs to be executed by the control unit 11. The storage unit 13 also has a walking information storage unit 14, a shooting information storage unit 15, an analysis result storage unit 16, and a KPI storage unit 17.

The driving information storage unit 14 stores driving information such as the driving route that the self-propelled robot 2 should travel within the store. The photography information storage unit 15 stores photography information such as location information where the self-propelled robot 2 should take photos and the timing of photography. The analysis result storage unit 16 stores and accumulates the analysis results by the image analysis unit 11d. And the KPI storage unit 17 stores and accumulates the KPIs measured by the KPI measurement unit 11e.

The control unit 11 is realized by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), and functions as a transmission/reception control unit 11a, a driving control unit 11b, an imaging control unit 11c, an image analysis unit 11d, a KPI measurement unit 11e, a generation unit 11f, and an output unit 11g by executing a program stored in the memory unit 13. The control unit 11 may be configured by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Array).

In this configuration, the transmission/reception control unit 11a controls communication with the self-propelled robot 2 and the management server 4 via the communication unit 12. More specifically, the transmission/reception control unit 11a functions as a transmission unit that transmits driving information, shooting information, etc. to the self-propelled robot 2, and a reception unit that receives image data from the self-propelled robot 2 and sales information, etc. from the management server 4.

The driving control unit 11b remotely controls the driving of the self-propelled robot 2 based on the driving information stored in the driving information storage unit 14. The photography control unit 11c remotely controls the photography by the self-propelled robot 2 based on the photography information stored in the photography information storage unit 15.

The image analysis unit 11d analyzes image data from the self-propelled robot 2. More specifically, as shown in FIG. 2(b), the image analysis unit 11d has a congestion situation analysis unit 11d-1, a display amount analysis unit 11d-2, a stopping rate analysis unit 11d-3, a pick-up rate analysis unit 11d-4, a visual recognition analysis unit 11d-5, and a walking analysis unit 11d-6.

The crowded situation analysis unit 11d-1 analyzes the image data, recognizes the presence of customers, and calculates the number of customers and the degree of closeness, thereby analyzing the crowded situation. The display quantity analysis unit 11d-2 analyzes the image data of the shelves, recognizes the products displayed and their numbers, and analyzes the display quantity. The stopping rate analysis unit 11d-3 analyzes the image data, calculates the presence and movement of customers, and calculates the proportion of customers who do not move their positions with both feet on the ground in the area to the total number of customers who are recognized to have entered the area within a target time, thereby analyzing the stopping rate.

The pick-up rate analysis unit 11d-4 analyzes the image data, recognizes the presence of customers, recognizes when the customers are picking up products, calculates the ratio of the number of customers who have picked up products to the total number of recognized customers, and analyzes the pick-up rate. The visibility analysis unit 11d-5 analyzes the image data, recognizes customers, and analyzes the line of sight of each customer by calculating the ratio of the number of customers who focus their eyes on a specific shelf or other point and analyzing the visibility. The walking analysis unit 11d-6 analyzes the image data, recognizes customers, and calculates the direction of movement of each customer entering the area and the moving speed at the time of entry based on the distance moved and the time required to enter the area, and analyzes the walking.

The KPI measurement unit 11e measures the KPIs based on the sales information acquired from the management server 4 and the analysis results by the image analysis unit 11d. The generation unit 11f generates a report on the measured KPIs, and the output unit 11g outputs the report.

Figure 3 shows and explains the detailed configuration of the self-propelled robot.

As shown in the figure, the self-propelled robot 2 has a control unit 21, a communication unit 22, a camera unit 23, an operation input unit 24, a memory unit 25, and a drive unit 26.

The communication unit 22 is realized by, for example, a NIC, and is connected to a communication network 5 such as the Internet by wire or wirelessly, and is a communication interface for communicating with the server device 1, etc. The camera unit 23 has at least an image capturing function and a sound collecting function, and takes pictures at points instructed by the server device 1 during the traveling process. The operation input unit 24 has an emergency stop button and various operation switches for switching to manual operation, etc. The memory unit 13 is realized by, for example, a semiconductor memory element such as RAM or flash memory, a hard disk drive, or an optical disk device, and stores in advance the program to be executed by the control unit 21. The drive unit 26 has a motor, wheels, etc., and drives the self-propelled robot 2 to travel by itself along the travel route under the control of the control unit 21.

The control unit 21 functions as a main control unit 21a, a transmission/reception control unit 21b, a position information acquisition unit 21c, and a drive control unit 21d by executing the programs in the memory unit 25.

The main control unit 21a is responsible for the overall control of the self-propelled robot 2. The transmission/reception control unit 21b functions as a receiving unit that receives driving information and shooting information sent from the server device 1 via the communication unit 22, and as a transmitting unit that transmits image data obtained by shooting to the server device 1 via the communication unit 22. The position information acquisition unit 21c acquires current position information of the self-propelled robot 2, for example, using a GPS function. Then, the drive control unit 21d controls the drive unit 26 to drive the robot based on the driving information and shooting information sent from the server device 1, and controls the camera unit 23 to take photos.

Figure 4 shows and explains the configuration of the store manager or consultant's terminal device.

As shown in the figure, the terminal device 6 has a control unit 61, a communication unit 62, a display unit 63, an operation input unit 64, and a memory unit 65. The units 61 to 65 are connected to each other so as to be able to communicate freely via a bus line. The communication unit 62 is realized, for example, by a NIC or the like, and is a communication interface that is connected to a communication network 5 such as the Internet by wire or wirelessly and communicates with the server device 1, etc.

The operation input unit 64 is realized by a mouse, a keyboard, etc., and accepts various operation inputs by the user. The display unit 63 is realized by a liquid crystal display, etc., and performs various displays. The operation input unit 64 and the display unit 63 may be integrated into a touch panel.

The storage unit 25 is realized, for example, by a semiconductor memory element such as a RAM or a flash memory, a HDD, or an optical disk device, and stores the programs executed by the control unit 61. The control unit 61 is realized, for example, by a CPU or an MPU, and functions as a main control unit 61a, a display control unit 61c, and a transmission/reception control unit 61b by executing the programs stored in the storage unit 65.

In this configuration, the main control unit 21a is responsible for controlling the entire terminal device. The display control unit 61c controls the display on the display unit 63 based on the analysis results (KPIs) received by the transmission/reception control unit 61b or display data related to a report that has been processed from the analysis results. The transmission/reception control unit 61b functions as a transmission unit that transmits various requests to the server device 1 and a reception unit that receives display data from the server device 1.

Below, the processing procedure of the KPI measurement system according to the embodiment of the present invention will be described in detail with reference to the flowchart in FIG. 5. Here, the explanation will be given with reference to the flowchart in FIG. 6 and the analysis results in FIG. 7 to FIG. 13 as appropriate. Note that this processing procedure also corresponds to the KPI measurement method according to this embodiment.

First, in the server device 1, the driving control unit 11b remotely controls the driving of the self-propelled robot 2 based on the driving information stored in the driving information storage unit 14 (S1). Furthermore, the photography control unit 11c remotely controls the photography by the self-propelled robot 2 based on the photography information stored in the photography information storage unit 15 (S2).

Then, when the transmission/reception control unit 11a receives image data from the self-propelled robot 2 (S3), the image analysis unit 11d analyzes the image data from the self-propelled robot 2 (S4).

More specifically, as shown in FIG. 6, the visibility analysis unit 11d-5 analyzes the image data, recognizes customers, and analyzes the line of sight direction and range of each customer, as well as changes therein, to calculate the proportion of each customer's visibility to a specific shelf or other point (visual location), thereby analyzing the relationship between the visibility rate and the visual location (S11).

Then, the gait analysis unit 11d-6 analyzes the image data, recognizes the customers, calculates the running direction and running speed of each customer, and analyzes their walking (S12).

Then, the stopping rate analysis unit 11d-3 analyzes the image data, recognizes the customers, calculates their movements, and calculates the percentage of the number of customers who do not move their positions with both feet on the ground in the area to the total number of customers who are recognized as having entered the area within the target time period, thereby analyzing the stopping rate, and analyzing the relationship between the visibility rate and the stopping rate in combination with the analysis results of the visibility analysis unit 11d-5 described above (S13).

Furthermore, the pick-up rate analysis unit 11d-4 analyzes the image data, recognizes the customer, recognizes the state in which the customer is picking up the product, calculates the ratio of the number of customers who have picked up the product to the total number of recognized customers, analyzes the pick-up rate, and combines the analysis results of the visibility analysis unit 11d-5 described above to analyze the relationship between the visibility rate and the pick-up rate (S14).

Returning to FIG. 5, the KPI measurement unit 11e then measures the KPIs based on the sales information acquired from the management server 4 and the analysis results by the image analysis unit 11d (S5).

More specifically, the analysis in step S11 gives the analysis results shown in FIG. 7(a) and FIG. 7(b). Here, Test A is a case where an MD panel is used as a POP, and Test B is a case where a POP is not used. FIG. 7(a) shows the analysis result of Test A, and FIG. 7(b) shows the analysis result of Test B. From these comparisons, the analysis results show that Test A has a higher visibility rate on the sales floor, and that the effect of making the product visible when passing through the sales floor is greater than the effect of hyperopia. When sales information is reflected in these results, the results shown in FIG. 8(a) and FIG. 8(b) are obtained. FIG. 8(a) shows the results of Test A, and FIG. 8(b) shows the results of Test B. From these comparisons, the analysis results show that Test A has a higher effect in terms of visibility rate, stopping rate, pick-up rate, and purchase (conversion). The KPI measurement unit 11e measures the contribution of the MD panel to improving visibility rate, stopping rate, pick-up rate, and purchase rate as KPIs based on sales information and analysis results.

Analysis by step S12 gives the analysis results shown in Fig. 9(a) and Fig. 9(b). Here, Test A is a case where MD panels are used, and Test B is a case where POP is not used. Fig. 9(a) shows the analysis result of Test A, and Fig. 9(b) shows the analysis result of Test B. From these comparisons, the analysis result is obtained that the walking speed at the time of entering the sales floor remains the same or is faster than that of Test B. The walking speed at the time of entering the sales floor tends to be constant or faster when a customer who is wandering around with the intention of purchasing in advance visually recognizes the product, and the purchase rate tends to be higher (see Fig. 13(a) and Fig. 13(b)). When sales information is reflected in this result, the results shown in Fig. 10(a) and Fig. 10(b) are obtained. Fig. 10(a) shows the result of Test A, and Fig. 10(b) shows the result of Test B. From these comparisons, the analysis result is obtained that Test A shows a higher effect in both the pick-up rate and purchase (conversion). By using the MD panel, it is possible to determine whether the walking speed when entering the sales floor does not decrease and whether the product has been successfully recognized by customers wandering around with the intention of purchasing the desired product. Based on the sales information and analysis results, the KPI measurement unit 11e measures the contribution of the MD panel to the reduction in walking speed, the improvement in the pick-up rate, and the improvement in the purchase rate as KPIs.

The analysis in step S13 produces the results shown in Figure 11. The figure shows that there are sales areas where POP display improves visibility and stopover rates compared to no POP display, leading to purchases (conversions), and there are sales areas where POP display does not lead to purchases (conversions). Based on the sales information and the analysis results, the KPI measurement unit 11e measures the contribution of POP to improved visibility, stopover rates, and purchase rates as KPIs, and suggests POPs that do not lead to purchases (conversions) that should have their display method and display content reviewed.

The analysis in step S14 produces the results shown in Figure 12. From this figure, the analysis result shows that there are sales areas where POP display improves visibility and pick-up rates compared to no POP display, leading to purchases (conversion), and there are sales areas where POP display does not lead to purchases (conversion). Based on the sales information and the analysis results, the KPI measurement unit 11e measures the contribution of POP to improved visibility, pick-up rate, and purchase rate as KPIs, and suggests POPs that do not lead to purchases (conversion) that should have their display method and display content reviewed.

In this way, the generation unit 11f generates a report on the measured KPI, and the output unit 11g outputs the report (S6). When outputting, the generation unit 11f generates display data related to the KPI (screen images in Figs. 7 to 13) or a report obtained by processing the KPI, and the transmission/reception control unit 11a transmits the display data to the terminal device 6 of the store manager or consultant. In the terminal device 6, the transmission/reception control unit 61b receives the display data, and under the control of the display control unit 61c, a screen of the KPI or a report obtained by processing the KPI is displayed on the display unit 63. This completes the series of processes. It is to be noted that this embodiment also includes measuring the KPI based on the results of the analysis in at least one of steps S1 to S14.

As described above, the present invention provides the following advantages:

First, in a KPI measurement system including a server device 1 and a self-propelled robot 2, the server device 1 includes a transmission/reception control unit 11a that communicates with the self-propelled robot, a travel control unit 11b that controls the travel of the self-propelled robot 2, an image capture control unit 11c that controls image capture by the self-propelled robot 2, an image analysis unit 11d that analyzes image data from the self-propelled robot 2 received by the transmission/reception control unit 11a, a KPI measurement unit 11e that measures KPIs based on the analysis results by the image analysis unit 11 and sales information from the management server 4 received by the transmission/reception control unit 11a, and a KPI measurement unit 11f that measures the measured KPIs. The self-propelled robot 2 has a camera unit 23, a drive unit 26, and a control unit 21 that controls the camera unit 23 to take pictures and the drive unit 26 to move based on the control of the server device 1, and controls the image data obtained by taking pictures to be sent to the server device 1. The image analysis unit 111d provides a KPI measurement system that analyzes at least one of the following: the customer's visibility rate and viewing location of the evaluation target, the customer's running direction and running speed, the customer's visibility rate and the rate at which the customer stops in front of the evaluation target, and the customer's visibility rate and the rate at which the evaluation target product is picked up. According to this system, the self-propelled robot is remotely controlled to take pictures at a predetermined place and time in the store, and the obtained image data can be analyzed to evaluate the effects of, for example, POP from various angles and measure KPIs, making it possible to objectively evaluate promotional activities.

Secondly, in a KPI measurement method using a server device 1 and a self-propelled robot 2, the server device 1 controls the travel of the self-propelled robot 2 and controls the photographing by the self-propelled robot 2, the self-propelled robot 2 controls the photographing by the camera unit and the travel by the drive unit based on the control by the server device 1, and transmits image data obtained by photographing to the server device 1, the server device 1 analyzes the image data from the self-propelled robot 2, measures KPIs based on the results of the analysis and sales information from the management server 4, and outputs the measured KPIs, and a KPI measurement method is provided in which the image data is analyzed to analyze at least one of the customer's visibility rate and viewing location of the evaluation target, the customer's traveling direction and traveling speed, the customer's visibility rate and stopping rate in front of the evaluation target, and the customer's visibility rate and pick-up rate of the evaluation target product. According to this method, a self-propelled robot can be remotely controlled to take photographs at specific locations and times within the store, and the image data obtained can be analyzed to, for example, evaluate the effectiveness of POP displays from multiple angles and measure KPIs, making it possible to objectively evaluate promotional activities.

The above describes an embodiment of the present invention, but the present invention is not limited to this, and various improvements and modifications are possible without departing from the spirit of the invention.

1...server device, self-propelled robot, 3...POS register system, 4...management server device, 5...communication network, 6...store manager or consultant terminal device, 11...control unit, 11a...transmission/reception control unit, 11b...travel control unit, 11c...photography control unit, 11d...image analysis unit, 11d-1...crowding situation analysis unit, 11d-2...display quantity analysis unit, 11d-3...stopping rate analysis unit, 11d-5...visual recognition analysis unit, 11d-6...walking analysis unit, 11e...image analysis unit, 11f...KPI measurement unit, 11g...generation unit, 11h...output unit, 12...communication unit, 13...memory unit, 14...travel information memory unit, 15...photography information memory unit, 16...analysis result memory unit, 17...KPI memory unit. 21...control unit, 21a...main control unit, 21b...transmission/reception control unit, 21c...position information acquisition unit, 21d...drive control unit, 22...communication unit, 23...imaging unit, 24...operation input unit, 25...storage unit, 26...drive unit, 61...control unit, 61a...main control unit, 61b...transmission/reception control unit, 61c...display control unit, 62...communication unit, 63...display unit, 64...operation input unit, 65...storage unit.

In order to solve the above problems, a KPI measurement system according to one aspect of the present invention is a KPI measurement system including a server device and a self-propelled robot, the server device including a transmission/reception control unit that communicates with the self-propelled robot, a traveling control unit that controls the traveling of the self-propelled robot, an image capture control unit that controls image capture by the self-propelled robot, an image analysis unit that analyzes image data from the self-propelled robot received by the transmission/reception control unit, a KPI measurement unit that measures KPIs based on the analysis results by the image analysis unit and sales information from a management server received by the transmission/reception control unit, and an output unit that outputs the measured KPIs, and the self-propelled robot includes a camera unit, a drive unit, and a and a control unit that controls the shooting by the camera unit and the driving unit based on control by a server device, and controls the image data obtained by shooting to be transmitted to the server device, wherein the image analysis unit analyzes the customer's visibility rate and viewing location of the evaluation target, the customer's driving direction and driving speed, the customer's visibility rate and the rate at which the customer stops in front of the evaluation target, and the customer's visibility rate and the rate at which the evaluation target product is picked up, and the KPI measurement unit calculates the customer's movement direction when entering the survey target area and the movement speed from the distance moved and the time required when entering the survey target area based on the analysis of the image data, analyzes the walking, and determines that there is a tendency for the purchase rate to be higher when the movement speed when entering is constant or becomes faster.

A KPI measurement method according to another aspect of the present invention is a KPI measurement method using a server device and a self-propelled robot, the server device controls the traveling of the self-propelled robot and controls photographing by the self-propelled robot, the self-propelled robot controls photographing by a camera unit and traveling by a drive unit based on the control by the server device, and transmits image data obtained by photographing to the server device, the server device analyzes the image data from the self-propelled robot, and measures KPIs based on the results of the analysis and sales information from a management server, KPIs are output, and the image data is analyzed to analyze the customer's visibility rate and viewing location of the evaluation target, the customer's entry direction and retreat direction and their walking speed, the customer's visibility rate and the rate at which they stop in front of the evaluation target, and the customer's visibility rate and the rate at which they pick up the evaluation target product.The server device recognizes customers by analyzing the image data, calculates the movement speed of each customer from the direction of entry into the survey target area and the distance traveled and time required to enter the survey target area, analyzes the walking, and determines that there is a tendency for the purchase rate to be higher if the movement speed when entering is constant or becomes faster.

Claims (2)

In a KPI measurement system equipped with a server device and a self-propelled robot,
The server device includes:
A transmission/reception control unit that communicates with the self-propelled robot;
A travel control unit that controls the travel of the self-propelled robot;
An imaging control unit that controls imaging by the self-propelled robot;
an image analysis unit that analyzes image data from the self-propelled robot received by the transmission/reception control unit;
A KPI measurement unit that measures a KPI based on the analysis result by the image analysis unit and the sales information from the management server received by the transmission/reception control unit;
An output unit that outputs the measured KPI,
The self-propelled robot comprises:
The camera section and
A drive unit;
a control unit that controls the image capturing by the camera unit and the driving by the drive unit based on the control by the server device, and controls the image data obtained by the image capturing to be transmitted to the server device;
A KPI measurement system in which the image analysis unit analyzes at least one of the customer's visibility rate and viewing location of the evaluation target, the customer's driving direction and driving speed, the customer's visibility rate and stopping rate in front of the evaluation target, and the customer's visibility rate and pick-up rate of the evaluation target product. In a method for measuring KPIs using a server device and a self-propelled robot,
The server device,
Controlling the travel of the self-propelled robot;
Controlling photography by the self-propelled robot;
The self-propelled robot,
Based on the control by the server device, controlling the photographing by the camera unit and the traveling by the drive unit, and transmitting image data obtained by photographing to the server device;
The server device,
Analyzing image data from the self-propelled robot;
Measure KPIs based on the results of the analysis and the sales information from the management server;
Outputting the measured KPIs;
The KPI measurement method includes analyzing at least one of the following in analyzing the image data: the customer's visibility rate and viewing location of the evaluation target, the customer's entry direction and retreat direction and their walking speed, the customer's visibility rate and the rate at which the customer stops in front of the evaluation target, and the customer's visibility rate and the rate at which the customer picks up the evaluation target product.

Images