Information processing device, analysis data output method, and program

Abstract

To provide an information processing device capable of providing information useful for a retail shop, an analysis data output method, and a program.SOLUTION: An information processing device according to an embodiment includes: acquisition means which acquires purchase data being narrowed-down by designated enterprises and commodities from a purchase information storage unit where purchase data in which sold commodities, sales prices of the commodities, stores in which the commodities are sold, enterprises operating the stores, and selling dates on which the commodities are sold are associated with each other is accumulated; setting means which sets a price representative value of the designated commodity for each of the stores on the basis of purchase data by stores obtained by classifying the purchase data acquired by the acquisition means for each of the stores; selection means which selects stores having the same price representative value set by the setting means; generation means which generates analysis data by integrating the purchase data by stores of the store selected by the selection means; and output means which outputs the analysis data generated by the generation means.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an information processing device, an analysis data output method, and a program. [Background technology]

[0002] Retailers aim to increase sales by formulating and implementing sales strategies such as setting sale days. Market information is essential for formulating sales strategies. For example, when setting sale days, retailers research the trends in sales prices of other companies for the products they sell and then decide the sale period, target products, and prices.

[0003] In reality, collecting information on other companies requires a lot of time and effort, as it involves collecting information from in-store POP (Point of Purchase) displays, flyers, etc. Electronic receipt systems that can collect receipt data from multiple companies are known (for example, Patent Document 1), but simply obtaining receipt data does not provide sufficient information for formulating sales strategies.

[0004] Furthermore, obtaining market information is useful not only for retailers, but also for companies that supply products to retailers. For example, market information is useful for formulating sales strategies such as developing new customers. Summary of the Invention [Problem to be solved by the invention]

[0005] The problem to be solved by the present invention is to provide an information processing device, an analysis data output method, and a program that are capable of providing useful information to retail stores and the like. [Means for solving the problem]

[0006] The information processing device of the embodiment retrieves from a purchase information storage unit that accumulates purchase data that associates a sold product, a sales price of the product, a store where the product was sold, a company that operates the store, and a sales date on which the product was sold.Matches the company and product conditions entered into the device An acquisition means for acquiring purchase data, and based on store-specific purchase data obtained by classifying the purchase data acquired by the acquisition means by store, The price with the most sales frequency or the most sales days in the purchase data by store is included in the purchase data by store. Representative product price as A setting means for setting the representative price for each store, a selection means for selecting stores having the same representative price value set by the setting means, and store-specific purchase data for the stores selected by the selection means. Combine by representative price do Purchasing information for specific products at specific companies Analysis Data as A generating means for generating the The aforementioned and an output means for outputting the analysis data. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram showing an outline of the entire system including an analytical data providing system including an analytical data providing device (information processing device) of the embodiment. [Figure 2] FIG. 2 is a diagram illustrating a data configuration of the purchase information storage unit of the electronic receipt server according to the embodiment. [Figure 3] FIG. 3 is a block diagram illustrating a hardware configuration of the analysis data providing device according to the embodiment. [Figure 4] FIG. 4 is a diagram showing the data structure of an analysis data management file stored in the memory unit of the analysis data providing device of the embodiment. [Figure 5] FIG. 5 is a block diagram illustrating the functional configuration of the control unit of the analysis data providing device according to the embodiment. [Figure 6] FIG. 6 is a flowchart showing the flow of an analysis data output process performed by the control unit of the analysis data providing device according to the embodiment. [Figure 7] FIG. 7 is a diagram showing purchase data by store classified by the control unit of the analysis data providing device of the embodiment. [Figure 8] FIG. 8 is a diagram illustrating a method for generating display data generated by the control unit of the analytical data providing device according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of display data generated by the control unit of the analysis data providing device according to the embodiment. [Figure 10] FIG. 10 is a diagram illustrating another example of display data generated by the control unit of the analysis data providing device according to the embodiment. [Figure 11] FIG. 11 is a diagram illustrating another example of display data generated by the control unit of the analysis data providing device according to the embodiment.

[0008] Hereinafter, an information processing device, an analysis data output method, and a program according to embodiments will be described with reference to the drawings. Note that the present invention is not limited to the embodiments described below. For example, in the embodiments described below, an example will be described in which a business operator that manages an electronic receipt server manages the analysis data providing device, but the analysis data providing device may be managed by a business operator different from the business operator that manages the electronic receipt server.

[0009] 1 is a diagram showing an outline of the entire system including an analytical data providing system 1 according to an embodiment. The analytical data providing system 1 includes an electronic receipt server 2 and an analytical data providing device 3. The electronic receipt server 2 and the analytical data providing device 3 are managed by the same business operator and are connected to each other via a network such as a LAN (Local Area Network) so that they can communicate with each other.

[0010] The electronic receipt server 2 is communicably connected to company servers Sa to Sn owned by a plurality of companies Ca to Cn via a network. The network may be a VPN (Virtual Private Network) or the Internet. These companies Ca to Cn are companies that sell products or services (hereinafter collectively referred to as "products"), and in this embodiment, are businesses that operate retail stores such as supermarkets. Each of the companies Ca to Cn is a company that participates in an electronic receipt service that provides electronic receipts to customers.

[0011] Each of the companies Ca to Cn has multiple stores. Each store is equipped with a store server (not shown). The store server is connected to multiple POS (Point Of Sales) terminals (not shown) installed within the store, and acquires receipt data related to transactions from the POS terminals. The company server acquires the receipt data from the store server.

[0012] For example, receipt data from each store of company Ca is sent to company server Sa via the company's internal network. Similarly, receipt data from each store of company Cn is sent to company server Sn via the company's internal network. Receipt data is data that shows the transaction information for one transaction.

[0013] The electronic receipt server 2 includes a purchase information storage unit 21. The purchase information storage unit 21 stores receipt data received from each of the company servers Sa to Sn. The purchase information storage unit 21 stores receipt data for each electronic receipt member who is eligible to receive the electronic receipt service. The purchase information storage unit 21 will be described in detail later.

[0014] The electronic receipt server 2 is connected to an information terminal 4 such as a consumer's smartphone via a network such as the Internet. The consumer's information terminal 4 is an information terminal of an electronic receipt member. The consumer can view the electronic receipt received from the electronic receipt server 2 on his or her own information terminal 4.

[0015] The analytical data providing device 3 is connected to a member terminal 5 via a network such as the Internet. The member terminal 5 is an information terminal managed by a member business (hereinafter also referred to as "user") that can receive the analytical data providing service. The user can receive analytical data from the analytical data providing device 3. The user may be a company participating in the electronic receipt service, i.e., a company that provides receipt data to the electronic receipt server 2, or may be a company that is not participating in the electronic receipt service.

[0016] The analytical data providing device 3 analyzes receipt data (purchase data) managed by the electronic receipt server 2 and provides useful analytical data to users. For example, the analytical data providing device 3 provides analytical data indicating a representative price (reference price) P of a specific company for a specific product and price trends relative to the representative price P. The analytical data providing device 3 is an example of an information processing device.

[0017] By recognizing the sales price trends of the specific company for the specific product, users who receive the analytical data can understand the discount status of the specific company and can use the analytical data as a reference to formulate their own sales strategies. The formulation of sales strategies based on the analytical data, in other words, the method of utilizing the analytical data, is carried out at the discretion of each user. Therefore, even if the analytical data provided is the same, different users may formulate different sales strategies.

[0018] 2 is a diagram showing the data configuration of the purchase information storage unit 21 of the electronic receipt server. The purchase information storage unit 21 manages receipt data received from each of the company servers Sa to Sn. The purchase information storage unit 21 is rewritten each time receipt data is received from each of the company servers Sa to Sn. The receipt data stored in the purchase information storage unit 21 is associated with information indicating the member, receipt number, date, company, store, product, and price.

[0019] The member field stores information that identifies the customer, such as a member code. The member code is the membership code for the electronic receipt service. The receipt number field stores information that identifies the receipt data, such as a receipt number. The receipt number can be said to be information that identifies the transaction.

[0020] The date field stores information indicating the date on which the transaction took place. In other words, the date field stores information indicating the date on which the product was sold. The company field stores information identifying the company that operates the store that sold the product, such as a company code. The store field stores information identifying the store that sold the product, such as a store code.

[0021] The product item stores information identifying the product sold, such as a product code. The registered product code is a code commonly used by each company, such as a JAN (Japanese Article Number) code. The price item stores information indicating the price of the product sold in the transaction, i.e., the selling price. If multiple units of the same product are purchased in one transaction, multiple identical product codes are registered in the product item. Therefore, it can be said that the purchase information storage unit 21 also stores the number of products purchased in one transaction.

[0022] The purchase information storage unit 21 accumulates and stores purchase data that associates the sold product, the sales price of the product, the store where the product was sold, the company that operates the store, and the sales date of the product. Furthermore, receipt data can be said to include purchase data; for example, if multiple products are purchased in one transaction, the receipt data will include multiple purchase data.

[0023] Next, the analytical data providing device 3 will be described in detail. Fig. 3 is a block diagram showing the main hardware configuration of the analytical data providing device 3. The analytical data providing device 3 includes a control unit 30, a memory unit 31, a display unit 32, an operation unit 33, and a communication unit 34. The control unit 30, the memory unit 31, the display unit 32, the operation unit 33, and the communication unit 34 are connected to one another via a bus 35 or the like.

[0024] The control unit 30 is configured as a computer including a CPU (Central Processing Unit) 301, a ROM (Read Only Memory) 302, and a RAM (Random Access Memory) 303. The CPU 301, the ROM 302, and the RAM 303 are connected to each other via a bus 35.

[0025] The CPU 301 controls the overall operation of the analytical data providing device 3. The ROM 302 stores various programs, such as a program used to drive the CPU 301, and various data. The RAM 303 includes an extracted data storage unit 304. The extracted data storage unit 304 stores purchase data acquired from the electronic receipt server 2 during the analytical data output process by the control unit 30, which will be described later. Specifically, the extracted data storage unit 304 stores purchase data (hereinafter also referred to as "extracted data") that has been narrowed down by a specified company, product, and sales period from the purchase information storage unit 21 of the electronic receipt server 2. The RAM 303 is used as a work area for the CPU 301, and loads various programs and data stored in the ROM 302 and the memory unit 31. The control unit 30 executes various control processes of the analytical data providing device 3 by the CPU 301 operating in accordance with the control programs stored in the ROM 302 and the memory unit 31 and loaded in the RAM 303.

[0026] The memory unit 31 is configured with a storage medium such as a hard disk drive (HDD) or flash memory, and maintains its stored contents even when the power is turned off. The memory unit 31 stores a control program 311 and an analysis data management file 312.

[0027] The control program 311 is a control program for executing the analysis data output process described later.

[0028] The analytical data management file 312 is a file that manages analytical data output by the analytical data providing device 3. The analytical data is data related to purchasing information for a specific product at a specific company. The analytical data management file 312 is updated every time the analytical data providing device 3 outputs analytical data. Figure 4 is a diagram showing the data structure of the analytical data management file 312. Each piece of data registered in the analytical data management file 312 is associated with information indicating the number, company, product, and analytical data.

[0029] The No. field is registered with a data number that identifies the analytical data. The Company field is registered with a company code that identifies the target company of the analytical data. The Product field is registered with a product code that identifies the target product of the analytical data. The analytical data field is registered with analytical data related to purchasing information for a specific product at a specific company. In response to a request from the member terminal 5, the analytical data providing device 3 can output the analytical data stored in the analytical data management file 312 to the member terminal 5 as appropriate. Alternatively, the analytical data providing device 3 can display the analytical data stored in the analytical data management file 312 on the display unit 32 as appropriate.

[0030] Returning to FIG. 3, the hardware configuration of the analytical data providing device 3 will be described.

[0031] The display unit 32 is configured with, for example, a liquid crystal panel and displays various information. The display unit 32 displays, for example, analysis data stored in the analysis data management file 312. The display unit 32 also displays an input screen for inputting conditions (hereinafter also referred to as "extraction conditions") for narrowing down the purchase data in the purchase information storage unit 21 of the electronic receipt server 2.

[0032] The operation unit 33 is used to input information to the control unit 30, and is composed of a keyboard, a touch panel, a mouse, etc. The operation unit 33 is used to input extraction conditions for purchase data in the purchase information storage unit 21, for example.

[0033] The communication unit 34 is an interface for communicating with external devices such as the electronic receipt server 2 and the user's member terminal 5. By connecting to the external devices via the communication unit 34, the control unit 30 can send and receive information (data) with the external devices.

[0034] Next, a description will be given of the functional configuration of the analytical data providing device 3. Fig. 5 is a block diagram showing an example of the main functional configuration of the analytical data providing device 3. The control unit 30 functions as an input means 3001, an acquisition means 3002, a setting means 3003, a selection means 3004, a generation means 3005, and an output means 3006, as a result of the CPU 301 operating in accordance with a control program 311 stored in the ROM 302 or memory unit 31. Note that each of these functions may be configured using hardware such as a dedicated circuit.

[0035] Various information is input to the input means 3001 based on the operation of the operation unit 33. For example, extraction conditions for purchase data in the purchase information storage unit 21 of the electronic receipt server 2 are input to the input means 3001. The extraction conditions include a designated company (hereinafter also referred to as a "designated company") and a designated product (hereinafter also referred to as a "designated product"). In this embodiment, a designated sales date period (hereinafter also referred to as a "designated period") is also an extraction condition.

[0036] Therefore, information specifying the company code of the designated company, the product code of the designated product, and the designated period is input as extraction conditions to the input means 3001. Note that extraction conditions received from the member terminal 5 may also be input to the input means 3001.

[0037] The acquiring means 3002 acquires purchasing data narrowed down by a specified company and a specified product from the purchasing information storage unit 21, which stores purchasing data that associates a sold product, the selling price of the product, the store where the product was sold, the company that operates the store, and the sales date of the product. In this embodiment, the acquiring means 3002 acquires purchasing data further narrowed down by a specified period.

[0038] Specifically, acquisition means 3002 acquires, from the purchase data stored in purchase information storage unit 21, purchase data that matches the extraction conditions input to input means 3001. More specifically, acquisition means 3002 acquires, as extracted data, from purchase information storage unit 21, purchase data related to stores operated by a designated company identified by the company code input to input means 3001, purchase data related to designated products identified by the product codes input to input means 3001, and purchase data related to a designated period identified by information indicating the period input to input means 3001. The extracted data acquired by acquisition means 3002 is stored in extracted data storage unit 304.

[0039] In this embodiment, the acquiring unit 3002 acquires the extracted data from the electronic receipt server 2 that manages receipt information, but this is not limited to this. For example, the extracted data may be acquired from a device that has a storage unit that stores purchase data separately from receipt information. Alternatively, the purchase data may be stored in the memory unit 31 of the analysis data providing device 3, and the acquiring unit 3002 may acquire the extracted data from the memory unit 31.

[0040] The setting means 3003 sets a representative price P of the specified product for each store based on the store-specific purchase data obtained by classifying the purchase data acquired by the acquisition means 3002 by store code. Specifically, the setting means 3003 generates store-specific purchase data by classifying the extracted data acquired by the acquisition means 3002 by store code. The setting means 3003 then sets a representative price P of the specified product in the store-specific purchase data.

[0041] The representative price value P can be considered the base price of the designated product at each store, and in this embodiment, it is the price of the designated product that has been sold the most frequently in the purchase data by store. In other words, the representative price value P is the price at which the most units have been sold among the sales prices of the designated product. Note that the representative price value P can also be the price of the designated product that has been on sale for the most number of days in the purchase data by store. The representative price value P can be set arbitrarily by the business operator that manages the analysis data provision device 3 and provides the analysis data provision service, or by the user of the analysis data provision service.

[0042] The selection means 3004 selects stores that have the same representative price value P set by the setting means 3003. In other words, the selection means 3004 classifies the store-specific purchase data generated by the setting means 3003 by the set representative price value P.

[0043] The generating means 3005 generates analytical data by integrating the store-specific purchase data of the stores selected by the selecting means 3004. Specifically, the generating means 3005 generates analytical data by integrating the store-specific purchase data of stores having the same representative price value P.

[0044] Furthermore, the generating means 3005 generates display data by visualizing the analytical data, such as by graphing it. For example, the generating means 3005 processes analytical data that integrates store-specific purchase data from stores with the same representative price value P, and generates display data in the form of a graph showing daily price trends for designated products. The analytical data can be processed, or in other words, displayed in any way, and display data that is suitable for examining the content of the analytical data can be used. The generated display data is also an example of analytical data.

[0045] Generally, product prices often differ between regions, companies, and stores, and simply looking at the overall purchasing data makes it difficult to determine which price in the market is the base price (normal selling price) and which price is the discounted price.Even if you look at purchasing data narrowed down to a specific company, product pricing often differs between regions and stores, so it is similarly difficult to determine which price is the base price and which price is the discounted price.

[0046] On the other hand, attempts have been made to understand the trends in product sales prices at a single store by focusing only on the purchase data of that store, but there are days when a specific product is not purchased with the purchase data of a single store, and sufficient purchase data cannot be obtained. As a result, it is difficult to determine which price is the base price and which price is the discounted price. This makes it difficult to understand how other companies set sale days and sale prices.

[0047] In contrast, the analytical data providing device 3 of this embodiment sets a representative price value P as a base price for each store for purchase data related to a specific product of a specific company, and generates analytical data by integrating store-specific purchase data for stores with the same representative price value P. In other words, the analytical data is generated by grouping the purchase data of a specified company by base price. Because the purchase data grouped by base price is an integration of multiple store-specific data, a sufficient amount of data can be secured.

[0048] Therefore, the generated analysis data allows accurate understanding of price trends for designated products of designated companies relative to each base price, making it possible to understand, for each base price, when and how much a designated company is discounting designated products.

[0049] The output means 3006 outputs the analysis data generated by the generation means 3005. For example, the output means 3006 outputs the display data generated by the generation means 3005 to the display unit 32. The display unit 32 can display the display data. The output means 3006 also outputs the display data generated by the generation means 3005 to the member terminal 5. The output means 3006 may output the display data to a separately provided web server. In this case, the output means 3006 transmits to the member terminal 5 the URL (Uniform Resource Locator) of the web page where the display data is published. The member terminal 5, which is equipped with a web browser, can download the display data published on the web and view it in the web browser by specifying the received URL.

[0050] Furthermore, the output means 3006 outputs the extraction conditions for the purchase data in the purchase information storage unit 21, which are input to the input means 3001, to the electronic receipt server 2. Specifically, the output means 3006 outputs the company code of the designated company, the product code of the designated product, and information for specifying the sales date period, which are input to the input means 3001, to the electronic receipt server 2.

[0051] Next, we will explain the analysis data output process executed by the analysis data providing device 3 configured as described above. Figure 6 is a flowchart showing the flow of the analysis data output process by the control unit 30 of the analysis data providing device 3. It can be said that the flowchart shown in Figure 6 shows the flow of the analysis data output method executed by the analysis data providing device 3.

[0052] The control unit 30 determines whether extraction conditions have been input to the input means 3001 (step S1), and if not, returns to the processing of step S1 and waits. When extraction conditions have been input (Y in step S1), the output means 3006 outputs the input extraction conditions to the electronic receipt server 2 (step S2).

[0053] The extraction conditions are a designated company, a designated product, and a designated period. Therefore, the output unit 3006 outputs information indicating the company code of the designated company, the product code of the designated product, and the designated period to the electronic receipt server 2.

[0054] The electronic receipt server 2 receives the extraction conditions output by the output means 3006. Then, the electronic receipt server 2 narrows down the purchase data in the purchase information storage unit 21 based on the received extraction conditions, and extracts extracted data that matches the extraction conditions. The electronic receipt server 2 outputs the extracted data to the analysis data providing device 3.

[0055] The acquiring unit 3002 acquires the purchase data, which is the extracted data output by the electronic receipt server 2 (step S3). Note that the purchasing information storage unit 21 may be provided in a server device different from the memory unit 31 or the electronic receipt server 2, and the acquiring unit 3002 may acquire the extracted data from the purchasing information storage unit 21.

[0056] Next, the setting means 3003 generates purchase data by store (step S4). Specifically, the setting means 3003 classifies the extracted data acquired by the acquisition means 3002 using the store code as a key, and generates a plurality of purchase data by store.

[0057] Figure 7 is a graph of store-specific purchase data. The store-specific purchase data shown in Figure 7 is purchase data related to store "C" among the purchase data extracted from the purchase information storage unit 21 using the extraction conditions of designated product "A," designated company "B," and designated period "August 1st to October 31st." In Figure 7, the vertical axis represents price, the horizontal axis represents date, and the plotted points represent the sales price on the corresponding date. The setting means 3003 generates store-specific purchase data for the number of store codes included in the extracted data.

[0058] Furthermore, the setting means 3003 sets a representative price value P of the designated product at each store from the store-specific purchase data for each store (step S5). In this embodiment, the price of the designated product that has been sold the most frequently in the store-specific purchase data is set as the representative price value P. In the above store-specific purchase data, the price at which product A has been sold the most frequently is 160 yen, and the setting means 3003 sets the representative price value P to 160 yen. Note that FIG. 7 does not show the number of times product A has been sold (number of units sold), and therefore does not indicate that the price at which product A has been sold the most frequently is 160 yen. On the other hand, in the above store-specific data, if the representative price value P is set to the price at which product A has been sold the most number of days, the price with the most plots in FIG. 7 becomes the representative price value P. In this case, as is clear from FIG. 7, the representative price value P will also be 160 yen.

[0059] Returning to the explanation of the flowchart in Figure 6, after the setting means 3003 sets the representative price value P for each store-specific purchase data, the selection means 3004 selects stores with the same representative price value P (step S6). In other words, the selection means 3004 classifies multiple store-specific purchase data into groups with the same representative price value P.

[0060] The generating unit 3005 then combines the store-specific purchase data for the selected stores (step S7). In other words, the generating unit 3005 combines the store-specific purchase data classified into the same group to generate analysis data. The generating unit 3005 then generates display data based on the analysis data (step S8).

[0061] Fig. 8 is a diagram showing a method for generating analytical data. As shown in Fig. 8, the generating means 3005 combines the store-specific purchase data of multiple stores (44 in this example) such as store C, store D, etc., where the representative price value P is 160 yen. The generating means 3005 then generates analytical data and generates display data that is graphed, for example, as shown in Fig. 8.

[0062] Next, the output means 3006 outputs the display data generated by the generation means 3005 (step S9). The output destination to which the output means 3006 outputs the display data can be set arbitrarily, and the display can be output to the display unit 32, the member terminal 5, or the like. Furthermore, the output means 3006 does not necessarily have to output the display data generated by the generation means 3005. For example, the display data shown in FIG. 8 may be generated by the member terminal 5 that has received the analysis data.

[0063] Then, when the output means 3006 has finished outputting the display data, the control unit 30 ends the analysis data output process.

[0064] 9 to 11 show examples of the generated display data. The analysis data shown in Fig. 9 is purchase data from multiple stores of company "X" in which the representative price P of product "AA" for the period "8 / 1 to 10 / 31" is "170 yen."

[0065] A user provided with the analysis data shown in Figure 9 can understand the price trends at Company X's stores, where the representative price of Product AA is 170 yen. The user can understand that Company X's stores discount Product AA approximately once a week, with the discount rate being around 10% or 20%.

[0066] If the user is a competitor of Company X, the user can formulate a sales strategy to increase sales based on the analysis data. For example, the user can create a plan to sell Product AA at a discount on a day other than the day on which Company X's store is expected to sell Product AA at a discount. In addition, the user can create a plan to sell Product AA at a discount at a price lower than the price at Company X's store on the day on which Company X's store is expected to sell Product AA at a discount.

[0067] The analysis data shown in Fig. 10 is purchase data from multiple stores of company "Y" for which the representative price P for product "BB" during the period "8 / 1 to 10 / 31" is "75 yen." In this embodiment, as described above, the representative price P is set to the price at which the product is sold the most frequently, so the representative price P for product BB is 75 yen, not 98 yen, which has the most plots in the graph in Fig. 10.

[0068] A user provided with the analysis data shown in Figure 10 can understand that Company Y's store periodically and repeatedly sells Product BB at a discount. Specifically, the user can understand that Company Y's store sells Product BB for 98 yen for roughly five days out of a week, and for 75 yen for the remaining two days. From this, the user can infer that Company Y's store purchases Product BB once a week and sells it at a discount as the expiration date approaches, and that Product BB sells well during the discount sale.

[0069] If the user is a manufacturer of Product BB, the user can make proposals to customers to acquire new customers based on the analysis data. For example, the user can propose to Company Y that they reduce the number of Product BB purchased at one time to purchase twice a week, thereby reducing the number of items sold at a discount.

[0070] The analysis data shown in FIG. 11 is purchase data from multiple stores of a company "Z" in which the representative price P of a product "CC" during the period "8 / 1 to 10 / 31" is "98 yen."

[0071] A user who receives the analysis data shown in FIG. 11 can understand that Company Z's stores are selling Product CC at discounts during a particular period.

[0072] If the user is a competitor of Company Z, the user can formulate a sales strategy to attract customers based on the analysis data. For example, the user can plan to offer discount sales of products similar to Product CC on the day that Company Z's store is expected to offer discount sales of Product CC.

[0073] The above-described method of utilizing the analytical data is merely an example, and the user can utilize the analytical data provided by the analytical data providing device in any way.

[0074] As described above, the analytical data providing device 3 of this embodiment comprises an acquisition means 3002 that acquires purchasing data narrowed down by a specified company and product from a purchasing information memory unit 21 that accumulates purchasing data correlating the sold product, the selling price of the product, the store where the product was sold, the company operating the store, and the sales date on which the product was sold; a setting means 3003 that sets a representative price value P of the specified product for each store based on store-specific purchasing data in which the purchasing data acquired by the acquisition means 3002 is classified by store; a selection means 3004 that selects stores having the same representative price value P set by the setting means 3003; a generation means 3005 that integrates the store-specific purchasing data of the stores selected by the selection means 3004 to generate analytical data; and an output means 3006 that outputs the analytical data generated by the generation means 3005.

[0075] This allows the analytical data providing device 3 to use the purchase data to set a sales reference value for a product and generate analytical data showing price trends relative to the set sales reference value. As a result, the analytical data providing device 3 can provide users with useful information that is useful for formulating sales strategies, etc.

[0076] Furthermore, the generating means 3005 of the analytical data providing device 3 of this embodiment can generate display data showing daily price trends.

[0077] This allows the analytical data providing device 3 to make price trends easier to see, thereby providing more useful information to the user.

[0078] Although the embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention.

[0079] In the above embodiment, the control programs executed by the analytical data providing device 3 and the member terminal 5 may be configured to be recorded on a computer-readable recording medium such as a CD-ROM and provided. Also, the control programs executed by the analytical data providing device 3 and the member terminal 5 may be configured to be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network, or may even be configured to be provided via a network such as the Internet. [Explanation of symbols]

[0080] 3. Analysis data providing device (information processing device) 21 Purchasing information storage section 3002 Acquisition method 3003 Setting method 3004 Selection method 3005 Generation means 3006 Output means

[0081] [Patent Document 1] Japanese Patent Application Publication No. 2020-191127

Claims

1. an acquisition means for acquiring purchase data that matches the conditions of the company and product input to the device from a purchase information storage unit that stores purchase data that associates the sold product, the sales price of the product, the store where the product was sold, the company that operates the store, and the sales date on which the product was sold; a setting means for setting, for each store, the price with the highest number of sales or the price with the highest number of sales days in the store-specific purchase data based on the store-specific purchase data obtained by classifying the purchase data acquired by the acquisition means by store, as a representative price value for the product included in the store-specific purchase data; a selection means for selecting stores having the same representative price value set by the setting means; a generating means for combining the store-specific purchase data of the stores selected by the selecting means for each representative price value and generating analysis data relating to purchase information of a specific product at a specific company; an output means for outputting the analysis data generated by the generation means; An information processing device comprising:

2. The representative price is the price at which sales have been most frequently made in the purchase data by store. The information processing device according to claim 1 .

3. The purchase data is data associated with the sale date of the product, The representative price is the price at which the number of days sold is the greatest in the purchase data by store. The information processing device according to claim 1 .

4. the generating means generates display data that visualizes daily price trends of the products included in the purchase data by store based on the analysis data.

4. The information processing device according to claim 1.

5. An analysis data output method executed by an information processing device, comprising: an acquisition step of acquiring purchase data that matches the company and product conditions input to the device from a purchase information storage unit that stores purchase data that associates the sold product, the sales price of the product, the store where the product was sold, the company that operates the store, and the sales date on which the product was sold; a setting step of setting, for each store, the price with the highest number of sales or the price with the highest number of sales days in the store-specific purchase data based on the store-specific purchase data obtained by classifying the purchase data acquired in the acquisition step by store, as a representative price value for the product included in the store-specific purchase data; a selection step of selecting stores having the same representative price value set in the setting step; a generating step of combining the store-specific purchase data of the stores selected in the selecting step for each representative price value to generate analysis data relating to purchase information of a specific product at a specific company; an output step of outputting the analysis data generated in the generation step; An analytical data output method including:

6. A program for controlling an information processing device by a computer, The computer an acquisition means for acquiring purchase data that matches the conditions of the company and product input to the device from a purchase information storage unit that stores purchase data that associates the sold product, the sales price of the product, the store where the product was sold, the company that operates the store, and the sales date on which the product was sold; a setting means for setting, for each store, the price with the highest number of sales or the price with the highest number of sales days in the store-specific purchase data based on the store-specific purchase data obtained by classifying the purchase data acquired by the acquisition means by store, as a representative price value for the product included in the store-specific purchase data; a selection means for selecting stores having the same representative price value set by the setting means; a generating means for combining the store-specific purchase data of the stores selected by the selecting means for each representative price value and generating analysis data relating to purchase information of a specific product at a specific company; an output means for outputting the analysis data generated by the generation means; A program that makes it work.

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