JP2009265747A - Marketing support system, marketing support method, marketing support program, and computer readable medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a marketing support system, a marketing support method, a marketing support program, and a computer readable medium can provide a more precise recommended number of order placements, and utilizing the recommended number of order placements usefully and easily. <P>SOLUTION: The system includes questionnaire acquisition means, in-store information acquisition means, a data warehouse, recommended number of order placement forecasting means, and order placement management means. The recommended number of order placement forecasting means generates a demand forecast value based on the in-store information obtained from the data warehouse, generates a corrected forecast value based on the questionnaire response information obtained from the questionnaire acquisition means, and generates a recommended number of order placements using at least the demand forecast value and the corrected forecast value. The order placement management means is configured to execute an order placement instruction from a POS system based on the recommended number of order placements. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a marketing support system, a marketing support method, a marketing support program, and a computer-readable medium that generate a recommended order quantity for a target product based on information acquired from a plurality of member terminals and a customer's POS system.

  Conventional marketing support systems generally know the technology to determine the appropriate order quantity of products using various government databases and data obtained from private databases (holidays, weather, marketing calendar, etc.). It has been.

Patent Document 1 below discloses a POS automatic ordering system that predicts a more accurate expected sales volume and automatically orders products by using the predicted weather, precipitation probability, and past performance data. ing.
Japanese Patent Application Laid-Open No. 08-329351

  However, the invention described in Patent Document 1 merely predicts the sales forecast amount based on past performance data (monthly sales results by product / month according to past products) and the expected weather and precipitation probability. Therefore, it has been desired to develop a system capable of predicting the sales forecast with higher accuracy.

  In addition, it has been desired to develop a system that allows customers to effectively use the predicted sales forecast amount.

  As described above, an object of the present invention is to provide a marketing support system, a marketing support method, a marketing support program, and a computer-readable medium that are beneficial to customers (users).

  It is another object of the present invention to provide a marketing support system, a marketing support method, a marketing support program, and a computer-readable medium that provide a highly accurate recommended order quantity for a product sold by a customer.

  Further, the present invention makes it possible to automatically perform an ordering work based on the recommended ordering number or to provide an ordering work via an authentication work to the customer when providing the recommended ordering number to the customer. It is an object to provide a marketing support system, a marketing support method, a marketing support program, and a computer-readable medium.

  A first invention of the present application made to solve the above-mentioned problems is a marketing support system configured to be capable of transmitting and receiving information via a network with a plurality of member terminals and a customer POS system, wherein the member terminal Questionnaire acquisition means for acquiring questionnaire response information regarding the target product from the store, in-store information acquisition means for collecting in-store information regarding the target product from the POS system, target attributes associated with each target product, in-store information, And a data warehouse for storing at least questionnaire answer information and corusal information, a recommended order quantity predicting means for generating a recommended order quantity of the target product from the in-store information, the questionnaire answer information, and the monkey information, and the customer's POS An order manager who can execute the recommended order quantity authentication and order command from the system The questionnaire acquisition means notifies the member terminal that matches the target attribute of the target product of a response to the questionnaire, and receives the questionnaire response information classified into the purchaser and the non-purchaser of the target product. The recommended order quantity predicting means generates a demand forecast value based on in-store information for each target product acquired from the data warehouse and the corusal information. A forecast correction value generating unit that generates a forecast correction value from the questionnaire response information for each target product acquired from the data warehouse; a forecast correction value generation unit; and the demand forecast value and the forecast correction value for each target product. The gist of the present invention is a marketing support system including a recommended order quantity generation unit that generates a recommended order quantity.

  Further, in the second invention of the present application, the prediction correction value generation unit generates a first correction value based on a questionnaire result of a purchaser and a second correction value based on a questionnaire result of a non-buyer from the questionnaire response information. Then, the gist is the marketing support system according to the first invention of the present application, wherein a value obtained by integrating the first correction value and the second correction value is generated as a prediction correction value.

  The third invention of the present application is a marketing support method of a marketing support system configured to be capable of transmitting and receiving information via a network with a plurality of member terminals and customer POS systems, wherein the marketing support system includes the member Questionnaire acquisition means for acquiring questionnaire response information about the target product from the terminal, in-store information acquisition means for collecting in-store information about the target product from the vPOS system, target attributes, in-store information associated with each target product, And a data warehouse for storing at least questionnaire answer information and corusal information, a recommended order quantity predicting means for generating a recommended order quantity of the target product from the in-store information, the questionnaire answer information, and the monkey information, and the customer's POS Certification and ordering of the recommended number of orders from the system Order management means capable of executing an order, and a questionnaire response request is notified from the questionnaire acquisition means to a member terminal that matches the target attribute of the target product, and the buyer and non-purchaser of the target product Acquiring the questionnaire result classified into the data warehouse and storing it in the data warehouse; acquiring the in-store information on the target product from the in-store information acquisition means to the customer's POS system; and the recommended ordering The number prediction means generates in-store information for each target product acquired from the data warehouse and the demand prediction value based on the corusal information, and predicts from the questionnaire response information for each target product acquired from the data warehouse. Generating a correction value and generating a recommended order quantity for each target product from the demand prediction value and the prediction correction value. Characterized in that, the gist that the marketing support method.

  According to a fourth aspect of the present invention, at least one information processing device configured to be able to transmit and receive information to and from a plurality of member terminals and customer POS systems, stores in-store information for each target product, A process of generating a demand forecast value based on information, a process of generating a forecast correction value from questionnaire response information for each target product, and a process of generating a recommended order number from the demand forecast value and the forecast correction value The gist is that it is a program for execution.

  The fifth invention of the present application is a computer-readable medium in which at least the program according to the fourth invention of the present application is recorded.

According to the marketing support system, the marketing support method, the marketing support program, and the computer-readable medium of the present invention, at least one of the following effects can be obtained.
(1) By generating a prediction correction value using a questionnaire result, it is possible to generate a recommended order quantity with higher accuracy.
(2) By classifying the questionnaire results for each purchaser and non-purchaser of the target product and generating a prediction correction value, it is possible to generate a recommended order quantity with higher accuracy.
(3) Ordering work based on the generated recommended number of orders can be easily performed from the POS system.
(4) The order quantity can be adjusted while referring to the recommended order quantity from the POS system, and the ordering work can be easily performed with the adjusted order quantity.

  Details of the embodiments of the present invention will be described below.

FIG. 1 is a schematic diagram illustrating a configuration example of a marketing support system according to the first embodiment of the present invention.
The marketing support system of this embodiment includes at least a questionnaire acquisition unit 1, an in-store information acquisition unit 2, a data warehouse 3, and a recommended order quantity prediction unit 4, and includes a plurality of member terminals 7 and customer POSs. Information is transmitted and received between the system 8 and the network 6.

  Each of the above devices is configured by means that can be executed by software, hardware, or a combination thereof. As the hardware, a general information processing device (computer) can be used. The information processing device includes a CPU (arithmetic processing device), a data transmission / reception interface, a storage device such as an HDD and a flash memory, a keyboard, An input device such as a mouse and an output device such as a display and a printer are optionally provided.

  The network 6 is an information communication network including an ISDN line, a CATV line, an optical cable line, a wireless line, and the like, and is configured to be able to transmit and receive information using protocols such as TCP / IP, FTP, and HTTP. For example, the Internet, LAN, VLAN Or other networks or combinations thereof.

  The member terminal 7 is a terminal used by a member of a WEB questionnaire managed and operated by the system provider of the present invention, and a general personal computer, a mobile phone, a PDA, or the like is used. The member terminal 7 includes a WEB browser, and is configured to be connectable to the questionnaire acquisition unit 1 using the WEB browser.

  The POS system 8 is a POS system used by a customer provided with the marketing support system of the present invention, and stores a POS terminal provided in each store, a POS server that manages and controls each client terminal, and various information. This is a general POS system configured by a database.

Next, each device provided in the present invention will be described.
(1) Questionnaire acquisition means 1
The questionnaire acquisition means 1 is a means having a mail transmission function and a function of displaying a questionnaire response page in response to access from the member terminal to the member terminal 7, and has at least a WEB server function and a mail server function. This is a general server device including the above.
The questionnaire acquisition means 1 has a storage device such as a hard disk or a flash memory, and in the storage device, a database is constructed for storing the contents of a question when conducting a questionnaire to the member terminal 7 and answer information of the questionnaire. Yes.

(2) In-store information acquisition means 2
The in-store information acquisition unit 2 is a unit that can connect to the POS system 8 and execute a function of collecting in-store information regarding the target product, and is configured by software, hardware, or a combination thereof.
The collection of in-store information is performed based on a command from an information processing terminal (not shown) used by a system administrator or a preset schedule (daily, weekly, monthly, etc.) Done. The in-store information mainly includes the number of stocks for each product, sales results, disposal results, ordering / purchasing results, safety stock numbers, and the like.

(3) Data warehouse 3
The data warehouse 3 is a database group that stores at least the questionnaire response information transmitted from the questionnaire acquisition unit 1 and the in-store information transmitted from the in-store information acquisition unit 2.
Various other information is optionally stored in the data warehouse 3. The various types of information include target information for each target product, weather / temperature information, sales promotion information, regional events, presence / absence of standard items, and other information including other information.

(4) Recommended order quantity prediction means 4
The recommended order quantity predicting means 4 is a means capable of executing a function for generating a recommended order quantity for each product from the information stored in the data warehouse 3, and is configured by software, hardware or a combination thereof. The
The recommended order quantity predicting means 4 is further described for each functional block. At least a demand forecast value generation unit 41, a prediction correction value generation unit 42, and a recommended order quantity generation unit 43 are provided. Details of each part will be described below.

(4-1) Demand forecast value generation unit 41
The demand prediction value generation unit 41 generates a demand prediction value, which is the number of sales predictions for each target product, from the in-store information acquired from the data warehouse 3 and the causal information using a prediction model formula provided in advance. It has the function to do.
FIG. 2 shows an example of a model formula used for generating the demand forecast value.
The prediction model formula is obtained by calculating a demand influence coefficient in units of month, day, weather, temperature, special event (regional event or other event), and adding a constant term to the coefficient.

(4-2) Prediction correction value generation unit 42
The prediction correction value generation unit 42 has a function of generating a prediction correction value based on the questionnaire response information acquired from the data warehouse 3.
The prediction correction value is generated based on the first correction value generated using the purchaser information and the second correction value generated using the non-purchaser information among the questionnaire response information. For example, A value obtained by integrating the first correction value and the second correction value can be used as the predicted correction value.

The calculation of the first correction value and the second correction value is based on the difference (hereinafter referred to as “sales error”) between the previous recommended order quantity obtained from the in-store information and the actual sales (actual sales), and questionnaire response information. This shall be done by analyzing the relationship with (including buyers and non-purchasers). The analysis can be performed by multiple regression analysis or discriminant analysis, or an analysis method that is optimal depending on the genre of the target product.
As an example of a multiple regression analysis or discriminant analysis method, analysis is performed with the sales error as an objective variable and questionnaire response information as an explanatory variable.
In the case of multiple regression analysis, “standard variation regression coefficient”, in the case of discriminant analysis, “discriminant coefficient”, and in the case of other analysis methods, the calculated influence coefficient is used as the prediction correction value.

[Example of model expression of first correction value and second correction value]
FIG. 3 shows an example of a prediction model formula used for generating the first correction value and the second correction value.
The first correction value uses the buyer information obtained from the questionnaire response information, the individual coefficient based on the percentage of those who intend to purchase again, and the percentage of members who have purchased more than a certain number of times (hereinafter referred to as “stable buyer percentage”). The individual coefficient based on the above is calculated by the above analysis method, and the coefficient is integrated.

  The second correction value is based on the non-purchaser information obtained from the questionnaire response information, and is based on the ratio of non-purchasers who intend to purchase in the future (hereinafter referred to as “percentage of new purchasers”). The coefficient is calculated by the above analysis method, and the coefficient is set as the second correction value.

(4-3) Recommended Order Number Generation Unit 43
The recommended order quantity generation unit 43 has a function of generating a recommended order quantity for each product using the generated demand forecast value and forecast correction value, the safety stock quantity obtained from the in-store information, and the inventory quantity at the time of ordering. Have.
FIG. 4 shows an example of a model formula used for generating the recommended order quantity.
The recommended order quantity is generated by adding the safety stock quantity to the demand forecast quantity multiplied by the prediction correction value and subtracting the order quantity at the time of ordering.

(5) Order management means 5
The order management means 5 is configured by a device that can execute the WEB server function by software, hardware, or a combination thereof.
The order management means 5 includes a database for storing the recommended order quantity for each target product transmitted from the recommended order quantity generation unit 43, and a terminal in the POS system 8 (hereinafter referred to as “POS terminal”). It has a function capable of executing authentication of the recommended order quantity and order instruction from a WEB browser provided.

  In the above embodiment, it is assumed that each of the above units is configured by an independent information processing apparatus, but is not limited to the present embodiment. It is good also as a structure programmed so that a processing apparatus could be performed as said each means.

Next, each step of the marketing support method of the present invention will be described.
The main flow of the marketing support method of the present invention is as follows.
(1) Questionnaire response processing The questionnaire response information acquired by the questionnaire acquisition means 1 is stored in the data warehouse 3.
(2) Recommended Order Number Generation Processing The recommended order number is generated in the questionnaire response information, the in-store information acquired from the POS system 8, and the corus information stored in the data warehouse 3.
When the recommended order quantity is generated for the first time for a specific target product, the questionnaire results have not yet been aggregated, so the demand forecast value generated based on the corus information and in-store information is used as is. Generate as
The generation process of the recommended order quantity for the second and subsequent times includes the forecast correction value obtained by analyzing the aggregated questionnaire results and in-store information (difference between the recommended order quantity for the first time and the actual sales performance), and the demand Generated based on the predicted value.
(3) Order processing The recommended order quantity is configured to be viewable from the POS terminal, and the order process is performed with the recommended order quantity or the newly entered order quantity from the POS terminal.
(4) In-store information update processing New in-store information (number of items in stock, sales record, disposal record, ordering / purchase record, number of safety stock, etc.) from the POS system 8 is obtained, and data warehouse 3 update in-store information.
Providing a marketing support method that allows the user of the POS system 8 to easily execute order processing by repeating the above (1) to (4) to generate a highly accurate recommended order quantity. It is.

In the following, each process relating to generation of the recommended order number for the second and subsequent times and order processing after placing the demand forecast value as the recommended order number will be described.
The data warehouse 3 in the system of the present invention stores in-store information including the sales results after provision of the recommended number of orders for the first time, target attributes for each target product, and corusal information in advance. This will be explained as a premise.

(1) Questionnaire answer processing (s100 to s180)
[Notification of questionnaire response request]
FIG. 5 shows a schematic diagram of questionnaire response processing among the member terminal 7, the questionnaire acquisition means 1, and the data warehouse 3.
First, in order to increase the accuracy of the questionnaire response content, the member acquisition terminal 1 is identified and extracted to some extent on the questionnaire acquisition means 1 (s100).
The identification / extraction of the member terminal 7 is a target for conducting the questionnaire from the storage device provided in the questionnaire acquisition means 1 or the member information (gender, age, etc.) stored in advance in the data warehouse 3 and the target attribute. This is done by extracting members that match the target attribute of the product.
Next, the questionnaire acquisition means 1 is a questionnaire execution command input from an information processing terminal (not shown) used by the system administrator or a questionnaire execution schedule (recorded and set in the storage device in advance). Based on the daily, weekly, monthly, etc.), the member terminal 7 is notified of a questionnaire response request for the target product registered in the data warehouse 3 (s110).
The response request notification is made by an e-mail with content that prompts an answer to a questionnaire by accessing a predetermined questionnaire response page provided on the WEB server in the questionnaire acquisition means 1. The e-mail may have a URL linked to the questionnaire response page.
The contents of the questionnaire are: product recognition rate, product review rate, product purchase rate, number of purchases, future purchase intention, intention to continue purchasing, store recognition rate, store visit frequency, store visit rate, product purchase rate at target store, target store It is composed of questions that can extract parameters such as future merchandise purchase intention, MD evaluation, and revisit intention.

[Questionnaire response processing]
The questionnaire acquisition means 1 accessed from the member terminal 7 that has received the questionnaire notification request to the questionnaire acquisition means 1 on the WEB browser displays a questionnaire response page on the display screen of the member terminal 7 (s120, s130, s140).
FIG. 6 shows an image of the questionnaire response page.
As a method of answering the questionnaire, it is assumed that the response is made in a well-known answer format such as a method of checking a check box provided on the answer page from the WEB browser of the member terminal 7.
When the questionnaire acquisition means 1 receives the answer information of the questionnaire input / transmitted by the member terminal 7, the contents of the answer are recorded in the own database as questionnaire answer information (s150, s160, s170).
Thereafter, the questionnaire acquisition means 1 stores the questionnaire response information accumulated in its own database in the data warehouse 3 (s180).

(2) Recommended order quantity generation processing (s200 to s240)
[Reception of in-store information and questionnaire response information]
FIG. 7 shows a schematic diagram of recommended order quantity generation processing among the data warehouse 3, the recommended order quantity predicting means 4, and the order management means 5. FIG. 8 shows a detailed process flow diagram of recommended order quantity generation.
The recommended order quantity predicting means 4 accesses the data warehouse 3 in accordance with a command from the administrator terminal of this system or a preset schedule (daily, weekly, monthly, etc.) and stores in-store information (product Inventory quantity, sales record, disposal record, order / purchase record, etc.) and questionnaire information are received (s200, s210, s220).

[Generation of demand forecast values]
FIG. 8 is a detailed process flow diagram for generating the recommended order quantity. Based on the in-store information and the corusal information, a predicted demand value that is the number of predicted sales for each target product is generated using a prediction model formula (s231).

[Prediction correction value generation / update]
When the received questionnaire result is the first time, the prediction correction value has not been generated yet. Therefore, the case is classified according to whether or not the received questionnaire result is the first time (s232), and if it is the first time, the recommended order number (= demand forecast value) generated first and the in-store information A prediction correction value is generated based on the difference in sales results and the questionnaire result. (S234)
From the second time on, the same procedure as described above is performed to sequentially update the prediction correction value. (S233)

[Generate recommended order quantity]
A recommended order quantity is generated based on the demand prediction value and the prediction correction value generated in the above step and the in-store information (s235).
The recommended order quantity is calculated by “recommended order quantity = (demand forecast value × forecast correction value) + safety stock quantity−stock quantity (FIG. 4)”, but other in-store information may be added.
The generated recommended order quantity is recorded in the storage medium provided in the recommended order quantity predicting means 4 and the order management means 5. (S240)

(3) Order processing (s300 to s370)
FIG. 9 shows a schematic diagram of order processing between the POS system 8 and the order management means 5.
When the order management means 5 is accessed from a terminal (POS terminal) in the POS system 8 via the WEB browser, the order management means 5 transmits a recommended order quantity browsing page to the POS terminal (s300, s310, s320). .
FIG. 10 shows an image of the recommended order quantity browsing page.
The recommended order quantity browsing page displays the recommended order quantity for each target product, and selects whether to perform order processing with the recommended order quantity or with the order quantity input from the POS terminal. Select buttons 51 and 52 are displayed. Note that it is desirable to simultaneously display weather and event information such as an event schedule as materials for making the above determination.

When placing an order with the recommended order number displayed on the recommended order quantity browsing page, the user is recommended to the order management means 5 from the POS terminal by pressing the selection button 51 displayed as “Order with Recommended Order Number”. An ordering command based on the number of orders is sent. Further, when placing an order with the number of orders newly input from the POS terminal, a new input is made from the POS terminal to the order management means 5 by pressing the selection button 52 displayed as “Order”. An ordering command based on the number of orders is sent. (S330)
The order management means 5 determines whether the received ordering command is an ordering command based on the recommended ordering number or the ordering number newly input from the POS terminal, and determines whether or not the ordering management unit 5 has an external ordering management system (see FIG. The ordering process is executed (s340 to s370).

(4): In-store information update processing (s400 to s440)
FIG. 11 shows a schematic diagram of the in-store information update process among the POS system 8, the in-store information acquisition means 2, and the data warehouse 3.
The in-store information acquisition means 2 receives in-store information from the POS system 8 based on a command from the terminal used by the system administrator of the present invention or a predetermined schedule (inventory count, sales record, disposal record for each product). , Ordering / purchasing results, etc.) are newly acquired, and the in-store information on the data warehouse 3 is updated. (S400-s440)

1 is a schematic configuration diagram of a marketing support system of the present invention. The figure which shows the example of a production | generation of a demand forecast value in this invention. The figure which shows the example of a production | generation of a prediction correction value in this invention. The figure which shows the example of a production | generation of the recommended order quantity in this invention. The schematic diagram of the questionnaire reply process of the marketing support method of the present invention. The image figure of the questionnaire response page displayed on a member terminal. The schematic diagram of the recommended order number generation processing of the marketing support method of the present invention. The detailed processing flow figure of the recommendation order number generation of the marketing support method of this invention. Schematic of the ordering process of the marketing support method of this invention. The figure which shows an example of the recommended order number browsing page displayed on a POS terminal. The schematic of the update process of the in-store information of the marketing support method of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Questionnaire acquisition means 2 In-store information acquisition means 3 Data warehouse 4 Recommended order number prediction means 41 Demand prediction value generation part 42 Forecast correction value generation part 43 Recommended order number generation part 5 Order management means 51 Selection button 52 Selection button 6 Network 7 Member terminal 8 POS system

Claims (5)

A marketing support system configured to be able to send and receive information via a network with a plurality of member terminals and customer POS systems,
Questionnaire acquisition means for acquiring questionnaire response information regarding the target product from the member terminal;
In-store information acquisition means for collecting in-store information about the target product from the POS system;
A data warehouse that stores at least target attributes, in-store information, and questionnaire response information associated with each target product;
A recommended order quantity predicting means for generating a recommended order quantity of the target product from the in-store information, questionnaire response information, and corusal information;
Order management means capable of executing authentication and ordering instructions for the recommended order quantity from the customer's POS system,
The questionnaire acquisition means notifies the member terminal that matches the target attribute of the target product of a questionnaire response request, acquires questionnaire response information classified into a purchaser and a non-purchaser of the target product, and the data Has the function of storing in the warehouse,
The recommended order quantity predicting means is:
In-store information for each target product acquired from the data warehouse, a demand prediction value generation unit that generates a demand prediction value based on the causal information,
From the questionnaire response information for each target product acquired from the data warehouse, a prediction correction value generation unit that generates a prediction correction value;
A recommended order quantity generation unit that generates a recommended order quantity for each target product from the demand forecast value and the forecast correction value,
Marketing support system. The prediction correction value generation unit generates a first correction value based on a questionnaire result of a purchaser and a second correction value based on a questionnaire result of a non-buyer from the questionnaire response information, and the first correction value and the first correction value The marketing support system according to claim 1, wherein a value obtained by integrating the two correction values is generated as a predicted correction value. A marketing support method of a marketing support system configured to be able to transmit and receive information via a network with a plurality of member terminals and customer POS systems,
The marketing support system is associated with each target product, a questionnaire acquisition unit that acquires questionnaire response information about the target product from the member terminal, an in-store information acquisition unit that collects in-store information about the target product from the POS system, In addition, a data warehouse that stores at least target attributes, in-store information, questionnaire response information, and corusal information, and a recommended order number for the target product is generated from the in-store information, questionnaire response information, and corus information. An order quantity predicting means, and an order management means capable of executing authentication of the recommended order quantity and an order command from the customer's POS system,
From the questionnaire acquisition means, a questionnaire response request is notified to the member terminal that matches the target attribute of the target product, and a questionnaire result classified into a purchaser and a non-purchaser of the target product is acquired, and the dataware Storing in the house;
Acquiring in-store information regarding the target product from the in-store information acquisition means to the customer's POS system;
The recommended order quantity predicting means generates in-store information for each target product acquired from the data warehouse and a demand forecast value based on the corusal information, and questionnaire response information for each target product acquired from the data warehouse Generating a forecast correction value, and generating a recommended order quantity for each target product from the demand forecast value and the forecast correction value;
Including at least
Marketing support method. At least one information processing apparatus configured to be able to send and receive information via a network with a plurality of member terminals and customer POS systems,
In-store information for each target product, processing to generate a demand forecast value based on the causal information,
Processing to generate a prediction correction value from questionnaire response information for each target product;
Processing for generating a recommended order quantity from the demand forecast value and the forecast correction value;
A program to execute at least A computer-readable medium in which at least the program according to claim 4 is recorded.