JP7135741B2 - Information processing device, information processing method, and program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and a program.

In Patent Document 1, history information indicating the use of programs installed in each of a plurality of devices is received and stored, attribute information for each user, information indicating devices available to the user, and By referring to the attribute information of the device, each piece of history information is classified into a plurality of groups based on commonality between the attribute information of the user who can use the device related to the history information and the attribute information of the device, and A first program that is selected based on the total number of uses for the group to which the first device belongs, by totaling the number of times of use of each program for each group based on the history information classified into the group, , an information processing system that identifies the first program that is not installed in the first device and outputs information stored regarding the identified first program.

JP 2016-006634 A

By the way, for example, a customer, who is a user of an information processing apparatus, may improve the functions of the information processing apparatus by introducing products to the information processing apparatus in order to solve his or her business problem. Providers of such products can propose to customers to introduce other products by analyzing data on products already introduced by customers. However, if, for example, another product is proposed based only on the number of times the product that has already been introduced is used, it may not be possible to propose a product that meets the customer's problem.

Therefore, an object of the present invention is to propose a product that better matches the customer's problem, as compared to the case where it is based only on the number of times the product that has already been introduced is used.

According to the first aspect of the invention, there is provided data acquisition means for acquiring product data, which is data of products that have already been introduced to a customer; a condition acquiring means for acquiring a proposal condition which is a condition individually determined for each other product; and when the product data acquired by the data acquiring means satisfies any of the proposal conditions, and output means for outputting proposal information indicating that the other product corresponding to the proposal condition is a product to be introduced to the customer.
In the invention according to claim 2, the proposal condition has a plurality of condition elements, and the output means outputs the proposal information when a predetermined number of the condition elements among the plurality of condition elements are satisfied. 2. The information processing apparatus according to claim 1, which outputs.
In the invention according to claim 3, the data acquiring means acquires the commercial material data from the introduced commercial material, and the output means outputs the commercial material data acquired by the data acquiring means to the plurality of 3. The information processing apparatus according to claim 2, wherein the proposal information is output when a predetermined number of conditional elements among the conditional elements are satisfied.
The invention according to claim 4 is the information processing apparatus according to claim 1, wherein the output means outputs the proposal information together with a reason for proposing the product of the proposal information.
In the invention according to claim 5, the data acquisition means acquires the product data from the introduced product, the proposal condition has a plurality of condition elements, and the output means outputs the data 5. The information processing apparatus according to claim 4, wherein when the merchandise data acquired by the acquiring means satisfies a predetermined number of conditional elements among the plurality of conditional elements, the degree of satisfaction of the plurality of conditional elements is output. be.
According to a sixth aspect of the present invention, the output means outputs information indicating a conditional element, among the plurality of conditional elements, which is determined not to be satisfied by the commercial material data from the introduced commercial material. 6. The information processing apparatus according to item 5.
According to a seventh aspect of the invention, the data acquisition means acquires the merchandise data from the introduced merchandise, and the proposed conditions have a plurality of conditional elements each of which is prioritized. 7. The output means according to any one of claims 1 to 6, wherein the output means determines whether or not the product data acquired by the data acquisition means satisfies each of the plurality of conditional elements according to the order of priority. It is an information processing device.
In the eighth aspect of the invention, the proposed conditions include a first conditional element relating to how the introduced product is used and a second conditional element relating to requirements for operating the other product. 8. The information processing apparatus according to any one of claims 1 to 7, wherein said output means outputs said proposal information when both said first conditional element and said second conditional element are satisfied.
According to the ninth aspect of the invention, when the output means cannot determine whether or not the second conditional element is satisfied from the product data, the output means determines whether the customer satisfies the second conditional element. 9. The information processing apparatus according to claim 8, which outputs information for inquiry.
The invention according to claim 10, wherein the output means, when the proposal condition for one of the plurality of other products is not satisfied, 10. The information processing apparatus according to any one of claims 1 to 9, wherein it is determined whether a product other than (1) satisfies the proposal conditions.
In the eleventh aspect of the invention, the output means outputs information indicating all of the products satisfying the proposal conditions when there are a plurality of products satisfying the proposal conditions among the plurality of other products. The information processing apparatus according to any one of claims 1 to 10.
According to a twelfth aspect of the invention, there is provided a step of acquiring product data, which is data of a product that has already been introduced to a customer; a step of acquiring a proposal condition that is a condition individually determined for each product; and a step of outputting proposal information indicating that the product is a product to be introduced to the customer.
According to the thirteenth aspect of the invention, there is provided a function of acquiring product data, which is data of a product that has already been introduced to a customer, and a A function to acquire proposal conditions, which are conditions individually determined for each product, and when the product data satisfies any of the proposal conditions, the other products corresponding to the satisfied proposal conditions and a function of outputting proposal information, which is information indicating that the product is a product to be introduced to the customer.

According to the first aspect of the invention, it is possible to propose a product that better matches the customer's problem, as compared to the case where the already introduced product is based only on the number of times of use.
According to the invention of claim 2, it is possible to propose products that better match the customer's problem.
According to the invention of claim 3, the process of determining the proposed merchandise is simplified.
According to the invention of claim 4, it is possible to give persuasiveness to the proposal of the merchandise.
According to the invention of claim 5, it is possible to give persuasiveness to the proposal of the merchandise.
According to the sixth aspect of the present invention, it is possible to increase the number of products that can be proposed by, for example, inquiring of the customer regarding the conditional elements determined not to satisfy the product data.
According to the invention of claim 7, the process of determining the proposed merchandise is simplified.
According to the invention of claim 8, products can be proposed according to the customer's usage environment.
According to the ninth aspect of the invention, it is possible to increase the number of products that can be proposed.
According to the invention of claim 10, it is possible to increase the number of products that can be proposed.
According to the eleventh aspect of the invention, the number of products that can be proposed can be increased.
According to the twelfth aspect of the present invention, it is possible to propose a product that better matches the customer's problem, as compared with the case where the already introduced product is based only on the number of times of use.
According to the thirteenth aspect of the present invention, it is possible to propose a product that better matches the customer's problem, compared to the case where the already introduced product is based only on the number of times of use.

1 is a schematic configuration diagram of a business improvement system to which this embodiment is applied; FIG. FIG. 4 is a first sequence diagram showing processing operations of the business improvement system; FIG. 9 is a second sequence diagram showing processing operations of the business improvement system; FIG. 11 is a third sequence diagram showing processing operations of the business improvement system; FIG. 14 is a fourth sequence diagram showing processing operations of the business improvement system; It is a figure which shows the hardware constitutions of a merchandise proposal server. It is a figure which shows the functional structure of a merchandise proposal server. (a) shows a customer information list managed by the customer information management unit, and (b) shows a product information list managed by the product information management unit. FIG. 4 is a diagram showing a product chain list managed by a product chain list creating unit; It is the flowchart which showed the processing operation example of a merchandise proposal server. FIG. 10 is a flow chart showing product proposal processing of a product proposal unit; FIG. FIG. 10 is a diagram showing an effect report; 10 is a flowchart showing effect report processing by a product proposal unit; It is a figure which shows a questionnaire. It is a figure which shows a merchandise proposal image. 2 is a diagram showing a hardware configuration example of an image processing apparatus; FIG. 2 is a diagram showing a functional configuration of an image processing device; FIG. 3 is a diagram showing the functional configuration of a plug-in management unit; FIG. (a) is a diagram showing a calculation example of a judgment value, and (b) is a diagram showing an example of weighting points.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.
<Business improvement system 1>
FIG. 1 is a schematic configuration diagram of a business improvement system 1 to which this embodiment is applied.
The business improvement system 1 includes a customer terminal 10 , an image processing device 20 , a cloud server 30 , a product proposal server 40 , a product distribution server 50 , a sales terminal 60 and a firewall 70 . The cloud server 30 , the product proposal server 40 , the product delivery server 50 , the sales terminal 60 and the firewall 70 are connected via a network 80 . Also, the customer terminal 10 and the image processing device 20 are connected to the network 80 via the firewall 70 .

Here, the customer terminal 10 , the image processing device 20 and the firewall 70 constitute a customer usage environment 90 . This customer usage environment 90 is an environment in which devices that can cooperate with services provided by the business improvement system 1 are used. The illustrated customer usage environment 90 is the system environment for users of the services provided by the business improvement system 1 .

Also, in the following description, the user of the service provided by the business improvement system 1 may be called a customer. A customer is not limited to a specific person or organization, and includes, for example, an individual or a company that conducts business. Also, in the following description, an organization or person who sells the business improvement system 1 or provides services via the business improvement system 1 may be referred to as a provider. Also, an organization or a person who conducts sales activities such as making proposals regarding the business improvement system 1 to customers may be referred to as a sales representative. In the following explanation, the provider and sales person are different persons, but they may be the same person or the same organization. Also, if the provider is an organization, the sales person may be a member of that organization. That is, a sales representative may be part of the provider.

Further, in the customer terminal 10, the image processing device 20, and the cloud server 30, it is possible to add products for functional improvement. A product is provided to a customer by a provider. This product is used in the customer's business and can be regarded as something that can solve the customer's problem. In addition, the product can be regarded as being able to acquire data on how the product is used by the customer. Examples of specific products include devices and software used in the business improvement system 1, for example. The product is, for example, the customer terminal 10, the image processing device 20, or a device connected to the customer terminal 10 and the image processing device 20 (for example, an image reading device, etc.). In addition, commercial materials include software installed in the customer terminal 10, the image processing device 20, and the cloud server 30, for example. Examples of this software include software for document management and document sharing, and so-called plug-ins, which are programs for adding functions to software. Note that this software may include a smartphone application installed in a smartphone or the like, content such as an electronic book or video, and the like.

In the following, while explaining each component of the business improvement system 1, the relationship between each component and the product will be described.
The customer terminal 10 is configured by a computer device capable of communicating with the image processing device 20 or the like. The customer terminal 10 in the illustrated example is a personal computer (PC) operated by a customer. The illustrated customer terminal 10 is a desktop computer, but may be a so-called mobile terminal such as a smart phone, a tablet computer, or a notebook computer. This customer terminal 10 is capable of installing or connecting a commercial product and operating the commercial product.

The image processing apparatus 20 is a so-called multifunction peripheral (MFP) having a function of forming an image on paper, a function of scanning an original image, and a FAX communication function of performing facsimile (FAX) transmission. This image processing apparatus 20 is capable of installing or connecting commercial materials and operating the commercial materials.

The cloud server 30 stores data transmitted from the image processing apparatus 20 or the like via the network 80, and has a function of transmitting the stored data or the like when accessed from the customer terminal 10 or the like. The cloud server 30 is capable of installing or connecting to commercial products and providing the functions of the commercial products to the customer terminal 10, the image processing device 20, and the like.

The product proposal server 40 receives data collected by the image processing device 20 and each product, and proposes products to customers (details will be described later).
The commercial material distribution server 50 distributes the commercial material to the image processing apparatus 20 or the like via the network 80 when the commercial material purchased by the customer is software.

The sales terminal 60 is configured by a computer device or the like that can communicate with the product proposal server 40 or the like. The sales terminal 60 in the illustrated example is a personal computer operated by a sales representative. Although the illustrated customer terminal 10 is a notebook computer, it is not particularly limited and may be a computer of another type. Based on the data received by the sales terminal 60 from the product proposal server 40 or the like, the sales person can carry out sales activities for customers.

The firewall 70 prevents unauthorized access and intrusion from the outside. The illustrated firewall 70 is configured as dedicated hardware (firewall server), but may be incorporated as software into the customer terminal 10, the image processing device 20, or the like.

Network 80 is a communication network used for data exchange between devices. The illustrated network 80 is configured by the Internet, but is not particularly limited, and may be, for example, a LAN (Local Area Network) or a WAN (Wide Area Network). Moreover, the communication line of the network 80 may be wired or wireless, and both of them may be used.

<Product proposal>
By the way, in recent years, business efficiency has been improved by utilizing IoT (Internet Of Things), big data, and AI (Artificial Intelligence). However, even if you actually try to improve the efficiency of your business by using these, you may not be able to improve the efficiency of your business even if you purchase general-purpose products because the problems are different for each customer.

In this case, for example, by collecting input/output data in the customer's business and analyzing the collected data, it is possible to find problems and determine countermeasures. Such data collection and analysis are carried out by persons in charge with specialized knowledge, such as engineers and consultants. However, it is difficult, for example, for small and medium enterprises with limited resources to hire special personnel such as engineers. In addition, there is also a measure to improve business efficiency by purchasing products that are popular in the industry to which the customer belongs, but the products do not correspond to the customer's business problem, and the efficiency that is commensurate with the investment cost. may not be achievable. Therefore, even if you do not have a special person in charge of data collection and analysis, it is possible to build a system that can solve the business problems of the company by combining products while keeping costs down. It has been demanded.

In the business improvement system 1 according to the present embodiment, it is determined whether or not the proposal conditions, which are the conditions for proposing the next product, are satisfied from the data processed by the products already introduced to the customer, and the proposal conditions are met. If it satisfies the above, the following products will be proposed. As a result, it is possible to build a system that can solve customers' business problems while combining products.

In addition, in the business improvement system 1 according to the present embodiment, the product introduced to the customer collects data on the processing status of the product, thereby finding problems in the customer's business in a chain reaction and solving the problem. It is possible to propose and provide products suitable for solutions in a chain. To explain further, multiple products are proposed in order according to the customer's business problem. This makes it possible to solve a wide range of business problems that cannot be solved with a single product. In addition, it is possible to provide the optimum merchandise in the optimum order.

In the business improvement system 1 shown in the figure, products are proposed in a chain using a product chain list. Although the details will be described later, the product chain list is a candidate list of products to be proposed to the customer, which is linked from one product to the next product. In addition, the product chain list is based on collected data collected by products that have already been introduced to customers (introduced products) (this collected data collected by products is an example of product data). Therefore, it indicates a product (proposed product) that is proposed to be newly introduced to the customer. Also, to introduce a product to a customer means that the customer can operate the product.

<Processing operation of business improvement system 1>
FIG. 2 is a first sequence diagram showing processing operations of the business improvement system 1. As shown in FIG.
FIG. 3 is a second sequence diagram showing processing operations of the business improvement system 1. As shown in FIG.
FIG. 4 is a third sequence diagram showing the processing operations of the business improvement system 1. As shown in FIG.
FIG. 5 is a fourth sequence diagram showing processing operations of the business improvement system 1. As shown in FIG.
Next, the processing operation of the business improvement system 1 according to the present embodiment will be described with reference to FIGS. 1 to 5. FIG. Although FIGS. 2 to 5 are divided into a plurality of drawings for clarity, they show a series of processing operations performed continuously in the order of FIGS. 2 to 5. FIG.

Also, as a prerequisite for the following explanation, it is assumed that the commercial material provided by the provider has not been introduced to the customer, that is, the commercial material that has been introduced does not exist on the customer side. Specifically, it is assumed that the customer terminal 10 purchased from a party other than the provider is installed in the customer usage environment 90, but the image processing device 20 is not installed. Also, it is assumed that the customer terminal 10 and the cloud server 30 do not incorporate any commercial material provided by the provider to the customer.
In addition, the processing operation of the business improvement system 1 described below is roughly as follows. Material D is introduced in order.

The processing operation of the business improvement system 1 will be specifically described below.
First, as shown in FIG. 2, the sales terminal 60 operated by the sales person registers product information, which is information about products, in the product proposal server 40 . Here, the product information includes the price of the product, the type of product (for example, for the customer terminal 10, for the image processing device 20, for the cloud server 30, etc.), data from which the product can be collected, and introduction of the product. It includes data used for judgment (judgment data) and judgment conditions. When new product information is provided by the sales terminal 60, the product proposal server 40 generates (constructs) a product chain list (described later).

Next, the sales terminal 60 operated by the sales person registers customer information (information on the customer's business type and business) in the merchandise proposal server 40 . Then, the merchandise proposal server 40 determines whether there is a merchandise to be proposed to the customer based on the registered customer information of the customer. In the illustrated example, since the product has not been introduced to the customer, the product proposal server 40 does not judge whether there is any product to be proposed, but prepares a questionnaire (described later) and sends it to the customer terminal 10. Send.

Next, the response to the questionnaire is transmitted from the customer terminal 10 to the product proposal server 40 by the customer's operation. Then, the product proposal server 40 that has received the answers to the questionnaire analyzes the answers to the questionnaire. Then, the merchandise proposal server 40 extracts and proposes the first merchandise (originating merchandise) to the customer based on the analysis result of the answer. Here, it is assumed that the image processing device 20 is proposed as a starting product, and the image processing device 20 is installed by the customer.

Note that the starting point product is proposed by the product proposal server 40 in a state in which there is no introduced product. Therefore, it is not possible to propose a starting point product based on the data collected from the introduced product. Therefore, the starting point product in the illustrated example is determined from products whose proposal can be judged according to the answers to the questionnaire. That is, the starting point product is determined based on data other than the data collected from the introduced product. In addition, if there is a product that the salesperson has sold to the customer in past sales activities, it may be used as the starting product.

Also, in FIG. 2, it has been explained that the registration of product information and the registration of customer information are executed by the salesperson operating the sales terminal 60, but the present invention is not limited to this. For example, it may be executed by the provider operating the product proposal server 40 or the like.

Moreover, the questionnaire sent by the product proposal server 40 to the customer terminal 10 may be sent to the sales terminal 60 together with the customer terminal 10 or instead of the customer terminal 10 . As a result, when the customer's questionnaire cannot be answered or the answer is insufficient, it becomes possible for the salesperson to contact the customer. To further explain, a sales representative may obtain responses to a survey from a customer. Then, the salesperson may send the responses to the questionnaire to the product proposal server 40 via the sales terminal 60 or the like.

Next, subsequent processing operations of the business improvement system 1 will be described with reference to FIG.
As described above with reference to FIG. 2, it is assumed here that the image processing apparatus 20, which is the starting product, is installed.
First, when the image processing device 20 installed in the customer usage environment 90 starts operating, the image processing device 20 collects data at a predetermined timing (for example, periodically), and sends the collected data to the product proposal server 40. Send (upload) to

Next, the product proposal server 40 analyzes the received collected data and creates an effect report. Although the details will be described later, the effect report is a report for judging whether the results expected by the customer who purchased the product have been obtained. The effect report generated by the product proposal server 40 is transmitted to the customer terminal 10 and sales terminal 60 . With this effect report, for example, if the product is the image processing apparatus 20, it is presented to the customer that the number of copies or the number of scans and the speed range of the image processing apparatus 20 match.

The product proposal server 40 also compares the collected data with the judgment conditions of the product chain list to determine whether there is a product to be proposed next. To explain further, the merchandise proposal server 40 extracts the proposed merchandise and proposes it to the customer. Here, the commercial material A and the commercial material E are proposed by the commercial material proposal server 40 . The proposal of the proposed product is executed by sending an e-mail containing information on the proposed product (for example, a URL indicating the WEB page of the proposed product) to the customer terminal 10 . This mail is also sent to the sales terminal 60 . A salesperson conducts sales activities for customers based on this e-mail or the like. Specifically, the salesperson can explain the proposed merchandise to the customer and encourage their purchase.

Next, when the customer who received the proposal decides to purchase the merchandise A and the merchandise E, a purchase instruction is transmitted from the customer terminal 10 operated by the customer to the merchandise proposal server 40 . At this time, the purchase instruction is also transmitted to the sales terminal 60 . It should be noted that the instruction to purchase the product can be made by accessing the URL of the WEB page described in the email proposing the proposed product, or by operating the UI 25 of the image processing device 20 (see FIG. 16, which will be described later), or The decision is made by an instruction or the like from the sales person who has confirmed the customer's purchase via the sales terminal 60 .

Next, the product proposal server 40, which has received the purchase instruction, transmits a distribution request for the product A and the product E to the product distribution server 50, and the product distribution server 50 distributes the product A and the product E. Send E. In the illustrated example, the product A is software for the customer terminal 10 , so it is transmitted to the customer terminal 10 and installed in the customer terminal 10 . Further, since the commercial material E is a function expansion plug-in that operates on the image processing apparatus 20 , it is transmitted to and installed on the image processing apparatus 20 .

Next, the delivered and installed product A and product E start operating on the customer terminal 10 and the image processing device 20, respectively. Then, the commercial material A and the commercial material E collect data at predetermined timings and transmit the collected data to the commercial material proposal server 40 .

Next, subsequent processing operations of the business improvement system 1 will be described with reference to FIG.
The product proposal server 40 analyzes the collected data received from the product A and the product E. FIG. The product proposal server 40 also generates an effect report for the product A and the product E, and transmits it to the customer terminal 10 and the sales terminal 60 . Then, the merchandise proposal server 40 extracts the proposed merchandise and transmits it to the customer terminal 10 and the sales terminal 60 . Here, the product B is proposed by the product proposal server 40 .

Next, when the customer decides to purchase the product B, the customer terminal 10 transmits a purchase instruction to the product proposal server 40 and the sales terminal 60 . In addition, the product proposal server 40 that has received the purchase instruction transmits a distribution request for the product B to the product distribution server 50, and the product distribution server 50 transmits the product B. FIG. Here, the product B is a function provided by the cloud server 30 as a cloud service. Therefore, the product proposal server 40 transmits the customer's setting file to the cloud server 30 instead of the software. By setting the customer in the cloud server 30 using this setting file, the provision of the service of the product B to the customer is started. That is, the product B works.

Next, commercial material B for which the service has been started collects data of the commercial material on the cloud server 30 at a predetermined timing, and transmits the collected data to the commercial material proposal server 40 . In addition, the product proposal server 40 analyzes the collected data received from the product B, generates an effect report of the product B, and transmits it to the customer terminal 10 and the sales terminal 60 .

Next, subsequent processing operations of the business improvement system 1 will be described with reference to FIG.
The commercial material proposal server 40 determines whether there is a commercial material to be proposed next from the collected data collected for the commercial material B. Here, it is assumed that there are products C and D as products that can be proposed after product B, but the collected data do not satisfy the conditions for providing these products. In the illustrated example, the merchandise proposal server 40 performs processing for acquiring additional information for determining whether to propose merchandise D, out of merchandise C and merchandise D, which can be proposed. conduct. Specifically, a questionnaire is created and sent to the customer terminal 10 .

Next, when a questionnaire is answered from the customer terminal 10 by the customer's operation, the product proposal server 40 analyzes the questionnaire answer. In addition, the merchandise proposal server 40 extracts the proposed merchandise based on the questionnaire. Here, when the conditions of the product D are satisfied based on the responses to the questionnaire received from the customer terminal 10, the product D is proposed by the product proposal server 40. FIG.

Next, when the customer decides to purchase the product D, the customer terminal 10 transmits a purchase instruction to the product proposal server 40 and the sales terminal 60 . In addition, the merchandise proposal server 40 that has received the purchase instruction transmits a distribution request for the merchandise D to the merchandise distribution server 50, and the merchandise distribution server 50 transmits the merchandise D. FIG. Here, since the product D is a function provided as a cloud service by the cloud server 30 , the product proposal server 40 transmits the customer's setting file to the cloud server 30 . By setting the customer in the cloud server 30 according to this setting file, the provision of the service of the product D is started. That is, the product D is activated.

Next, for the product D for which the service has been started, data of the product D is collected on the cloud server 30 at a predetermined timing and transmitted to the product proposal server 40 . Further, the product proposal server 40 analyzes the collected data received from the product D, generates an effect report for the product D, and transmits it to the customer terminal 10 and the sales terminal 60 . In addition, the product proposal server 40 determines whether there is a product to be proposed next, based on the collected data obtained by the product D. Here, since there is no product to be proposed after the product D in the product chain list, the product proposal server 40 ends the product proposal processing operation.

<Hardware Configuration of Merchandise Proposal Server 40>
FIG. 6 is a diagram showing the hardware configuration of the product proposal server 40. As shown in FIG.
Next, the hardware configuration of the product proposal server 40 will be described with reference to FIG.
As shown in FIG. 6, the product proposal server 40 includes a CPU 41, a RAM (Random Access Memory) 42, a ROM (Read Only Memory) 43, a HDD (Hard Disk Drive) 44, and a communication interface (communication I/ F) 45;

The CPU 41 implements each function of the product proposal server 40 by loading various programs stored in the ROM 43 or the like into the RAM 42 and executing them.
The RAM 42 is a memory used as a work memory for the CPU 41 and the like.
The ROM 43 is a memory that stores various programs executed by the CPU 41 .
The HDD 44 is a storage area that stores input data for various programs executed by the CPU 41 and output data from various programs.
Communication I/F 45 transmits and receives various information to and from other devices via network 80 .

<Functional Configuration of Merchandise Proposal Server 40>
FIG. 7 is a diagram showing the functional configuration of the product proposal server 40. As shown in FIG.
8A shows a customer information list managed by the customer information management unit 411, and FIG. 8B shows a product information list managed by the product information management unit 413. FIG.
FIG. 9 is a diagram showing a product chain list managed by the product chain list creation unit 415. As shown in FIG.

Next, the functional configuration of the product proposal server 40 will be described with reference to FIGS. 7 to 9. FIG.
As shown in FIG. 7, the product proposal server 40 includes a customer information management unit 411, a product information management unit 413, a product chain list creation unit 415, a collected data collection unit 417, and a product proposal unit 421. , a collected data control unit 423 , and a product delivery instruction unit 425 . Each functional configuration constituting the product proposal server 40 will be described below.

<Customer information management unit 411>
The customer information management unit 411 manages customer information. This customer information is entered by a salesperson, provider, or the like. The illustrated customer information management unit 411 manages customer information using a customer information list as shown in FIG. 8(a). The customer information list shown in FIG. 8(a) is managed by linking the customer ID, which is the identification information of the customer, the business type of the customer, and the purchased product, which is the product purchased by the customer. be. For example, a customer identified by "customer 01" as the "customer ID" in FIG. have purchased.

<Product information management unit 413>
The product information management unit 413 manages product information. This merchandise information is input by a salesperson, a provider, or the like. The illustrated product information management unit 413 manages product information using a product information list as shown in FIG. 8B.

Hereinafter, the product information list will be described in detail with reference to FIG. 8(b).
As shown in FIG. 8(b), the product information list includes "product", "collected data" which is data collected by the product, and "judgment data" used for judgment when proposing the product. ”, “judgment conditions”, and “introduction conditions”, which are prerequisites for introducing the product, are linked and managed.

Each item of the merchandise information list will be described below.
First, in the illustrated example, the "merchandise" includes "image processing apparatus 20" which is "MFP" in the figure, "merchandise A" which is software for managing documents, and software for sharing documents. It includes "Product B", "Product C" which is software for reimbursement of travel expenses, "Product D" which is software for business card management, and "Product E" which is software for simple scanning. be

“Collected data” is data collected from each product. That is, the collected data is data relating to the behavior of the commercial material that is collected by the commercial material itself after the commercial material is introduced to the customer. Here, the collected data is data indicating which function is used in each product.

For example, when the "merchandise" is the "image processing apparatus 20", "JobLog" and "count by document (paper)" are collected as collected data. Here, "JobLog" is a history of jobs executed by the customer in the image processing apparatus 20 (JobLog, job log), and execution dates and times of copying/printing/scanning/fax transmission/reception, the number of jobs, and the like are acquired. “Count by document (paper)” is a count for each type of document that has been scanned using a paper medium in the image processing apparatus 20 . This "count by document" is classified by analyzing the content of the executed document. For example, based on the result of OCR (Optical Character Recognition) in the document, the type of the document such as an invoice or fax cover sheet is determined, and the count of each type of document is collected.

In addition, when the "merchandise" is "merchandise A", the "number of converted documents", the "number of distributed documents (Email)", and the "count by document (electronic)" are collected as collected data. . The "number of converted documents" is the number of documents converted into electronic format by the product A. “Number of distributed documents (Email)” is the number of documents sent by e-mail for product A. “Count by document (electronic)” is a count for each type of document processed as electronic data by product A. FIG.

Further, when the "merchandise" is "merchandise B", the "count by document (electronic)", the "number of duplicate documents", and the "number of document accesses" are collected as collected data. “Count by document (electronic)” is a count for each type of document stored in the cloud server 30 by the product B. FIG. The “number of duplicated documents” is the number of duplicated documents stored in the cloud server 30 for the product B. FIG. The "number of document accesses" is the number of accesses to each document stored in the cloud server 30 by the product B. FIG.

Further, when the "merchandise" is "merchandise C", "settlement processing time" is collected as collected data. “Settlement processing time” is the time required for the travel expense settlement executed by the product C. FIG.
Further, when the "merchandise" is "merchandise D", "count by document (electronic: business card)" is collected as collected data. “Count by document (electronic: business card)” is the count of business cards scanned by using an electronic medium for product D. FIG.

Further, when the "merchandise" is "merchandise E", "count by document (paper: simple scan)" is collected as collected data. "Count by document (paper: simple scan)" is a count for each type of document scanned by the image processing apparatus 20 using a paper medium.

The "judgment data" in the product information list shown in FIG. 8B is the type of data for judging whether or not to propose the introduction of each product to the customer. That is, the judgment data is the type of data for proposing the introduction of each product before introducing the product to the customer.
The "judgment condition" is a condition for judging whether or not to propose the introduction of each product to the customer. That is, the judgment condition is a condition for proposing the introduction of each product before introducing the product to the customer.

Here, the "judgment data" and the "judgment condition" form a set. Also, if any of the plurality of sets is satisfied, it is determined that the conditions proposed to the customer are satisfied (OR condition). Also, the greater the number of conditions that are satisfied, the greater the strength with which the proposal should be executed.

Further, in the illustrated example, the "judgment data" includes "questionnaire", "JobLog", and the like. “Questionnaire” indicates that whether or not to propose the introduction of the product to the customer is determined based on the answers to the questionnaire sent from the customer terminal 10 . "JobLog" indicates that whether or not to propose the introduction of the product to the customer is determined based on the history of the job executed by the customer for the product A, for example.

Further, as the "judgment data", in principle, data such as "JobLog" collected from products is used. However, if the data is insufficient to decide whether or not to propose the introduction of the product, or if it satisfies the predetermined conditions, it may be necessary to use other data other than the data collected for the product, such as answering a questionnaire. Data are used exceptionally. For example, if the conditions of "JobLog" and "count by document" out of the "judgment data"/"judgment conditions" of merchandise A are not satisfied, it is necessary to make a judgment based on the judgment result of the questionnaire. 40 sends a questionnaire to the customer terminal 10 . In addition, in FIG. 8(b), the use of a questionnaire as data other than the data collected from the product is displayed in brackets as "(questionnaire)".

Also, for example, the "collected data" in the "merchandise A" is the "number of converted documents", the "number of distributed documents (Email)", and the "count by document (electronic)". On the other hand, the “judgment data” for “merchandise B” are “JobLog”, “number of converted documents”, and “number of distributed documents (Email)”. Therefore, the "number of converted documents" and the "number of distributed documents (Email)" of the "collected data" collected by the operation of "product A" are the same as the "number of converted documents" and "distribution If the "judgment condition" of "the number of documents (Email)" is satisfied, the "product B" is judged to be the proposed product. In the illustrated example, when the "number of converted documents" is 200 or more (number of documents >= 200) or when the "number of distributed documents (Email)" is 20 or more (number of documents >= 20), " Product B” is determined to be the proposed product.

In addition, "merchandise D" includes "document-by-document count" as "judgment data". Therefore, if the "count by document (electronic)", which is the "collected data" of "merchandise A", satisfies the "judgment condition" of the "count by document" in "merchandise D", then "merchant D" It is judged as a proposed product. In the illustrated example, when the number of business cards is 100 or more in the "count by document" (business card >= 100), "merchandise D" is determined to be the proposed merchandise.

"Introduction conditions" in the product information list shown in FIG. 8B are conditions (requirements) for introducing each product to the customer. That is, the "introduction conditions" are devices, software, etc. that must be installed in advance for the introduction of each product. Here, "NA" in the "installation conditions" shown in the figure indicates that there is no condition for introduction, "PC" indicates that a computer must be installed in advance, and "merchandise B". indicates that it is a condition that "merchandise B" has been introduced in advance. To explain further, for example, the "introduction condition" of "merchandise D" is "merchandise B". Therefore, "merchandise D" cannot be a proposed merchandise until after "merchandise B" is introduced. By proposing a commercial product based on the introduction conditions, the proposed commercial product can be quickly put into operation after the introduction of the proposed commercial product.

In the illustrated example, if the "introduction condition" of the product and any one of the "judgment conditions" are satisfied, it is determined that the product can be proposed. In other words, in addition to judging whether the “judgment conditions” are met based on the “collected data” of the introduced product, it is also judged whether the “introduction conditions” are met. It is judged that the material can be proposed. It may be determined that the product can be proposed when the "introduction condition" of the product and a plurality of "judgment conditions" are satisfied.

<Product chain list creation unit 415>
The product chain list creating unit 415 shown in FIG. 7 creates and manages the product chain list. To explain further, the product chain list creation unit 415 creates a product chain list from the product information collection data, judgment data, judgment conditions, and introduction conditions managed by the product information management unit 413 .

The product chain list will be described in detail below with reference to FIGS. 7 to 9. FIG.
As shown in FIG. 9, the product chain list designates a chain of products to be proposed next (proposed products) from the data collected from the previous product (introduced products). The beginning of this product chain list is the product that is the starting point of the list (originating product), which is the image processing device 20 in the illustrated example.

A product chain has one or more paths. For example, from the collected data of the "image processing apparatus 20" which is the starting point product, there are a plurality of paths proposing each of "product A" and "product E". Specifically, there are paths (see paths P11 and P12) for proposing "product A" and "product E" using "JobLog" of "image processing apparatus 20" as collected data. Further, there are paths for proposing "merchandise A" and "merchandise E" using the "count by document" of the image processing apparatus 20 as collected data (see path P13 and path P14).

Further, from the collected data of "merchandise A", there are paths that propose each of "merchandise B", "merchandise C", and "merchandise D". Specifically, there is a path (see path P21) for proposing "product B" using the "number of converted documents" of "product A" as collected data. There is also a path (see path P22) for proposing "product B" using the "number of distributed documents (Email)" of "product A" as collected data. There are also paths (see paths P23 and P24) for proposing "product C" and "product D" using the "count by document" of "product A" as collected data.

Further, from the collected data of "merchandise B", there are paths to propose "merchandise C" and "merchandise D". Specifically, there are paths (see paths P31 and P32) for proposing 'merchandise C' and 'merchandise D' using the 'count by document' of 'merchandise B' as collected data.
In the illustrated example, there is no product to be proposed after "product C,""productD," and "product E," which is the end of the list.

In addition, since the collected data of the products in the product chain list cannot be used for the proposal of the starting point product, may be determined.
Also, when a new product is registered in the product information management unit 413, or when a product registered in the product information management unit 413 is upgraded or terminated, collected data, When judgment data/judgment conditions or introduction conditions are updated, the product chain list creating unit 415 reconstructs the product chain list. In other words, the product information management unit 413 selects and proposes products in the order according to the product chain list while automatically updating the product chain list.

In addition, by using the product chain list as described above, it is possible to determine the product that solves the customer's business problem from among a plurality of products. To explain further, it is possible to grasp the customer's business problems based on how the customer uses the introduced product, and to propose to the customer a product that solves the grasped problem. Here, when a new product is registered in the product information management unit 413, the product chain list is reconstructed. According to this reconstructed product chain list, products that were not proposed products before reconstruction can be newly specified as proposed products. As a result, it is possible to propose more products that can solve customers' business problems.

Further, by using the product chain list, the type of data to be collected for the previous product (introduced product) changes according to the judgment data of the product to be proposed next (proposed product). For example, when it is possible to collect a plurality of data from the introduced product, only data that matches the judgment data of the proposed product is collected from among the plurality of data that can be collected from the introduced product. To explain further, for example, if product A is an already-introduced product and product B is a proposed product, the "number of converted documents", "number of distributed documents (Email)", Of the "count by document", the "number of converted documents" and the "number of distributed documents (Email)", which are judgment data for product B, are collected, but the "count by document" is not collected. As a result, the amount of collected data collected by the product A is suppressed.

<Collected data collection unit 417>
The collected data collecting unit 417 shown in FIG. 7 collects collected data collected from each of the introduced products. For example, "JobLog" and "count by document (paper)", which are "collected data", are collected from the "image processing apparatus 20". Here, as the "collected data" from the "image processing apparatus 20", for example, data such as FAX reception jobs=150, Scan jobs=150, and the number of documents counted by document count=15 are collected.

<Product proposal department 421>
The product proposal unit 421 shown in FIG. 7 analyzes the data collected by the collected data collection unit 417, determines the proposed product based on the judgment conditions and introduction conditions of the product chain list, and proposes it to the customer. For example, "JobLog" and "count by document", which are "collected data" from the "image processing apparatus 20", satisfy the judgment conditions for product A and product E (for example, FAX reception job = 150, Scan job). = 150, and the number of documents counted by document count = 15), "product A" and "product E" are proposed.

In addition, the “number of converted documents”, “number of distributed documents (Email)”, and “count by document (paper)”, which are “collected data” from “product A”, satisfy the proposal judgment conditions for “product B”. If it is determined that the requirements are satisfied (for example, the number of converted documents=240, the number of distributed documents=20), "merchandise B" is proposed. Here, after introducing “merchandise A”, “collected data” from the “image processing apparatus 20”, ie, “count by document” satisfies the judgment condition of “merchandise D” (for example, business card = 120). If it is determined that, "merchandise D" can be a proposal candidate. However, as shown in FIG. 8(b), "merchandise D" cannot be proposed until after "merchandise B" is introduced because "merchandise B" is an introduction condition.

As described above, in the present embodiment, the product chain list does not determine the proposed product based only on the number of times the introduced product is used. Proposed products are determined based on data on how well the functions are used and how the functions are used. Further, the product chain list has judgment conditions individually determined for each product, and when the judgment conditions are satisfied, the proposed product is determined.

Now, as an example different from the present embodiment, it is possible to employ a mode in which the customer's usage rankings of other companies in the same industry are used when deciding on a product to propose. In other words, it is a form of proposing to customers products that are frequently used by other companies in the same industry. However, for example, when a new commercial product is introduced to the market, the number of times of use is 0 and the usage ranking is low because there are no users who actually use the commercial product in the field. In addition, even if a product is highly evaluated in the market, it takes time to reach the top of the usage ranking. On the other hand, in the present embodiment, proposed products are determined based on the attributes of the product and the manner in which the customer uses the introduced product (operation history of the introduced product). It is possible to propose products regardless of the timing of introduction.

<Collection data control unit 423>
The collected data control unit 423 shown in FIG. 7 determines duplication of collected data when a plurality of commercial products are operated, and instructs the commercial products to stop or resume collection of overlapping collected data. Here, if the collected data collected by the introduced products overlaps or is similar, by aggregating the overlapping/similar data collected between products, security risks related to data collection and data collection It is possible to reduce the load for

<Merchandise delivery instruction unit 425>
The product distribution instruction unit 425 shown in FIG. 7 instructs the product distribution server 50 to distribute the product when the customer decides to purchase the product.

<Example of processing operation of product proposal server 40>
FIG. 10 is a flow chart showing an example of the processing operation of the product proposal server 40. As shown in FIG.
Next, a processing operation example of the product proposal server 40 will be described with reference to FIGS. 1, 7, and 10. FIG.

First, the merchandise proposal unit 421 in the merchandise proposal server 40 adds a new merchandise to the merchandise information list managed by the merchandise information management unit 413 when the salesperson operates the sales terminal 60 ( (S1001). Then, if the product information has been updated (YES in S1001), the product chain list creating unit 415 builds a product chain list (S1002). Then, the merchandise proposal unit 421 executes merchandise proposal processing for proposing the proposed merchandise to customers registered in the customer information list managed by the customer information management unit 411 (S1003).

<Product Proposal Processing by Product Proposal Unit 421>
FIG. 11 is a flowchart showing the product proposal processing of the product proposal unit 421. As shown in FIG.
Next, an operation example of the product proposal processing of the product proposal unit 421 will be described with reference to FIGS. 1, 7, and 11. FIG.

First, the product proposal unit 421 determines whether there is collected data collected from the introduced product (S1101). If the collected data exists (YES in S1101), the product proposal unit 421 compares the collected data with the determination data/determination conditions and introduction conditions of the product chain list, and determines whether the proposed product exists ( S1102). If there is a proposed product (YES in S1102), the product proposal unit 421 proposes the proposed product to the customer by transmitting information on the proposed product to the customer terminal 10 (S1103).

Next, the merchandise proposal unit 421 determines whether or not a merchandise purchase instruction has been received from the customer terminal 10 operated by the customer within a predetermined period (S1104). If no instruction to purchase a product is received from the customer terminal 10 within a predetermined period (NO in S1104), that is, if no purchase is made, it is determined whether there is another proposed product (S1102).

When a product purchase instruction is received from the customer terminal 10 (YES in S1104), the product delivery instruction unit 425 outputs a product provision instruction (S1105). Here, if the proposed product is software that can be distributed via the network 80 , the product distribution instruction unit 425 outputs a distribution instruction for the proposed product to the product distribution server 50 . If the proposed product cannot be distributed via the network 80, such as when the proposed product is an apparatus, the product distribution instruction unit 425 outputs a product installation instruction. In this example, an inventory system (not shown) is instructed to ship the product.

Next, for example, a commercial product, which is software, is installed in the customer terminal 10 or the image processing device 20 of the customer usage environment 90, or a commercial product, which is a device, is installed in the customer usage environment 90. When the material starts operating, the collected data collection unit 417 receives collected data from the product (S1106). Then, the product proposal unit 421 determines whether the collected data collection unit 417 has received the collected data (S1107). Then, when the collected data collecting unit 417 determines that the collected data has been received (YES in S1107), the product proposal unit 421 analyzes the collected data (S1108). Then, the product proposal unit 421 executes effect report processing according to the analysis result (S1109, described later).

Next, when a plurality of products are introduced, the collected data control unit 423 confirms whether or not there is duplication in the collected data from each product (S1110). For example, if the value of the count by document is the same for product A and product B, then all of the collected data for product A is output to product B. The count by document is duplicated. In this case, it means that there is no need to count by product A.

Next, the collected data control unit 423 determines whether or not there is overlap in the collected data (S1111). If it is determined that there is overlap in the collected data (YES in S1111), the collected data control unit 423 collects duplicate collected data for any one of the plurality of products. It instructs to stop (S1112). Then, the product proposal unit 421 determines whether or not there is collected data (S1101).

Here, if the collected data does not exist (NO in S1101), the product proposal unit 421 creates a questionnaire (described later) and transmits it to the customer terminal 10 (S1113). Then, the merchandise proposal unit 421 determines whether or not a questionnaire response has been received (S1114). If it is determined that a questionnaire response has been received (YES in S1114), the product proposal unit 421 determines whether there is collected data (S1101).

If there is no proposed product (NO in S1102), the product proposal unit 421 terminates the product proposal process. If there is no overlap in the collected data (NO in S1111), the product proposal unit 421 determines whether there is collected data (S1101).

<Effect Report>
FIG. 12 is a diagram showing an effect report.
Next, the effect report will be described with reference to FIG.
As shown in FIG. 12, the effect report describes the changes in the collected data of the previous product in the chain list used for proposing a certain product before and after the introduction of the product. This effect report is displayed, for example, on the UI 25 (see FIG. 16, which will be described later).

In the illustrated example, the product before the chain list is the MFP, that is, the image processing device 20, and the corresponding product is product A. To explain further, in the effect report shown in FIG. 12, changes in collected data due to the introduction of product A are displayed (see display image R1). In the illustrated example, the number of print cost reduction pages (Page number) is displayed. Also, in the illustrated example, the collected data of the product A is displayed, and the usage status of the product A is displayed (see display image R2).

The illustrated effect report also includes an answer column for answering the customer's degree of satisfaction with the introduction of the product A, that is, the degree of satisfaction with the effect (see display image R3). The answer column shown in the figure accepts customer evaluations from evaluation 1 (high satisfaction) to evaluation 5 (low satisfaction) as a satisfaction survey of the introduction effect of the product A. FIG. This answer column can receive an answer from the customer by operating the UI 25 by the customer. When the customer inputs any evaluation from 1 to 5, it is sent as HTML mail, for example. The input satisfaction level is sent to the product proposal server 40, and the evaluation is notified to the salesperson and the provider. The questionnaire may be answered by mail. In this case, the customer checks the evaluation entry column of the degree of satisfaction with the effect in the questionnaire written on the paper medium, and returns it to the sales person, for example. Then, the salesperson scans and inputs the entered evaluation into the product proposal server 40, for example, so that the characters are recognized and the degree of satisfaction with the effect is input.

<Effective report processing>
FIG. 13 is a flow chart showing effect report processing by the product proposal unit 421 .
Next, an operation example of effect report processing will be described with reference to FIG.
First, the product proposal unit 421 compares and displays the collected data of the introduced product (the image processing device 20 in the illustrated example) (S1301). In addition, the product proposal unit 421 displays the collected data of the target product (product A in the illustrated example) (S1302). Here, as an example, changes in the number of jobs in the job log of the image processing apparatus 20 before and after introduction of product A are comparatively displayed, and the effect amounts for paper reduction and cost reduction are displayed. In addition, the product proposal unit 421 displays the input items for effect satisfaction ("1" to "5" in the illustrated example) (S1303).

Next, the product proposal unit 421 creates an effect report and transmits it to the image processing apparatus 20 (S1304). Then, when the product proposal unit 421 receives an effect satisfaction response from the image processing apparatus 20 (S1305), it transmits a notification of the effect satisfaction to the sales terminal 60 or the like (S1306). A salesperson who confirms the degree of satisfaction with the effect through the sales terminal 60 can conduct sales activities according to the degree of satisfaction with the effect, for example.

Note that the effect report may be transmitted to the customer terminal 10 and the sales terminal 60 in addition to the image processing device 20 or instead of the image processing device 20 . That is, effectiveness reports may be presented to customers and sales representatives.

<Questionnaire>
FIG. 14 is a diagram showing a questionnaire.
Next, referring to FIG. 14, the questionnaire sent by the product proposal server 40 to the customer terminal 10 will be described.

As shown in FIG. 14, the questionnaire is displayed on the customer terminal 10, for example. In the illustrated example, an image (see display image Q1) requesting an answer to a questionnaire regarding product D is displayed. In addition, the illustrated questionnaire includes an image (see display image Q2) of an answer column for the customer to answer questions (questionnaire items) regarding the merchandise D. FIG. This answer column can receive an answer from the customer by operating the customer terminal 10 by the customer. When the customer enters a check mark in the answer column included in the display image Q2, the email is sent to the product proposal server 40 as HTML mail, for example.

Now, a questionnaire for a target customer who has not yet introduced any product is created as follows. That is, the product proposal unit 421 lists items of judgment conditions for products that can be proposed to the target customer, and the product is created according to the items. In other words, a questionnaire is created according to the judgment conditions of the merchandise. Here, in the product information list shown in FIG. 8(b), there are a plurality of conditions for one product as "judgment conditions" for introducing each product. Therefore, as the questionnaire items, there may be questionnaire items for each judgment condition. That is, the number of judgment conditions for one product may be the same as the number of questionnaire items included in the questionnaire for that product.

Further, the questionnaire is sent to the customer terminal 10 by e-mail or the like, but after being sent to the sales terminal 60, it may be sent to the customer by e-mail or mail via the sales representative. Also, instead of the questionnaire itself, a URL or the like indicating the WEB page of the questionnaire may be sent to the customer terminal 10 by e-mail. The customer may respond to the questionnaire by accessing the URL described in this e-mail. Also, the customer's response may be obtained by scanning the questionnaire results (answers) received by the sales representative from the customer in the form of paper media or electronic data. Further, the product proposal unit 421 may receive the customer's answer by the salesperson inputting information obtained by the salesperson through interviews with the customer.

In addition, in the above description, it is explained that the questionnaire is displayed on the customer terminal 10, but the present invention is not limited to this. For example, the information regarding the questionnaire may be displayed on the sales terminal 60, or the information regarding the questionnaire may be displayed on another device such as the image processing device 20. FIG.

<Product proposal image>
FIG. 15 is a diagram showing a product proposal image.
Next, a product proposal image that the product proposal server 40 causes the sales terminal 60 to output will be described with reference to FIG. 15 .

Proposing a product to a customer is not limited to sending an e-mail to the customer terminal 10 or the like as described above, as long as information on the product is notified. For example, an image as shown in FIG. 15 may be displayed on the sales terminal 60. FIG.

Here, in the example shown in FIG. 15, an image displaying the next proposing product to the customer (see display image Q3), an image showing the reason for proposing the product (see display image Q4), a sales representative An instruction image (see instruction image Q5) for displaying items (to-do) that a person should do when interviewing a customer (see instruction image Q5), for example, an instruction image for outputting (printing) a proposal including a check sheet to be filled out by the customer (see instruction image Q6) etc. is displayed.

In addition, in the display image Q3, "merchandise F" is displayed as a proposed merchandise. Also, in the display image Q4, a plurality of reasons for proposing the product are displayed. To explain further, in the illustrated example, out of "many settlement documents", "many remands", "occurrence of approval delay", and "overtime in settlement work", "many settlement documents" and "many remands" , and “Occurrence of delay in approval” are displayed with a check image, and no check image is displayed in the item of “Overtime work for settlement work”. It shows that "merchandise F" is determined to be a proposed merchandise due to the reasons of "many settlement documents", "many times of remand", and "occurrence of approval delay" for which check images are displayed. In this way, by displaying the reason why the proposed product is determined to be the proposed product, the proposal of the proposed product can be persuasive.

In addition, "many settlement documents", "many times of rejection", and "occurrence of delay in approval" can be regarded as problems that have not been solved with products that have already been introduced to customers (introduced products). . In addition, "overtime work for settlement work" can be regarded as a condition that has not been satisfied among the conditions for judging "merchandise F" as a proposed merchandise. To explain further, the display image Q4 can be regarded as an image showing how the conditions for judging that the "merchandise F" is the proposed merchandise are satisfied.

<Hardware Configuration of Image Processing Device 20>
FIG. 16 is a diagram showing a hardware configuration example of the image processing apparatus 20. As shown in FIG.
As shown in FIG. 16, the image processing apparatus 20 includes a CPU 21, a RAM 22, a ROM 23, an HDD 24, a user interface (UI) 25, an image reading section 26, a printing section 27, and a communication I/F 28. Prepare.

The CPU 21 implements each function of the image processing apparatus 20 by loading various programs stored in the ROM 23 or the like into the RAM 22 and executing them.
The RAM 22 is a memory used as a work memory for the CPU 21 and the like.
The ROM 23 is a memory that stores various programs executed by the CPU 21 .
The HDD 24 stores image data (scanner data) read by the image reading unit 26, image data (print data) used for image formation by the printing unit 27, plug-ins as commercial materials received from the commercial material distribution server 50, and the like. For example, it is a magnetic disk device that stores the .
The UI 25 is, for example, a touch panel that displays various types of information and accepts operation input from the user.

The image reading section 26 reads an image recorded on a document. Here, the image reading unit 26 is, for example, a scanner, and may employ a CCD method in which light emitted from a light source onto an original is reduced by a lens and received by a CCD (Charge Coupled Devices), or an LED light source may emit light onto the original. A CIS system that irradiates and receives reflected light with a CIS (Contact Image Sensor) can be used.

The printing unit 27 forms an image on paper. The printing unit 27 is, for example, a printer, and uses an electrophotographic system that forms an image by transferring toner adhered to a photoreceptor onto a sheet of paper, or an inkjet system that forms an image by ejecting ink onto a sheet of paper. be able to.
Communication I/F 28 transmits and receives various information to and from other devices via network 80 (see FIG. 1). The illustrated communication I/F 28 is capable of wireless communication such as BLE (Bluetooth (registered trademark) Low Energy) communication with other devices.

Here, the program executed by the CPU 21 is stored in a computer-readable recording medium such as a magnetic recording medium (magnetic tape, magnetic disk, etc.), an optical recording medium (optical disk, etc.), a magneto-optical recording medium, or a semiconductor memory. provided to the image processing apparatus 20 in the state. Also, the program executed by the CPU 21 may be transmitted to the image processing device 20 from a server (for example, the product proposal server 40) on the network 80, for example.

<Functional Configuration of Image Processing Apparatus 20>
FIG. 17 is a diagram showing the functional configuration of the image processing device 20. As shown in FIG.
Next, the functional configuration of the image processing device 20 will be described with reference to FIGS. 16 and 17. FIG.
As shown in FIG. 17, the image processing apparatus 20 includes a UI control unit 201, a job control unit 203, an image processing unit 205, a FAX communication unit 207, a printer unit 209, a scanner unit 211, and a network communication unit. 213 , a system control unit 215 , a log management unit 217 , an OCR unit 219 , a collected data control unit 221 , and a plug-in management unit 223 . Each functional configuration constituting the image processing apparatus 20 will be described below.

The UI control unit 201 displays the image processing apparatus 20, job status, function buttons, etc. on the UI 25, and receives operations/inputs from the user (customer).
A job control unit 203 controls start/stop/completion of jobs (copy/print/scan/FAX) executed by the image processing apparatus 20 .
The image processing unit 205 cooperates with the FAX communication unit 207, the printer unit 209, the scanner unit 211, and the network communication unit 213 to realize copy/print/scan/FAX functions.

A FAX communication unit 207 controls the image reading unit 26, the printing unit 27, and the communication I/F 28, and performs FAX communication of image data with another FAX device.
A printer unit 209 controls the printing unit 27 and performs printing necessary for copying/printing.
The scanner unit 211 controls the image reading unit 26 to scan and read a document.
A network communication unit 213 controls the communication I/F 28 and performs reception of plug-ins, transmission of business analysis data, network communication of image data, and the like.

A system control unit 215 controls the entire image processing apparatus 20 .
The log management unit 217 records and manages job logs executed by the image processing apparatus 20 and image logs of documents processed by the image processing apparatus 20 .
The OCR unit 219 performs OCR processing on image logs in addition to OCR processing on documents.

The collected data control unit 221 collects collected data and uploads the data to the product proposal server 40 in a predetermined form (for example, data structure). Here, if the product is the image processing apparatus 20 , the collected data control unit 221 sends the job log and the document count as collected data to the product proposal server 40 . Specifically, the collected data control unit 221 sends, as collected data, a document-by-document count value obtained by analyzing and classifying the job log and the image log recorded in the log management unit 217 by the OCR unit 219 . Further, when instructed to stop collecting the collected data from the product proposal server 40, the collected data control unit 221 stops collecting the instructed collected data. Further, after stopping, if the product proposal server 40 instructs to resume due to reasons such as being unable to acquire the collected data for other products, the collected data control unit 221 restarts the stopped collection of the collected data. do.

The plug-in management unit 223 controls registration, deletion, and execution of plug-ins as products received from the product distribution server 50 . Here, the plug-in is a separate program from the firmware that implements the copy/print/scan/FAX functions, which are the basic functions of the image processing apparatus 20, and is written in Java (registered trademark) language, for example. program. The plugin management unit 223 also includes a platform (PF) for operating plugins. The plug-in management unit 223, for example, JavaVM (Java Virtual Machine) is a platform that operates a plug-in written in the Java language.

<Functional configuration of plug-in management unit 223>
FIG. 18 is a diagram showing the functional configuration of the plug-in manager 223. As shown in FIG.
Next, the functional configuration of the plug-in manager 223 will be described with reference to FIG. 18 .

As shown in FIG. 18, the plugin management unit 223 has a job log collection plugin 241 , a document information collection plugin 243 , a BLE information collection plugin 245 and an MFP plugin 247 . Each functional configuration constituting the plug-in management unit 223 will be described below.

The job log collection plug-in 241 collects job logs of jobs executed by the image processing apparatus 20 . The document information collection plug-in 243 collects document-by-document counts of jobs executed by the image processing apparatus 20 . The BLE information collection plug-in 245 collects information on BLE communication executed by the image processing device 20 . MFP plug-in 247 collects information from each of job log collection plug-in 241 , document information collection plug-in 243 , and BLE information collection plug-in 245 , and transfers the information to product proposal server 40 via network communication unit 213 . . Note that these job log collection plug-in 241 , document information collection plug-in 243 , BLE information collection plug-in 245 , and MFP plug-in 247 can each be regarded as products introduced into the image processing apparatus 20 .

As described above, the image processing apparatus 20 has a plurality of collection plug-ins (the job log collection plug-in 241, the document information collection plug-in 243, and the BLE information collection plug-in 245). These collection plug-ins can be regarded as measurement points for each product. Data collected by these measuring points (collected data) is transferred to the product proposal server 40 via a transfer plug-in (MFP plug-in 247).

Although the MFP plug-in 247 transfers collected data to the product proposal server 40 here, the present invention is not limited to this. For example, the MFP plug-in 247 may transfer collected data to other products installed in the image processing apparatus 20 . In other words, the data collected by the low-order product may be sent to the high-order product via the transfer plug-in. Then, this superior product may transfer the collected data to the product proposal server 40 .

<Stop collecting collected data>
Here, processing for stopping collection of collected data will be described.
The collected data control unit 423 of the product proposal server 40 stops collecting the collected data, for example, when there is no proposed product to be proposed next or when the determination conditions cannot be obtained. Specifically, the collected data control unit 423 outputs an instruction to stop collecting the collected data to the collected data control unit 221 of the image processing apparatus 20 . Upon receipt of the instruction, the collected data control unit 221 stops collecting collected data from the product.

Further, even when collected data is collected redundantly, the collected data control unit 423 performs a process of stopping collection of collected data. For example, if the document-specific counters are collected redundantly for product A and product B, the collection of the document-specific counters for one product (product A) is stopped, and the other product (product B) is collected. Collect the counter for each document in .

Here, after the collection of one product is stopped, the other product may be canceled, and the collected data cannot be collected from the other product after the fact. In this case, the collected data control unit 423 restarts the collection of collected data from the suspended product (product A in the above example). This avoids the continuation of the state in which the collected data cannot be collected.

In addition, in the above example, even if an abnormality is detected in the collected data for the product B, the collected data control unit 423 resumes the collection of the document-by-document counter for the product A, which had been stopped. For example, if the number of converted documents for product A and the total sum of the counters for each document for product B do not match after stopping collection of counters for each document for product A, converted documents for product A It may be output to a route other than B. Therefore, even when such a situation is detected, the stopped data collection of the document counter for the product A is resumed.

Next, the handling of the collected data when the collected data collected by each of the upper-level product and the lower-level product overlaps will be described. If the collected data overlaps between the upper-level product and its lower-level product, one of the collected data may not be used, that is, some of the collected data may be excluded or discarded. For example, the collected data collected from the upper and lower products in the image processing device 20 are both transmitted to the product proposal server 40, and the collected data control unit 423 of the product proposal server 40 selects any of the collected data. may be excluded. Alternatively, the collected data control unit 423 of the product proposal server 40 may stop the collection of collected data for either the higher-order product or the lower-order product.

Further, duplication of collected data may be eliminated in the image processing device 20 instead of the product proposal server 40 . For example, in the image processing apparatus 20, when the collected data collected by each of the upper-ranking product and its lower-ranking product overlaps, the higher-ranking product excludes the collected data received from the lower-ranking product, and the upper-ranking product collects the collected data. Only collected data may be transmitted to the product proposal server 40 . In addition, the upper-level product may stop the collection of the collected data in the lower-level product.

It should be noted that whether or not to collect collected data may be set in advance for each of the high-ranking product and the low-ranking product. To explain further, the collected data control unit 221 of the image processing apparatus 20 or the collected data control unit 423 of the product proposal server 40 has storage means for storing whether or not to collect the collected data for each product. may Further, the image processing device 20 or the product proposal server 40 may store the collected data in association with the attributes of the product such as the type of the product from which the collected data is collected. As a result, it becomes possible to check the merchandise data after the fact.

<Judgment value>
FIG. 19A is a diagram showing an example of calculation of a judgment value, and FIG. 19B is a diagram showing an example of weighting points.
An example of determining the proposed product using the judgment value will be described with reference to FIGS. 19(a) and (b).
In the above embodiment, it has been described that the proposed merchandise is determined when any one of the judgment conditions is satisfied when determining the proposed merchandise, but the present invention is not limited to this. For example, the decision to determine the proposed product may be made based on a plurality of decision conditions. For example, a suggested product may be determined when some or all of a plurality of judgment conditions are satisfied.

Moreover, while weighting the judgment conditions, the product may be determined by adding up a plurality of judgment conditions (for example, total points). For example, as shown in FIG. 19A, the "weight" of "JobLog" with "judgment ID" of "1" is set to "60%", and the "count by document" with "judgment ID" of "2". ' is set to '40%'. In this example, when the collected data shown in FIG. 19B is collected, the judgment value is 0.98. Then, when the threshold value of the judgment value for proposing is 0.8, the judgment value is 0.98, which exceeds the threshold value, so it is judged that the product can be proposed.

<Determination of Proposed Product by Image Processing Apparatus 20>
In the above description, the product proposal server 40 acquires collected data from the products introduced into the image processing apparatus 20, and the product proposal server 40 determines the proposed product based on the collected data. Not limited. For example, the proposed product may be determined on the customer usage environment 90 side, such as the customer terminal 10 or the image processing device 20 .

For further explanation, it is assumed that the product X has been introduced into the image processing apparatus 20, for example. Then, the image processing device 20 or the like may acquire from the product proposal server 40 information about a product that can be introduced next to the product X, and information regarding the criteria for introducing the product that can be introduced. Based on the data acquired from the product proposal server 40, the image processing device 20 or the like may determine the proposed product and display it on the UI 25 of the image processing device 20 or the like.

<Other Modifications>
Now, normally, if the introduction condition is not satisfied, such as when the product that is the introduction condition is not introduced, the customer cannot introduce the product even if the product is proposed. However, if you also propose the introduction of the product that is the introduction condition, it will be possible to make a proposal. Therefore, if the introductory conditions are not satisfied, you may also propose products that meet the introductory conditions. Here, for example, weighting may be performed based on the possibility of introduction of equipment (price, installation space, etc.), which is an introduction condition. To explain further, the weight may be 1.0 if the introduction condition is satisfied, 0.8 if the introduction barrier is low and can be proposed, and 0 if the introduction barrier is high and the introduction is impossible.

Also, when there are a plurality of product candidates, the number of items that satisfy the judgment condition or the ratio of the number of items that satisfy the criteria (matching degree) is high. That is, according to the priority (order of priority) of each of a plurality of products, a plurality of products may be proposed, or only a product that satisfies one item with a high priority may be proposed. This difference in processing is controlled by the Proposal Mode (not shown) setting set by the sales representative for each customer.

In addition, as a judgment process, the judgment conditions are weighted as described above, and when judgment is made by summing multiple judgment conditions, multiple proposal products are proposed, such as the product with the higher total value. can be similarly controlled. Also, when the introduction conditions are weighted, the priority of the proposal is determined by the product of the points of the judgment conditions and the points of the introduction conditions.
Furthermore, if the customer has a budget, the budget may be included in the judgment conditions. That is, the proposed merchandise may be determined based on the judgment conditions including the customer's budget.

As mentioned above, some products are given priority over others, that is, by proposing products that are highly compatible with the solution of the customer's business problem, the efficiency of product proposals is improved. and reduce the risk that the product will lead to cancellation.

In the above description, the cloud server 30, the product proposal server 40, and the product distribution server 50 are described as separate servers. may be executed by a common server.

By the way, "merchandise data" includes, for example, data collected by merchandise introduced into the information processing apparatus. The product itself is equipped with information gathering means, the product has a function of collecting its own data by the information gathering means, and the data collected by the information gathering means possessed by the product is Material data may be used. In addition, the information collection means is provided not in the product itself but in the information processing device into which the product is introduced, and the information collection means of the information processing device is used to collect information from the product introduced in the information processing device. The collected data may be used as merchandise data. Also, the product data may be data relating to how the product is used. The product data is, for example, data such as who uses the product and what functions are used. In addition, from all kinds of data related to how the product is used, it is possible to select the collection target and collect only the data necessary to judge whether the proposal conditions are satisfied, or to collect information indicating the product itself (for example, Product number, product name) may not be treated as product data and may not be collected because they are not necessary for judging proposal conditions.

Also, the collected data collection unit 417 in the above description is an example of data acquisition means. The product information management unit 413 is an example of condition acquisition means. The merchandise proposal unit 421 is an example of output means. The product proposal server 40 is an example of an information processing device. A judgment condition is an example of a proposal condition, a conditional element, and a first conditional element. The introduction condition is an example of a second conditional element. The display image Q3 is an example of proposal information.

Although various embodiments and modifications have been described above, it is of course possible to combine these embodiments and modifications.
In addition, the present disclosure is not limited to the above embodiments, and can be embodied in various forms without departing from the gist of the present disclosure.

DESCRIPTION OF SYMBOLS 1... Business improvement system 10... Customer terminal 20... Image processing apparatus 40... Merchandise providing server 221... Collected data control part 223... Plug-in management part 421... Merchandise proposal part

Claims (13)

data acquisition means for acquiring product data that is data of products that have already been introduced to a customer;
condition acquisition means for acquiring proposal conditions, which are conditions individually determined for each of a plurality of other commercial products that are different from the introduced commercial products;
When the merchandise data acquired by the data acquisition means satisfies any of the proposal conditions, the other merchandise corresponding to the satisfied proposal conditions is a merchandise to be introduced to the customer. and output means for outputting proposal information that is information indicating the information processing apparatus. The proposed condition has a plurality of condition elements,
2. The information processing apparatus according to claim 1, wherein said output means outputs said proposal information when a predetermined number of conditional elements among said plurality of conditional elements are satisfied. The data acquisition means acquires the merchandise data from the introduced merchandise,
3. The information processing apparatus according to claim 2, wherein said output means outputs said proposal information when said product data acquired by said data acquisition means satisfies a predetermined number of condition elements among said plurality of condition elements. . 2. The information processing apparatus according to claim 1, wherein said output means outputs said proposal information together with a reason for proposing the product of said proposal information. The data acquisition means acquires the merchandise data from the introduced merchandise,
The proposed condition has a plurality of condition elements,
3. When the product data acquired by the data acquisition means satisfies a predetermined number of conditional elements among the plurality of conditional elements, the output means outputs a degree of satisfaction of the plurality of conditional elements. 5. The information processing device according to 4. 6. The information processing apparatus according to claim 5, wherein said output means outputs information indicating a conditional element judged not to be satisfied by said product data from said introduced product among said plurality of conditional elements. The data acquisition means acquires the merchandise data from the introduced merchandise,
The proposed condition has a plurality of conditional elements with respective priorities,
7. The information according to any one of claims 1 to 6, wherein the output means determines whether or not the product data acquired by the data acquisition means satisfies each of the plurality of conditional elements according to the priority order. processing equipment. The proposed conditions include a first conditional element related to how the introduced product is used and a second conditional element related to requirements for operating the other product,
The information processing apparatus according to any one of claims 1 to 7, wherein said output means outputs said proposal information when both said first conditional element and said second conditional element are satisfied. 3. The output means outputs information for inquiring whether the customer satisfies the second conditional element when it cannot be determined from the product data whether the second conditional element is satisfied or not. 9. The information processing device according to 8. The output means, when the proposal condition for one product out of the plurality of other products is not satisfied, sets the proposal condition for products other than the one product out of the plurality of other products. 10. The information processing apparatus according to any one of claims 1 to 9, wherein it is determined whether the condition is satisfied. 11. The output means according to any one of claims 1 to 10, wherein, when there are a plurality of products satisfying the proposal conditions among the plurality of other products, the output means outputs information indicating all of the products satisfying the proposal conditions. The information processing device according to item 1. a step of acquiring product data, which is data of products that have already been introduced to a customer;
a step of acquiring proposal conditions, which are conditions individually determined for each of a plurality of other commercial products that are different from the introduced commercial products;
Proposal information, which is information indicating that, when the product data satisfies any of the proposal conditions, the other product corresponding to the satisfied proposal condition is a product to be introduced to the customer. and a step of outputting an information processing method. A function to acquire product data, which is the data of products that have already been introduced to customers,
A function of acquiring proposal conditions, which are conditions individually determined for each of a plurality of other commercial products that are different from the introduced commercial products;
Proposal information, which is information indicating that, when the product data satisfies any of the proposal conditions, the other product corresponding to the satisfied proposal condition is a product to be introduced to the customer. A program for realizing a function to output and a computer.

Images