JP2020064336A - Information processing system, information processing apparatus, information processing method and program - Google Patents

Abstract

To optimize a sales activity of a person in charge.SOLUTION: An apparatus includes: a similarity determination unit that determines a similarity of a submission with a target person in charge for another person in charge using a frequency for a plurality of keywords included in the submission regarding a sales activity for a specific product within a setting period time by the target person in charge and a frequency for a plurality of keywords included in the submission regarding the sales activity for the specific product within a setting period time by the other person in charge; a similar person in charge extraction unit that extracts at least one or more similar persons in charge; a key driver extraction unit that extracts one or more keywords as a key driver of the specific product from the keywords included in the submission of the similar person in charge using an appearance frequency of the keyword included in the submission of the similar person in charge and a similarity to the person in charge for the similar person in charge; and an aggregation unit that aggregates the frequencies of the key driver of the specific product extracted for aggregation unit period time regarding each of the plurality of persons in charge belonging to a group.SELECTED DRAWING: Figure 20

Description

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

  Conventionally, a search method that can search more appropriate information for various activities such as sales activities has been proposed. For example, in Patent Document 1, an activity report is acquired, and the activity contents included in the acquired activity report are compared with a series of activity contents in a plurality of activity reports held as one activity report in the activity report holding means. And an activity report retrieval device including an activity report extraction means for extracting an activity report similar to the activity report acquired by the activity report acquisition means, and a display means for displaying the activity report extracted by the activity report extraction means. ing.

JP, 2007-226677, A

  However, in the technique of Patent Document 1, when the sales level of the target person in charge (for example, the person in charge of sales of pharmaceuticals) is low, the sales method described in the sales report of another sales person having a high sales level. May be too advanced to understand (or chew sufficiently). In addition, if the skill of the person in charge of sales of pharmaceuticals is low, it is necessary to comply with other standards, including compliance with the “Pharmaceuticals and Medical Devices Act” and “Adequate Advertising Standards for Pharmaceuticals (Guidelines for Sales Information Provision of Prescription Drugs)” There is a problem that it is difficult to actually apply the advanced sales method described in the sales report of a highly skilled sales person to sales.

  In addition, for example, when displaying information related to sales activities of a specific product to multiple persons in charge, the more persons in charge, the more managerial personnel check whether the displayed information is appropriate for management purposes. Difficult to do. In addition, for example, how much information about sales activities of a specific product for managerial staff, etc. relative to the number showing the sales result (for example, the number of orders, the number of hires or sales, the number of prescriptions of drugs, etc.) It is difficult to know if there is an impact. In addition, for example, it is desirable that the person in charge conducts sales activities properly, including compliance with the "Pharmaceuticals and Medical Devices Act" and "Adequate Advertising Standards for Drugs (Guidelines for Sales Information Provision of Prescription Drugs)" .

  The present invention has been made in view of the above problems, and an object of the present invention is to provide an information processing system, an information processing device, an information processing method, and a program capable of further optimizing sales activities of a person in charge. To do.

  The information processing system according to the first aspect of the present invention is the frequency of each of a plurality of keywords included in a post related to a sales activity targeting a specific product by a person in charge in a set period, and the frequency by another person in charge. By using the frequency of each of a plurality of keywords included in posts related to sales activities targeting the specific product in the set period, the similarity of the post with the target person in charge is determined for each other person in charge. A similarity determining unit, a similar person extracting unit that extracts at least one similar person based on the similarity, and an appearance frequency of each keyword included in the post of the extracted similar person Using each of the keywords and the degree of similarity between the similar person in charge and the target person in charge, at least one or more key words are selected from each keyword included in the post of the similar person in charge. A key driver extraction unit for extracting as a key driver of the specific product, and for a plurality of persons in charge belonging to the group, the frequency of the key driver of the specific product extracted for each total unit period for each person in charge And an aggregator.

  According to this configuration, since the key drivers of the specific products provided to the person in charge are aggregated, it is possible to determine whether the key driver is appropriate with a small amount of effort, and it is possible to judge in group units. By systematically grasping the key driver as an activity trigger, it is possible to help optimize the sales activity of each person in charge for the particular product. Further, it is possible to grasp the important key driver by analyzing the degree of influence on the number showing the business result by using the frequency of the key driver for each group. As a result, the important key driver can be made known to each person in charge, so that the business activities of each person in charge can be made more appropriate.

  An information processing system according to a second aspect of the present invention is the information processing system according to the first aspect, further including an output unit that outputs information for displaying a result of the counting by the counting unit.

  According to this configuration, the frequency of the entire group of key drivers can be grasped in time series. As a result, it is possible to determine whether the key driver is appropriate for each group with a small amount of labor. Furthermore, by systematically grasping the key driver as the activity trigger of each individual person in charge, it can be linked to the trajectory correction of the approach of the item arranged as an organization, and from the trend trend of the key driver conspicuous for the particular product, The emergence of unexpected key drivers is gaining insight.

  An information processing system according to a third aspect of the present invention is the information processing system according to the first aspect, and describes the frequency of each of the key drivers obtained as a result of the aggregation by the aggregating unit for each aggregation unit period. A variable, an analysis execution unit that executes a multiple regression analysis with the number representing the sales performance of each specific unit for each aggregation unit period as an objective variable, and information for displaying the result of the execution by the analysis execution unit. And an output unit for outputting.

  According to this configuration, the degree of influence of each key driver on the number representing the business result can be grasped as the tendency of the group.

  An information processing system according to a fourth aspect of the present invention is the frequency for each of a plurality of keywords included in a post related to sales activities targeting a specific product by a person in charge for a set period, and the frequency by another person in charge. By using the frequency of each of a plurality of keywords included in posts related to sales activities targeting the specific product in the set period, the similarity of the post with the target person in charge is determined for each other person in charge. A similarity determining unit, a similar person extracting unit that extracts at least one similar person based on the similarity, and an appearance frequency of each keyword included in the post of the extracted similar person Using each of the keywords and the degree of similarity between the similar person in charge and the target person in charge, at least one or more key words are selected from each keyword included in the post of the similar person in charge. The includes a key driver extraction unit that extracts as the specific product key driver, and an output unit for outputting information for displaying the extracted key driver.

  With this configuration, the key driver can be presented to the person in charge. The key driver corresponding to the sales level of the target person in charge is extracted, and the extracted key driver changes gradually as the sales level rises. Since it is possible to improve the possibility of fully understanding the key driver, which is a keyword, and the possibility of utilizing it, it is possible to further optimize the sales activities of the person in charge.

  An information processing system according to a fifth aspect of the present invention is the information processing system according to the fourth aspect, wherein the output unit is attached to the specific product together with the extracted key driver (for example, “pharmaceutical product”). Output the information for making it possible to refer to the most basic and important official documents based on the "Medical Devices Act" and "Guidelines for Sales Information Provision of Prescription Drugs".

  According to this configuration, the attached document of the specific product can be presented to the target person in charge, so that knowledge of the specific product can be easily obtained while optimizing the sales activities.

  An information processing system according to a sixth aspect of the present invention is the information processing system according to the fourth or fifth aspect, wherein the information for identifying the specific product and the attached document of the specific product are stored in association with each other. The storage unit is further provided, and the output unit outputs information for displaying the attached document of the specific product according to the operation by the person in charge of the target.

  According to this configuration, the attached document of the specific product can be presented to the target person in charge, so that knowledge of the specific product can be easily obtained while optimizing the sales activities.

  An information processing apparatus according to a seventh aspect of the present invention is the frequency of each of a plurality of keywords included in a post regarding sales activities targeting a specific product in a set period by a target person in charge, and the frequency by another person in charge. By using the frequency of each of a plurality of keywords included in posts related to sales activities targeting the specific product in the set period, the similarity of the post with the target person in charge is determined for each other person in charge. A similarity determining unit, a similar person extracting unit that extracts at least one similar person based on the similarity, and an appearance frequency of each keyword included in the post of the extracted similar person At least one or more keywords are selected from each of the keywords included in the post of the similar person by using each and the degree of similarity with the person in charge of the similar person in charge. A key driver extraction unit that extracts as a key driver of a specific product, and a plurality of persons in charge who belong to the group, and an aggregate that aggregates the frequency of the key driver of the specific item extracted for each aggregated unit period for each person in charge And a section.

  According to this configuration, since the key drivers of the specific products provided to the person in charge are aggregated, it is possible to determine whether the key driver is appropriate with a small amount of effort, and it is possible to judge in group units. By systematically grasping the key driver as an activity trigger, it is possible to help optimize the sales activity of each person in charge for the particular product. Further, it is possible to grasp the important key driver by analyzing the degree of influence on the number showing the business result by using the frequency of the key driver for each group. Thereby, the key driver often used in sales and the important key driver can be made known to each person in charge, so that the sales activity of each person in charge can be further optimized.

  An information processing apparatus according to an eighth aspect of the present invention is the frequency for each of a plurality of keywords included in a post related to a sales activity targeting a specific product by a person in charge of a target, and the frequency of the other person in charge. By using the frequency of each of a plurality of keywords included in posts related to sales activities targeting the specific product in the set period, the similarity of the post with the target person in charge is determined for each other person in charge. A similarity determining unit, a similar person extracting unit that extracts at least one similar person based on the similarity, and an appearance frequency of each keyword included in the post of the extracted similar person At least one or more keywords are selected from each of the keywords included in the post of the similar person by using each and the degree of similarity with the person in charge of the similar person in charge. Serial includes a key driver extraction unit that extracts a particular product key driver, and an output unit for outputting information for displaying the extracted key driver.

  With this configuration, the key driver can be presented to the person in charge. The key driver corresponding to the sales level of the target person in charge is extracted, and the extracted key driver changes gradually as the sales level rises. Since it is possible to improve the possibility of fully understanding the key driver, which is a keyword, and the possibility of utilizing it, it is possible to further optimize the sales activities of the person in charge.

  In the information processing method according to the ninth aspect of the present invention, the similarity determination unit includes a frequency for each of a plurality of keywords included in a post regarding sales activities targeting a specific product by a person in charge in a set period, By using the frequency of each of a plurality of keywords included in a post related to the sales activity targeting the specific product by the other person in charge in the setting period, the person in charge of the person in question concerned with the person in charge of the other person concerned. The step of determining the similarity of posts, the step of the similar person extracting unit extracting at least one similar person based on the degree of similarity, and the key driver extracting unit of the extracted similar person Of each of the keywords included in the post and the similarity of the person in charge of the similar person in question to each key included in the post of the similar person. A step of extracting at least one or more keywords from the word as a key driver of the specific product; and a totalizing unit, for a plurality of persons in charge who belong to a group, the specific number extracted for each total period for each person in charge. Collecting the frequency of the key driver of the product.

  According to this configuration, since the key drivers of the specific products provided to the person in charge are aggregated, it is possible to determine whether the key driver is appropriate with a small amount of effort, and it is possible to judge in group units. By systematically grasping the key driver as an activity trigger, it is possible to help optimize the sales activity of each person in charge for the particular product. Further, it is possible to grasp the important key driver by analyzing the degree of influence on the number showing the business result by using the frequency of the key driver for each group. Thereby, the key driver often used in sales and the important key driver can be made known to each person in charge, so that the sales activity of each person in charge can be further optimized.

  In the information processing method according to the tenth aspect of the present invention, the similarity determining unit sets a frequency for each of a plurality of keywords included in a post regarding a sales activity targeting a specific product by a person in charge in a setting period, By using the frequency of each of a plurality of keywords included in a post related to the sales activity targeting the specific product by the other person in charge in the setting period, the person in charge of the person in question concerned with the person in charge of the other person concerned. The step of determining the similarity of posts, the step of the similar person extracting unit extracting at least one similar person based on the degree of similarity, and the key driver extracting unit of the extracted similar person Each of the appearance frequencies of the keywords included in the post and each of the degrees of similarity between the target person in charge of the similar person and each of the items included in the post of the similar person From keyword has extracting at least one of the keywords as the specific product key driver, the output unit, and a step of outputting information for displaying the extracted key driver.

  With this configuration, the key driver can be presented to the person in charge. The key driver corresponding to the sales level of the target person in charge is extracted, and the extracted key driver changes gradually as the sales level rises. Since it is possible to improve the possibility of fully understanding the key driver, which is a keyword, and the possibility of utilizing it, it is possible to further optimize the sales activities of the person in charge.

  A program according to an eleventh aspect of the present invention causes a computer to set a frequency for each of a plurality of keywords included in a post regarding a sales activity targeting a specific product by a person in charge of a target, and a frequency by another person in charge. By using the frequency of each of a plurality of keywords included in posts related to sales activities targeting the specific product in the setting period, the similarity of the post with the target person in charge is calculated for each other person in charge. A similarity determination unit to determine, a similar person extraction unit to extract at least one similar person based on the similarity, and the appearance of each keyword included in the post of the extracted similar person At least one or more is selected from each keyword included in the post of the similar person using each frequency and each similarity degree with the target person in charge of the similar person. For a plurality of persons in charge who belong to the group, a key driver extraction unit that extracts the keyword of the key driver as the key driver of the particular item, and the frequency of the key driver of the particular item that is extracted for each total unit period for each person in charge. It is a program for functioning as a counting unit that counts.

  According to this configuration, since the key drivers of the specific products provided to the person in charge are aggregated, it is possible to determine whether the key driver is appropriate with a small amount of effort, and it is possible to judge in group units. By systematically grasping the key driver as an activity trigger, it is possible to help optimize the sales activity of each person in charge for the particular product. Further, it is possible to grasp the important key driver by analyzing the degree of influence on the number showing the business result by using the frequency of the key driver for each group. Thereby, the key driver often used in sales and the important key driver can be made known to each person in charge, so that the sales activity of each person in charge can be further optimized.

  A program according to a twelfth aspect of the present invention causes a computer to set a frequency for each of a plurality of keywords included in a post related to a sales activity targeting a specific product by a person in charge of a target and a frequency by another person in charge. By using the frequency of each of a plurality of keywords included in posts related to sales activities targeting the specific product in the setting period, the similarity of the post with the target person in charge is calculated for each other person in charge. A similarity determination unit to determine, a similar person extraction unit to extract at least one similar person based on the similarity, and the appearance of each keyword included in the post of the extracted similar person At least one or more is selected from each keyword included in the post of the similar person using each frequency and each similarity degree with the target person in charge of the similar person. A key driver extractor for the keywords extracted as the specific product key driver is a program to function as an output unit, which outputs information for displaying the extracted key driver.

  With this configuration, the key driver can be presented to the person in charge. The key driver corresponding to the sales level of the target person in charge is extracted, and the extracted key driver changes gradually as the sales level rises. Since it is possible to improve the possibility of fully understanding the key driver, which is a keyword, and the possibility of utilizing it, it is possible to further optimize the sales activities of the person in charge.

According to one aspect of the present invention, since the key drivers of a specific product to be provided to a person in charge are aggregated, it is possible to determine whether a key driver is appropriate with a small amount of effort, and it is possible to determine whether the key driver is appropriate. By systematically grasping the key driver as the activity trigger of the person in charge, it is possible to help optimize the sales activity of each person in charge for the particular product. Further, it is possible to grasp the important key driver by analyzing the degree of influence on the number showing the business result by using the frequency of the key driver for each group. As a result, the key driver often used in sales and the important key driver can be made known to each person in charge, so that the sales activity of each person in charge can be further optimized.
According to another aspect of the present invention, the key driver can be presented to the person in charge. The key driver corresponding to the sales level of the target person in charge is extracted, and the extracted key driver changes gradually as the sales level rises. Since it is possible to improve the possibility of fully understanding the key driver, which is a keyword, and the possibility of utilizing it, it is possible to further optimize the sales activities of the person in charge.
According to still another aspect of the present invention, for example, a package insert conforming to the “Pharmaceuticals and Medical Devices Act” and “Adequate Advertising Standards for Drugs (Guidelines for Sales Information Provision of Prescription Drugs)” established by the government By being able to refer to it, it also aims to optimize business activities.

It is a schematic block diagram which shows the structure of the information processing system S which concerns on this embodiment. It is a schematic block diagram which shows the structure of the information processing apparatus 1 which concerns on this embodiment. It is an example of a drug master table. It is an example of a pharmaceutical company master table. It is an example of a supplementary matter table. It is an example of a person in charge master table. It is an example of a hospital master table. It is an example of a business report data table. It is a schematic block diagram which shows the structure of the terminal device 2 which concerns on this embodiment. FIG. 6 is a diagram showing an example of a screen transition at the time of posting an article in the terminal device 2. It is a flow chart which shows the outline of the flow of processing at the time of contribution. It is a table for explaining calculation of the degree of similarity between another person in charge and the person in charge. 9 is a table for explaining calculation of average relevance for specific keywords. 9 is a table for explaining a key driver extraction process. It is a flow chart which shows an example of processing which extracts a key driver. 3 is a table showing an example of data stored in a storage unit 11. It is a figure which shows an example of the screen transition at the time of the check before a visit in the terminal device 2. It is an example of a screen on which a key driver is displayed. It is another example of the screen in which the key driver is displayed. It is a flow chart which shows an example of the display processing of a key driver. It is a figure for demonstrating the effect which concerns on this embodiment. It is the 3rd example of the screen where a key driver is displayed. It is a schematic block diagram which shows the structure of the information processing system S2 which concerns on 2nd Embodiment. It is a schematic block diagram which shows the structure of the information processing apparatus 1b which concerns on 2nd Embodiment. It is an example of a selection screen for displaying a graph in which the extraction frequency of the key driver for a specific product is aggregated for each aggregation unit period. It is an example of the graph which totaled the extraction frequency of the key driver with respect to a specific product for every total unit period. It is an example of a selection screen for displaying a graph displaying a result of multiple regression analysis. It is an example of a graph showing a result of multiple regression analysis.

  Hereinafter, the present embodiment will be described with reference to the drawings. However, more detailed description than necessary may be omitted. For example, detailed description of well-known matters and repeated description of substantially the same configuration may be omitted. This is for avoiding unnecessary redundancy in the following description and for facilitating understanding by those skilled in the art.

The information processing system according to the present embodiment provides a target person in charge with a keyword important to the person in charge as a key driver. Specifically, as an example, the information processing system according to the present embodiment provides a person in charge of sales of a drug with a key driver, which is an important keyword for the person in charge of sales of a particular drug, in the sales of the drug.
The target person in charge is, for example, a person in charge of sales of pharmaceuticals, and as an example in the present embodiment, the target person in charge is a wholesaler of pharmaceuticals (also referred to as Marketing Specialist: MS). Will be described below.
The target person in charge may be an MR (Medical Representative) of a pharmaceutical company.

  FIG. 1 is a schematic block diagram showing the configuration of the information processing system S according to this embodiment. As shown in FIG. 1, the information processing system S includes an information processing apparatus 1 and terminal devices 2-1, ..., 2-N (N is a positive value) connected to the information processing apparatus 1 via a communication network 3. And an input terminal device 4-1, ..., 4-M (M is a positive integer) connected to the information processing device 1 via the communication network 3.

The information processing device 1 is, for example, a server and provides a WEB function and a database function.
The terminal devices 2-1, ..., 2-N access the WEB page provided by the information processing device 1 by a target person in charge (herein, as an example, a person in charge of wholesale of pharmaceutical products) or another person in charge. Is the terminal of. The terminal devices 2-1, ..., 2-N are, for example, mobile phones, multifunctional mobile phones (so-called smartphones), tablet terminals, notebook computers, desktop computers, or the like. The terminal devices 2-1, ..., 2-N are collectively referred to as the terminal device 2.

  The target person in charge can post using the terminal device 2 regarding a sales activity, and can browse a key driver, which is a keyword related to the sales activity of the product, for each product (here, a pharmaceutical product).

  FIG. 2 is a schematic block diagram showing the configuration of the information processing device 1 according to the present embodiment. As illustrated in FIG. 2, the information processing device 1 includes a storage unit 11, a RAM (Random Access Memory) 12, an input unit 13, a communication unit 14, and a CPU (Central Processing Unit) 15. Each unit is connected via a bus.

The storage unit 11 stores a program that the CPU 15 reads and executes.
The RAM 12 temporarily holds information.
The input unit 13 receives an input from an administrator who manages the information processing device 1.
The communication unit 14 communicates with the input terminal devices 4-1, ..., 4-M and the terminal devices 2-1, ..., 2-N via the communication network 3.
The CPU 15 functions as the similarity determination unit 151, the similar person in charge extraction unit 152, the key driver extraction unit 153, and the output unit 154 by reading the program from the storage unit 11 and executing it. Details of these processes will be described later.

FIG. 3A is an example of a drug master table. FIG. 3B is an example of a pharmaceutical company master table. FIG. 3C is an example of the supplementary item table.
The drug master table T1 shown in FIG. 3A is stored in the storage unit 11. In the drug master table T1, a drug ID, which is identification information for identifying a drug, a drug item, and a pharmaceutical company ID, which is identification information for identifying a pharmaceutical company, are associated with each other.
The storage unit 11 also stores a pharmaceutical company master table T2 shown in FIG. 3B. In the pharmaceutical company master table T2, the pharmaceutical company ID and the pharmaceutical company name are associated with each other. By referring to the pharmaceutical company master table T2, the pharmaceutical company of each drug in the drug master table T1 can be specified.

  The storage unit 11 also stores a supplementary matter table T3 shown in FIG. 3C. In the supplementary item table T3, supplementary items related to each drug ID, each keyword peculiar to the drug (here, as an example, combination example, insufficient example, drug effect) and the package insert file of the drug are associated with each other. ing. That is, the storage unit 11 stores information for identifying a specific product (here, a drug ID as an example) and an attached document of the specific product (here, an attached document file of the drug) in association with each other.

  FIG. 4A is an example of a person-in-charge master table. FIG. 4B is an example of a hospital master table. FIG. 4C is an example of a business report data table.

  The person in charge master table T4 shown in FIG. 4A is stored in the storage unit 11. In the person-in-charge master table T4, a person-in-charge ID that is information for identifying a person in charge of sales, a person-in-charge name of the motorcycle, a position of the person-in-charge, an area of a branch to which the person-in-charge belongs, and a person in charge Is associated with the branch to which it belongs.

  The storage unit 11 also stores a hospital master table T5 shown in FIG. 4B. In this hospital master table T5, a hospital ID that is hospital identification information for identifying a hospital and a hospital name of the hospital are associated with each other.

  Further, the storage unit 11 stores a business report data table T6 shown in FIG. 4C. In the business report data table T6, the data posted by the person in charge of sales via the terminal device 2 is accumulated. In this business report data table T6, a post ID that is information for identifying a post, a post date and time of the post, a person ID of a person who posted the post, a hospital ID of a hospital that is the target of the post, and a post of the post. The drug ID of the target drug and the article (comment) described in the post are associated with each other.

  Next, the configuration of the terminal device 2 will be described. FIG. 5 is a schematic block diagram showing the configuration of the terminal device 2 according to the present embodiment. As shown in FIG. 5, the terminal device 2 includes a storage unit 21, a RAM 22, an input unit 23, a communication unit 24, a CPU 25, and a display 26. Each unit is connected via a bus.

The storage unit 21 stores a program that the CPU 25 reads and executes.
The RAM 22 temporarily stores information.
The input unit 23 receives an input from using the terminal device 2. The input unit 23 is a touch panel in the case of a smartphone or a tablet terminal.
The communication unit 24 communicates with the information processing device 1 via the communication network 3. This communication may be wired or wireless.
The CPU 25 reads the program from the storage unit 21 and executes it.
The display 26 is displayed according to an instruction from the CPU 25.

  FIG. 6 is a diagram showing an example of screen transitions at the time of posting an article on the terminal device 2. On the screen G1 of FIG. 6, in area a, the pharmaceutical company that manufactured the drug to be posted is selected, and in area b, the person in charge selects the hospital to be posted. As a result of these selections, the screen changes from the screen G1 to the screen G2.

  In the screen G2 of FIG. 6, the product name of the drug to be posted is selected in the area c, and the article to be posted is input in the area d. When these inputs are completed, the screen changes from the screen G2 to the screen G3.

  In the screen G3 of FIG. 6, the selected hospital is displayed in the area e, the product name of the selected drug is displayed in the area f, and the name of the person in charge of posting (Taro Yamada here) is displayed in the area g. Then, in the area h, the post of the person in charge (here, the MS leader) is displayed. In the screen G3 of FIG. 6, the article input by the person in charge is displayed in the area i, the date and time when the article is posted is displayed in the area g, and the area k is located below the area i. A reply article of another person in charge (here, MR Hanako Sato) to the article is displayed.

  FIG. 7 is a flowchart showing an outline of the flow of processing at the time of posting.

  (Step S21) First, the terminal device 2 receives an input of a post from a person in charge.

  (Step S22) Next, the terminal device 2 transmits the posted data including the received posted contents to the information processing device 1.

  (Step S11) Next, the information processing device 1 receives the posted data transmitted from the terminal device 2, and adds the posted data to the business report data table T6 of the storage unit 11. As a result, the posted data is accumulated in the business report data table T6 of the storage unit 11.

  Next, with reference to FIGS. 8 to 10, a key driver extraction process, which is a keyword related to a sales activity of a specific product, in the information processing device 1 will be described. FIG. 8 is a table for explaining calculation of the degree of similarity between another person in charge and the person in charge. FIG. 9 is a table for explaining the calculation of the average degree of association for a specific keyword. FIG. 10 is a table for explaining the key driver extraction processing.

The similarity determination unit 151 extracts a person in charge who has the same area as the target person in charge as another person in charge. Thus, as shown in FIG. 8, when the target person in charge is user0, the person in charge of user1, ..., User5, ... Is extracted as another person in charge.
The degree-of-similarity determination unit 151 determines the degree of similarity with the person in charge of the target for each of the extracted other persons in charge. Specifically, the similarity determining unit 151 posts articles posted by the target person in charge user0 and other persons in charge user1, ..., User5, ... During a preset period (for example, within the last 13 weeks). Then, morphological analysis is performed. After the morphological analysis is executed, the similarity determination unit 151 is posted by the target person in charge user0 and other persons in charge user1, ..., User5, ... During the preset period (for example, within the last 13 weeks). Count the frequency of each keyword in the article. At that time, the similarity determination unit 151 aggregates the synonyms into one word and counts them. For example, the WEB, the web, and the web lesson are all regarded as the web lesson, and the count number of the web lesson is increased.

  Here, the similarity determination unit 151 may extract only the preset keywords and count the frequency, or may extract the frequencies in descending order.

  Here, the similarity is a cosine similarity as an example. The cosine similarity is expressed by the following formula.

  Here, the q vector is a vector whose element is the frequency of each keyword of the target person in charge, and the d vector is a vector whose element is the frequency of each keyword of another person who calculates the similarity. Yes, i is an index, and V is the number of elements in the q and d vectors.

  As shown in FIG. 8, a method of calculating the cosine similarity between the target person in charge user0 and another person in charge user1 when there are only three keywords will be described.

From FIG. 8, the q vector is (3, 4, 2) and the d vector is (2, 5, 1). The cosine similarity is 0.95 (= (3 × 2 + 4 × 5 + 2 × 1) / ((√3 ² +4 ² +2 ² ) × (√2 ² +5 ² +1 ² ))).

  In this way, the similarity determination unit 151 calculates the cosine similarity for persons in charge other than user1.

  As described above, the similarity determination unit 151 determines the frequency of each of a plurality of keywords included in a post related to a sales activity targeting a specific product (pharmaceutical product) by a target person in charge during a set period, and other persons in charge. By using the frequency for each of a plurality of keywords included in a post regarding sales activities targeting the specific product (pharmaceutical product) in the setting period according to, for each other responsible person, Determines the similarity of posts. Here, the post similarity is, for example, the similarity between the appearance frequency of each keyword included in the post of the target person in charge and the appearance frequency of each keyword included in the post of another person in charge, and as an example, Calculated by cosine similarity.

  Then, the similar person in charge extraction unit 152 extracts at least one similar person in charge based on the degree of similarity. Specifically, the similar person extraction unit 152 extracts at least one similar person by applying the degree of similarity to a predetermined criterion. In the present embodiment, as an example, the similar person-in-charge extraction unit 152 extracts L persons (L is a positive integer) and similar person-in-charge from other persons in descending order of similarity. As a result, in the case of FIG. 9, for example, five users, user1, user2, user3, user4, and user6 are extracted as similar persons.

Next, a method of calculating the average relevance will be described with reference to FIG.
In FIG. 9, for each of the extracted similar persons, the value obtained by multiplying the posting frequency of the keyword “Web workshop” in the set period and the degree of similarity between the similar person and the target person is summed up. The value (sum of “similarity × keyword frequency”) is shown as 7.33.
Further, the total degree of similarity between the extracted similar persons and the target person in charge is indicated as 3.31. A total of 7.33 of “similarity × frequency of keyword” is a total of similarity. The value divided by 31 is shown as the average degree of association 2.21.

  In FIG. 10, the average degree of association is shown for each of the keywords “Web class”, “poster”, and “accompanying time difference”. As shown in FIG. 10, the key driver extraction unit 153 calculates the average degree of association for each keyword included in the posts of the extracted similar persons.

  Then, the key driver extraction unit 153 extracts, for example, the top K keywords (K is a positive integer) with high average relevance as a key driver.

  In the present embodiment, as an example, the key driver extraction unit 153 calculates the average relevance as a value obtained by dividing the sum of “similarity × frequency of keywords” by the total similarity, but the present invention is not limited to this. Absent. The key driver extraction unit 153 may calculate the sum of “similarity × frequency of keyword” as a value obtained by dividing the total number of extracted similar persons. Further, the key driver extraction unit 153 does not compare the average relevance, but compares the total of “similarity × keyword frequency”, and the higher the total of “similarity × keyword frequency”, the higher the priority. Then, the keyword may be calculated as a key driver.

  In this way, the key driver extraction unit 153 uses the appearance frequency of each keyword included in the post of the extracted similar person in charge and each similarity degree with the target person in charge of the similar person in charge. , At least one or more key drivers of the specific product are extracted from each keyword included in the post of the similar person in charge.

  Specifically, the key driver extraction unit 153, for each keyword included in each of the posts of the extracted similar persons in charge, the appearance frequency of the keyword included in the extracted posts of the similar persons and the similar person in charge. The degree of relevance of the subject person in charge to the keyword based on the degree of similarity of the post with the person in charge of the subject person, and based on the degree of relevance calculated for each keyword, at least the key driver Extract one or more.

  As a result, the higher the degree of similarity of posts and the higher the frequency of appearance of keywords included in posts of similar persons, the higher the degree of relevance can be set, and keywords with high degrees of relevance are extracted as key drivers. Therefore, the keywords frequently posted by a person with the same sales level as the person in charge is extracted as the key driver. Therefore, it is possible to improve the possibility of fully understanding the keyword related to the sales activity of the specific product provided to the person in charge, and the possibility of utilizing it.

  Here, the degree of relevance is the sum of “similarity × keyword frequency”, the value obtained by dividing the total of “similarity × keyword frequency” by the number of extracted similar persons, or “similarity × keyword frequency”. Is a value obtained by dividing the sum of the above by the total of the similarities of the extracted similar persons (that is, the average degree of association in FIGS. 9 and 10).

  In the present embodiment, as an example thereof, a value obtained by dividing the total of “similarity × frequency of keyword” by the total similarity of extracted similar persons is used as the degree of association. That is, as an example in the present embodiment, the key driver extraction unit 153, for each keyword included in each of the posts of the extracted similar persons, and the appearance frequency of the keyword included in the extracted posts of the similar persons. A value obtained by multiplying a value obtained by multiplying the similarity of the similar person in question with the target person in charge is summed over the similar persons to obtain the value of the similarity with the target person in charge of each of the extracted similar persons. A value obtained by dividing the sum (that is, the average degree of association in FIGS. 9 and 10) is calculated as the degree of association.

  The process of extracting the key driver for each person in charge will be described with reference to FIG. FIG. 11 is a flowchart showing an example of a process for extracting a key driver.

  (Step S101) First, the CPU 15 determines whether or not the set time has come. The following processing in this flowchart is executed when the set time is reached in one day. It is preferable that the set time is a time zone in which the person in charge does not use (for example, night time).

  (Step S102) When it is determined in step S101 that the set time has come, the CPU 15 selects user0 as the target person in charge and selects one drug as the target drug.

  (Step S103) Next, the similarity determination unit 151 extracts at least one other person in charge who belongs to the same area as the person in charge.

  (Step S104) Next, the similarity determination unit 151 performs morphological analysis on articles posted by the target person in charge and the other person in charge about the target drug within the set period, and the keywords included in the article are analyzed for each person in charge. Count.

  (Step S105) Next, the similarity determination unit 151 calculates the similarity for each of the other similarities by the above-described calculation formula, for example.

  (Step S106) Next, the similar person in charge extraction section 152 extracts L persons and similar person in charge from the one having the highest degree of similarity.

  (Step S107) Next, the key driver extraction unit 153 calculates the average degree of association for each keyword included in the articles posted by other persons in charge during the set period.

  (Step S108) Next, the key driver extraction unit 153 extracts the top K key drivers having a high average degree of association.

  (Step S109) Next, the key driver extraction unit 153 saves the set of the extracted K key drivers and the average degree of association corresponding to the storage unit 11 in the storage unit 11.

  (Step S110) Next, the CPU 15 determines whether or not there is a next drug not selected.

  (Step S111) If there is a next drug that has not been selected in step S110, the CPU 15 selects the next drug as a target drug, and executes the processing of step S104 and subsequent steps again. By repeating this, the storage unit 11 stores a set of average relevance degrees corresponding to K key drivers for all of the posted pharmaceutical products for a certain person in charge.

  (Step S112) When there is no next medicine not selected in step S110, the CPU 15 determines whether there is a next person in charge who has not selected. If there is no next person who is not selected, the process of this flowchart ends.

  (Step S113) If there is a next person in charge who has not been selected in step S112, the CPU 15 selects the next person in charge as the target person in charge, and executes the processing from step S103 again. By repeating this, the storage unit 11 stores a set of average relevance degrees corresponding to K key drivers for all posted pharmaceutical products for all posted staff members.

  By repeating the process of step S109 of FIG. 11, as shown in FIG. 12, a plurality of key drivers is accumulated for each drug for each subject, and the corresponding average similarity is accumulated. FIG. 12 is a table showing an example of data stored in the storage unit 11. As shown in FIG. 11, a set of a subject ID, a drug ID, a key driver, and an average similarity is associated and stored in the storage unit 11.

  Next, a screen of the terminal device 2 in the case where the target person in charge checks the key driver using the terminal device 2 before visiting the doctor who is the sales office will be described with reference to FIG. 13. FIG. 13 is a diagram showing an example of a screen transition at the time of checking before the visit in the terminal device 2. In FIG. 13, when the "check before visit" button B1 is selected on the screen G4, the screen changes to the screen G5. On the screen G5, a key driver is displayed for each drug item. By scrolling up and down as shown by arrow A1 on the screen G5, the key drivers for the other drug items are displayed. On the screen G5, when the link L1 of "Benefit" of the item B is selected, a screen G6 is displayed. The effect of the item B is displayed on the screen G6. Information such as usage and capacity may be displayed in addition to the efficacy and utility of the drug.

  In order to perform such a display, the output unit 154 outputs information for displaying at least one of the efficacy, the utility, the usage, and the capacity of the drug on the display 26 in response to a request from the terminal device. As a result, not only the key driver of the drug but also at least one of the drug's efficacy, utility, usage, and capacity can be displayed on the display 26. Therefore, the person in charge is in charge of the drug's efficacy, utility, usage. , At least one of the capacities can be easily grasped.

  FIG. 14 is an example of a screen on which the key driver is displayed. The screen G51 of FIG. 14 is an example of the screen G5 corresponding to the result of FIG. In FIG. 14, “poster”, “web lesson”, and “time difference companion” are key drivers, and the larger the average relevance, the larger the character size, and the larger the average relevance, the more clearly they can be seen. For example, the redness of letters is high.

  In order to perform such a display, the output unit 154 displays the corresponding key driver of the terminal device 2 in the size and / or color of the character corresponding to the value of the degree of association (here, the average degree of association). Information to be displayed on the display 26 is output. Accordingly, the key driver having a larger value of the degree of association (here, the average degree of association, as an example) can be visually recognized more clearly by the person in charge.

  In FIG. 14, “Web”, “Web class”, and “Web” are shown as synonyms for the key driver “Web class”. These synonyms are complementary to the key driver "Web Workshop". These synonyms are displayed in a character size and / or color that can be distinguished from the key driver.

  In order to perform such a display, when the synonym of the key driver displayed on the display 26 is included in the post of the other person in charge and / or the post of the person in charge of the target, the output unit 154 gives the consent. Information for displaying on the display 26 is output in a display mode in which a word is distinguished from the key driver. Thereby, when the synonym of the key driver is included in the posts of other persons in the same area, the synonym is displayed on the display 26 together with the key driver. Therefore, even if it is difficult to understand the key driver only on the display 26, the synonyms of the key driver are displayed, thereby facilitating the understanding of the meaning of the key driver by the person who looks at the display 26. be able to.

  FIG. 15 is another example of the screen on which the key driver is displayed. The screen G52 of FIG. 15 is an example of the screen G5 corresponding to the result of FIG. In FIG. 15, “combination example”, “insufficient example”, and “medicine effect” are key drivers, and these are keywords peculiar to pharmaceutical products. When "example of combination" is selected on the screen G52, supplementary items corresponding to "example of combination" are displayed. Here, the supplementary matter of the combination example is information on a specific medicine, that is, a medicine to be administered in combination with the medicine of the item xx of FIG.

  When "insufficient example" is selected on screen G52, supplementary items corresponding to "insufficient example" are displayed. Here, the supplementary matter of the insufficient cases was a specific medicine, that is, another medicine having the same efficacy as the item xx in FIG. 15, and there was a patient whose prescription doctor judged that the efficacy was insufficient. This is information in case. By displaying supplementary items corresponding to this “insufficient example”, when a sales representative appeals for a specific drug (for example, item xx in FIG. 15), an insufficient example of another company's product with the same drug efficacy is obtained. The specific item determined to be can be confirmed in advance by this function before the negotiation, and the negotiation scenario can be set up as a specific switching target.

  When "medicine effect" is selected on screen G52, supplementary items corresponding to "medicine effect" are displayed. Here, the supplementary item of the drug effect is information on the drug effect of a specific drug, that is, the drug of the item xx of FIG.

  In order to make such a display, as shown in the supplementary item table T3 of FIG. 3C, the keywords specific to the drug and the supplementary items related to the keyword are stored in association with each other in the storage unit 11. ing. The output unit 154 refers to the storage unit 11 and refers to the storage unit 11 when the person in charge of the target drug specifies the drug-specific keyword among the key drivers displayed on the display 26 for the specific drug. And information for displaying supplementary items corresponding to the designated set of keywords on the display 26. As a result, even if the key driver displayed for a specific drug is a keyword specific to that drug, the person in charge can check the supplementary items, so it is easy to do this in a short time before business hours. You can grasp the contents of the key driver.

  FIG. 16 is a flowchart showing an example of the display process of the key driver.

  (Step S41) First, the terminal device 2 determines whether or not the "check before visit" button B1 is pressed.

  (Step S42) When the "check before visit" button B1 is pressed in step S41, the terminal device 2 transmits a request for the "check before visit" page to the information processing device 1. At this time, the terminal device 2 also transmits the person-in-charge ID of the person in charge who is using the terminal device 2 to the information processing apparatus 1.

  (Step S31) The information processing device 1 receives the request for the “check before visit” page, and the CPU 15 of the information processing device 1 responds to the request and averages the key driver and the average for each person in charge by drug. Data corresponding to a pair with the degree of similarity (that is, display data of the key driver for each drug item as shown in FIG. 15) is generated.

  (Step S32) The information processing device 1 transmits the generated data to the terminal device 2.

  (Step S43) The terminal device 2 receives the data transmitted from the information processing device 1 and displays the received data.

  FIG. 17 is a diagram for explaining the effect according to the present embodiment. If the sales force of the target person (hereinafter referred to as the sales level) is low, the posted content will be similar to other people with the same low sales level, so the frequency of each keyword in the posted article Will be closer. As a result, as shown in FIG. 17, for each drug, while the sales ability (hereinafter, referred to as the sales level) of the target person in charge is low, the article posted by another person in the same sales level is low. Is displayed as a key driver.

  Next, if the sales ability of the target person in charge (hereinafter referred to as the sales level) rises to the medium level, the content of the post becomes similar to that of the other person with the sales level of the medium level. The frequency of each keyword in the posted articles will also be close. As a result, as shown in FIG. 17, for each drug, when the sales ability of the target person in charge (hereinafter referred to as the sales level) is the medium level, the sales level is similarly posted by another person in the middle level. Keywords in the article are displayed as a key driver.

  Next, if the sales capability of the target person in charge (hereinafter referred to as the sales level) rises to a high level, the content of the post will be similar to other people in the same high sales level. The frequency of each keyword in the posted articles will also be close. As a result, as shown in FIG. 17, when the sales ability (hereinafter referred to as the sales level) of the person in charge for each drug is at a high level, the sales level is similarly posted by another person at a high level. Keywords in the article are displayed as a key driver.

  As described above, the information processing system S according to the present embodiment provides the target person in charge with the keyword regarding the sales activity of the specific product as a key driver. The information processing system S determines the frequency of each of a plurality of keywords included in a post related to the sales activity targeting the specific product by the person in charge of the target during the set period, and the specific frequency in the set period by another person in charge. A similarity determining unit that determines the degree of similarity with the person in charge of the target by using the frequency of each of the plurality of keywords included in the post regarding the sales activity targeting the product is provided. Furthermore, the information processing system S includes a similar person extraction unit that extracts at least one similar person based on the degree of similarity. Furthermore, the information processing system S uses the appearance frequency of each keyword included in the post of the extracted similar person in charge and the degree of similarity between the person in charge of the target of the similar person in charge of the similarity. A key driver extraction unit that extracts at least one or more key drivers of the specific product from each keyword included in the post of the person in charge.

  According to this configuration, the key driver corresponding to the sales level of the target person in charge is extracted, and the extracted key driver changes gradually as the sales level rises. It is possible to improve the possibility of fully understanding the keyword related to the sales activity of the product (pharmaceutical product in this case) and the possibility of utilizing it.

  The screen shown in FIG. 18 may be displayed on the terminal device 2. FIG. 18 is a third example of the screen on which the key driver is displayed. The screen G61 of FIG. 18 is an example of the screen G5 corresponding to the result of FIG. In the screen G61 of FIG. 18, a plurality of key drivers are displayed for the medicine “item xx”. In order to display this, the output unit 154 outputs information for displaying the extracted key driver.

  With this configuration, the key driver can be presented to the person in charge. The key driver corresponding to the sales level of the target person in charge is extracted, and the extracted key driver changes gradually as the sales level rises. Since it is possible to improve the possibility of fully understanding the key driver, which is a keyword, and the possibility of utilizing it, it is possible to further optimize the sales activities of the person in charge.

  Further, on the screen G61 of FIG. 18, as an example, the button L2 described as the attached document is displayed for the medicine “item xx”. In order to display this, the output unit 154, together with the key driver extracted by the key driver extraction unit 153, an attached document (for example, “Pharmaceutical Medical Device Act” and “Medical”) of a specific product (here, “item xx”). Output the information to make it possible to refer to the most basic and important public documents based on the “Guidelines for sales information provision activities for prescription drugs”. The communication unit 14 transmits this information to the terminal device 2, the communication unit 24 of the terminal device 2 receives this information, and the CPU 25 of the terminal device 2 controls the display 26 to display this information. The button L2 is not limited to the button and may be a link.

  According to this configuration, based on the package insert (for example, “Pharmaceutical Medical Equipment Act” and “Guidelines for Sales Information Provision of Prescription Drugs”) of the specific product (here, “item xx”) to the person in charge. The most basic and important official document) can be presented, so it is possible to easily obtain knowledge about a specific product while optimizing sales based on the sales information provision guidelines for ethical drugs. it can.

  When the user selects and operates the button L2 described as “attached document” on the screen G61 of FIG. 18, a pop-up screen G62 is displayed below the screen G61 as an example. The attached document of “xx” is displayed.

  In order to display this, the output unit 154 selects a specific product (here, a selection operation by the person in charge who is the button L2 and is described as "attached document" as an example) by the person in charge. Then, the information for displaying the attached document of "item xx") is output. Here, as an example thereof, the output unit 154 refers to the storage unit 11 and outputs the attached document file associated with the “item xx”. The communication unit 14 transmits this information (here, attached document file) to the terminal device 2, the communication unit 24 of the terminal device 2 receives this information (here, attached document file), and the CPU 25 of the terminal device 2 The display 26 is controlled to display this information (here, the attached document file).

  With this configuration, it is possible to present the package insert of the specific product (here, “item xx”) to the person in charge, so it is appropriate for the business in consideration of the sales information provision activity guidelines for prescription drugs. It is possible to easily obtain knowledge about a specific product while trying to realize it. Further, since the terminal device 2 displays the key driver and the attached document at the same time, the person in charge can compare the key driver and the attached document. You can check it instantly.

<Second Embodiment>
Next, the second embodiment will be described. In the first embodiment, the key driver is displayed according to the person in charge (for example, MS). When this key driver is displayed to multiple persons in charge, the more persons in charge, the person in charge of management who manages the person in charge (hereinafter referred to as “administrator”) can display the key driver for management purposes. It is difficult to check if it is valid.
To solve this problem, in this embodiment, a plurality of persons in charge (for example, MS) are aggregated into a group of management units such as a branch or a sales department, and the terminal device 2 is displayed to persons in charge included in the group. The key driver frequency aggregation result is displayed and / or the transition of the aggregation result is displayed in time series. As a result, the administrator can grasp the aggregation result of the frequency of the key driver displayed to the person in charge included in the group and / or the transition of the aggregation result in time series, so that the display of the key driver is appropriate. You can check if there is.

  FIG. 19 is a schematic block diagram showing the configuration of the information processing system S2 according to the second embodiment. As shown in FIG. 19, in the information processing system S2 according to the second embodiment, the information processing apparatus 1 in FIG. 1 is changed to the information processing apparatus 1b according to the second embodiment. . The configuration of the terminal device 2 is the same as that of the first embodiment, and thus detailed description thereof will be omitted.

  FIG. 20 is a schematic block diagram showing the configuration of the information processing device 1b according to the second embodiment. The information processing device 1b according to the second embodiment is different from the information processing device 1 of FIG. 2 in the program stored in the storage unit 11. The CPU 15 reads out the program from the storage unit 11 and executes the program to add the similarity determination unit 151, the similar person extraction unit 152, the key driver extraction unit 153, and the output unit 154, and further the totaling unit 155 and the analysis execution unit. Function as 156.

  FIG. 21 is an example of a selection screen for displaying a graph in which the extraction frequency of the key driver for a specific product is aggregated for each aggregation unit period. FIG. 21 is an example of a screen displayed on a terminal device used by an administrator who manages a sales person. As shown in FIG. 21, the upper limit number of displayed key drivers is set by designating the “upper limit number of words”. In addition, the display period of the extraction frequency (here, as an example, from June 8, 2018 to September 12, 2018) is designated by the administrator, and the display period of the extraction frequency is set. The specific product is selected by the item designated by the administrator. The collection period for collecting the extraction frequencies is one week here as an example, but may be one month or one day. As shown in FIG. 21, branch offices, sales departments, branches, etc. to be totaled are selected. As a result, a graph can be displayed for each organization such as each branch office, each sales department, or each branch. Further, as shown in FIG. 21, the manager selects a position. As a result, a graph can be displayed for each position. Here, MS is selected as an example.

  FIG. 22 is an example of a graph in which the extraction frequency of the key driver for a specific product is aggregated for each aggregation period. This graph is displayed on the terminal device 2 used by the administrator. Here, the aggregation unit period is, for example, one week, but may be one month, one day, or any period. The vertical axis represents the total frequency of key drivers transmitted to a plurality of MSs, and the horizontal axis represents the time in week units here. Here, it is assumed that the key driver extraction unit 153 extracts the key driver for each product, for example, once a day for one user. In FIG. 22, the weekly total frequency of key drivers transmitted to a plurality of MSs is shown for each key driver. As shown in the region R1, the key driver uses the synonyms (“cool”, “cool feeling”, “cool feeling”, “cool feeling”) of the key driver registered in advance in the storage unit 11 and used at the time of posting. It is displayed collectively in one key driver (“feeling unpleasant”).

  In order to display the graph of FIG. 22, the totaling unit 155 is designated by the administrator on the selection screen of FIG. 21, for example, from the highest frequency of the key drivers extracted for individual persons in charge (for example, MS). Words for the upper limit of the number of words (here, 15 words with the highest frequency) are extracted. The upper limit of the number of words may be set in advance. The tallying unit 155 tallies the frequency of the key drivers of the specific products extracted within the tallying unit period (here, one week unit) for each of the staff members belonging to the group. Here, as an example, the counting of the frequencies is performed for the extracted 15 words with the highest frequency. In addition, this totaling is executed for each product. In addition, at the time of totaling, key driver synonyms registered in advance and used at the time of posting are aggregated into one key driver. Then, the output unit 154 outputs information for displaying the result of the counting by the counting unit 155 (here, for example, information for displaying the graph of FIG. 22). Thereafter, this output information is transmitted from the communication unit 14 to the terminal device 2, the communication unit 24 of the terminal device 2 receives this information, and the CPU 25 of the terminal device 2 controls to display this information on the display 26. To do. As a result, the graph of FIG. 22 is displayed on the terminal device 2.

  According to this configuration, the frequency of the entire group of key drivers can be grasped in time series. As a result, it is possible to determine whether the key driver is appropriate for each group with a small amount of labor. Furthermore, by systematically grasping the key driver as the activity trigger of each individual person in charge, it can be linked to the trajectory correction of the approach of the item arranged as an organization, and from the trend trend of the key driver conspicuous for the particular product, The emergence of unexpected key drivers is gaining insight. For example, if the frequency of “samples” is higher than you think, it is possible to review the internal circumstances and find out that demos of “samples” (eg formulation samples) are accepted on site, and review the measures for sales activities. it can.

  FIG. 23 is an example of a selection screen for displaying a graph displaying the results of multiple regression analysis. FIG. 23 is an example of a screen displayed on a terminal device used by an administrator who manages a sales person. As shown in FIG. 23, by specifying “fixed number of words”, the number of key drivers (here, 10 as an example) used as explanatory variables used in multiple regression analysis is set. That is, here, as an example, the top 10 words of the extracted key driver frequencies are used as explanatory variables of the multiple regression analysis. The aggregation unit period for aggregating the frequency of the key driver is one week here as an example, but may be one month or one day, or may be set to any period.

  Further, the target period of the multiple regression analysis (here, as an example, from July 1, 2018 to August 31, 2018) is designated by the administrator, and the target period of the multiple regression analysis is set. Further, a specific product (here, a specific pharmaceutical product as an example) is selected by designating the item by the administrator. As shown in FIG. 23, the branch office, sales department, branch office, etc. to be aggregated are selected. As a result, a graph can be displayed for each organization such as each branch office, each sales department, or each branch. Here, as an example, when the sales department is designated as the “Hanshin sales department”, the number of prescriptions of the drug of the target item xx is subjected to multiple regression analysis by the multiple regression analysis in the “Hanshin sales department”. The effect on the key driver is determined by the analysis execution unit 156 for each key driver.

  The objective variable of multiple regression analysis is described as an example of the number of prescriptions for each aggregation unit period of a specific product, but the number is not limited to this, and is a number that represents sales results such as the number of orders received, the number of hires, or the number of sales. May be

  FIG. 24 is an example of a graph showing the results of multiple regression analysis. As shown in FIG. 24, this bar graph is displayed on the terminal device 2 used by the administrator. The vertical axis of the bar graph of FIG. 24 is the degree of influence on the number of prescriptions obtained by the multiple regression analysis, and the horizontal axis is the key driver. Here, as an example, the top 10 frequencies in the target period of the multiple regression analysis are shown. It is a key driver. The key driver considers the difference in expression, and those described in synonymous terms are aggregated into one key driver (for example, indication for illness). As shown in the region R2, the synonyms of the key driver used at the time of posting (“OO”, “adaptation of OO”) are collected into one key driver (“adaptation of OO”). Is displayed. The synonyms used when analyzing the region R2 may be displayed when the displayed cursor is overlaid on the bar graph, or when the input unit 23 of the terminal device 2 is a touch panel. It may be displayed when the bar graph is tapped.

  In order to display the graph of FIG. 24, the tallying unit 155, for a plurality of persons in charge who belong to the group (here, “Hanshin Sales Department” as an example), the tallying unit period (here, as an example, one week) for each person in charge. The frequency of the key driver of the specific product (in this example, the medicine of the item xx) extracted within is aggregated. The analysis execution unit 156 then explains the frequency for each aggregation unit period (here, for example, one week) of each key driver obtained as a result of the aggregation by the aggregation unit 155 as an explanatory variable, and the aggregation unit period of the specific product (here Then, multiple regression analysis is executed with the number of orders (here, as an example, the number of prescriptions) for each order, as an objective variable. The output unit 154 outputs information for displaying the result of execution by the analysis executing unit 156 (here, information for displaying the graph of FIG. 24 as an example). Thereafter, this output information is transmitted from the communication unit 14 to the terminal device 2, the communication unit 24 of the terminal device 2 receives this information, and the CPU 25 of the terminal device 2 controls to display this information on the display 26. To do. As a result, the graph of FIG. 24 is displayed on the terminal device 2.

  According to this configuration, the degree of influence of each key driver on the number representing the business result can be grasped as the tendency of the group.

  As described above, in the information processing system S2 according to the present embodiment, the frequency of each of a plurality of keywords included in a post related to a sales activity targeting a specific product by a target person in charge, and the setting by another person in charge. By using the frequency of each of a plurality of keywords included in the posting related to the sales activity targeting the specific product in the period, the similarity of the posting to the relevant person in charge is determined for each other person in charge. The similarity determination unit 151 is provided. Further, the information processing system S2 includes a similar person-in-charge extraction unit 152 that extracts at least one similar person in charge based on the degree of similarity. Furthermore, the information processing system S2 uses the respective appearance frequencies of the respective keywords included in the post of the extracted similar person in charge and the respective degrees of similarity with the target person in charge of the similar person in charge of the similarity. A key driver extraction unit 153 that extracts at least one or more keywords as a key driver of the specific product from the keywords included in the post of the person in charge is provided. Further, the information processing system S2 includes a totaling unit 155 that totals the frequency of the key driver of the specific product extracted for each total unit period for each of the plurality of persons in charge who belong to the group.

  According to this configuration, since the key drivers of the specific products provided to the person in charge are aggregated, it is possible to determine whether the key driver is appropriate with a small amount of effort, and it is possible to judge in group units. By systematically grasping the key driver as an activity trigger, it is possible to help optimize the sales activity of each person in charge for the particular product. Further, it is possible to grasp the important key driver by analyzing the degree of influence on the number showing the business result by using the frequency of the key driver for each group. Thereby, the key driver often used in sales and the important key driver can be made known to each person in charge, so that the sales activity of each person in charge can be further optimized.

  As described above, the present invention is not limited to the above-described embodiments as they are, and constituent elements can be modified and embodied without departing from the scope of the invention in an implementation stage. Further, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the above embodiments. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, the constituent elements of different embodiments may be combined appropriately.

S, S2 Information processing system 1, 1b Information processing device 2-1, ..., 2-N Terminal device 3 Communication line network 11 Storage unit 12 RAM (Random Access Memory)
13 input unit 14 communication unit 15 CPU (Central Processing Unit)
21 storage unit 22 RAM
23 input unit 24 communication unit 25 CPU
26 Display 151 Similarity Determining Section 152 Similar Person Extracting Section 153 Key Driver Extracting Section 154 Output Section 155 Aggregating Section 156 Analysis Execution Section

Claims (12)

Regarding the frequency of each of a plurality of keywords included in a post regarding sales activities targeting a specific product in a setting period by a target person in charge, and sales activities targeting the specific product in the setting period by another person in charge Using the frequency of each of a plurality of keywords included in the post, for each other person in charge, a similarity degree determination unit that determines the similarity degree of the post with the person in charge of the target,
A similar person extracting unit that extracts at least one similar person based on the degree of similarity;
Using the extracted frequency of each keyword included in the post of the similar person in charge and the degree of similarity with the person in charge of the target of the similar person, in the post of the similar person in charge From each included keyword, a key driver extraction unit that extracts at least one or more keywords as a key driver of the specific product,
With respect to a plurality of persons in charge who belong to the group, an aggregating unit that aggregates the frequency of the key driver of the specific product extracted for each aggregating unit period,
An information processing system including. The information processing system according to claim 1, further comprising: an output unit that outputs information for displaying a result of tallying by the tallying unit. Multiple regression analysis using the frequency of each key driver obtained as a result of the aggregation by the aggregating unit for each aggregation unit period as an explanatory variable, and the number representing the business performance of each particular product for each aggregation unit period as an objective variable An analysis execution unit that executes
An output unit for outputting information for displaying a result of execution by the analysis executing unit,
The information processing system according to claim 1, further comprising: Regarding the frequency of each of a plurality of keywords included in a post regarding sales activities targeting a specific product in a setting period by a target person in charge, and sales activities targeting the specific product in the setting period by another person in charge Using the frequency of each of a plurality of keywords included in the post, for each other person in charge, a similarity degree determination unit that determines the similarity degree of the post with the person in charge of the target,
A similar person extracting unit that extracts at least one similar person based on the degree of similarity;
Using the extracted frequency of each keyword included in the post of the similar person in charge and the degree of similarity with the person in charge of the target of the similar person, in the post of the similar person in charge From each included keyword, a key driver extraction unit that extracts at least one or more keywords as a key driver of the specific product,
An output unit for outputting information for displaying the extracted key driver,
An information processing system including. The information processing system according to claim 4, wherein the output unit outputs information for making it possible to refer to the attached document of the specific product together with the extracted key driver. Further comprising a storage unit in which information identifying the specific product and an attached document of the specific product are stored in association with each other,
The information processing system according to claim 4, wherein the output unit outputs information for displaying an attached document of the specific product according to an operation performed by a person in charge of the target. Regarding the frequency of each of a plurality of keywords included in a post regarding sales activities targeting a specific product in a setting period by a target person in charge, and sales activities targeting the specific product in the setting period by another person in charge Using the frequency of each of a plurality of keywords included in the post, for each other person in charge, a similarity degree determination unit that determines the similarity degree of the post with the person in charge of the target,
A similar person extracting unit that extracts at least one similar person based on the degree of similarity;
Using the extracted frequency of each keyword included in the post of the similar person in charge and the degree of similarity with the person in charge of the target of the similar person, in the post of the similar person in charge From each included keyword, a key driver extraction unit that extracts at least one or more keywords as a key driver of the specific product,
With respect to a plurality of persons in charge who belong to the group, an aggregating unit that aggregates the frequency of the key driver of the specific product extracted for each aggregating unit period,
An information processing apparatus including. Regarding the frequency of each of a plurality of keywords included in a post regarding sales activities targeting a specific product in a setting period by a target person in charge, and sales activities targeting the specific product in the setting period by another person in charge Using the frequency of each of a plurality of keywords included in the post, for each other person in charge, a similarity degree determination unit that determines the similarity degree of the post with the person in charge of the target,
A similar person extracting unit that extracts at least one similar person based on the degree of similarity;
Using the extracted frequency of each keyword included in the post of the similar person in charge and the degree of similarity with the person in charge of the target of the similar person, in the post of the similar person in charge From each included keyword, a key driver extraction unit that extracts at least one or more keywords as a key driver of the specific product,
An output unit for outputting information for displaying the extracted key driver,
An information processing apparatus including. The similarity determination unit determines the frequency of each of a plurality of keywords included in a post related to a sales activity targeting a specific product by a person in charge during a setting period, and the specific product in the setting period by another person in charge. Using the frequency of each of a plurality of keywords included in the post related to the target sales activity, determining the similarity of the post with the target person in charge for each other person in charge,
A step in which the similar person in charge extracting section extracts at least one similar person in charge based on the degree of similarity;
The key driver extraction unit uses the similarity occurrence frequency of each keyword included in the post of the extracted similar person in charge and the similarity degree with the target person in charge of the similar person in charge of the similar person in charge. A step of extracting at least one or more keywords as a key driver of the specific product from each of the keywords included in the post of the person,
A step of totalizing the frequency of the key driver of the specific product extracted for each of the persons in charge for each of the persons in charge for a plurality of persons in charge belonging to the group;
An information processing method including. The similarity determination unit determines the frequency of each of a plurality of keywords included in a post related to a sales activity targeting a specific product by a person in charge during a setting period, and the specific product in the setting period by another person in charge. Using the frequency of each of a plurality of keywords included in the post related to the target sales activity, determining the similarity of the post with the target person in charge for each other person in charge,
A step in which the similar person in charge extracting section extracts at least one similar person in charge based on the degree of similarity;
The key driver extraction unit uses the similarity occurrence frequency of each keyword included in the post of the extracted similar person in charge and the similarity degree with the target person in charge of the similar person in charge of the similar person in charge. A step of extracting at least one or more keywords as a key driver of the specific product from each of the keywords included in the post of the person,
An output unit outputting information for displaying the extracted key driver,
An information processing method including. Computer,
Regarding the frequency of each of a plurality of keywords included in a post regarding sales activities targeting a specific product in a setting period by a target person in charge, and sales activities targeting the specific product in the setting period by another person in charge Using the frequency of each of a plurality of keywords included in the post, for each other person in charge, a similarity degree determination unit that determines the similarity degree of the post with the person in charge of the target,
A similar person extracting unit that extracts at least one similar person based on the degree of similarity;
Using the extracted frequency of each keyword included in the post of the similar person in charge and the degree of similarity with the person in charge of the target of the similar person, in the post of the similar person in charge From each included keyword, a key driver extraction unit that extracts at least one or more keywords as a key driver of the specific product,
With respect to a plurality of persons in charge who belong to the group, an aggregating unit that aggregates the frequency of the key driver of the specific product extracted for each aggregating unit period,
Program to function as. Computer,
Regarding the frequency of each of a plurality of keywords included in a post regarding sales activities targeting a specific product in a setting period by a target person in charge, and sales activities targeting the specific product in the setting period by another person in charge Using the frequency of each of a plurality of keywords included in the post, for each other person in charge, a similarity degree determination unit that determines the similarity degree of the post with the person in charge of the target,
A similar person extracting unit that extracts at least one similar person based on the degree of similarity;
Using the extracted frequency of each keyword included in the post of the similar person in charge and the degree of similarity with the person in charge of the target of the similar person, in the post of the similar person in charge From each included keyword, a key driver extraction unit that extracts at least one or more keywords as a key driver of the specific product,
An output unit for outputting information for displaying the extracted key driver,
Program to function as.