WO2002057973A1 - Systeme et procede de promotion de la vente de marchandises - Google Patents

Systeme et procede de promotion de la vente de marchandises

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Publication number
WO2002057973A1
WO2002057973A1 PCT/JP2001/000290 JP0100290W WO02057973A1 WO 2002057973 A1 WO2002057973 A1 WO 2002057973A1 JP 0100290 W JP0100290 W JP 0100290W WO 02057973 A1 WO02057973 A1 WO 02057973A1
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WO
WIPO (PCT)
Prior art keywords
purchase
customer
product
sales
data
Prior art date
Application number
PCT/JP2001/000290
Other languages
English (en)
Japanese (ja)
Inventor
Sumio Semura
Original Assignee
Kabushiki Kaisha Mitsukoshi
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Kabushiki Kaisha Mitsukoshi filed Critical Kabushiki Kaisha Mitsukoshi
Priority to PCT/JP2001/000290 priority Critical patent/WO2002057973A1/fr
Priority to JP2002558188A priority patent/JPWO2002057973A1/ja
Publication of WO2002057973A1 publication Critical patent/WO2002057973A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising

Definitions

  • the present invention relates to a sales promotion method for promoting sales of various products to a large number of customers such as merchandise sellers, especially department stores, supermarkets, etc., a combination system for the same, and a computer using the computer. Regarding programs to be implemented. Background art
  • Retail includes, for example, specialty stores that sell specific, specific products to consumers, but also department stores, supermarkets, and other retailers that sell large quantities of products.
  • the RFM method was developed in the United States in the 1940's as a scientific method for promoting such retailers' sales. This RFM method analyzes the consumer's purchase behavior by dividing the consumer into the most recent purchase time (R), the cumulative number of purchases (F) and the cumulative purchase amount (M) over a specific period. It is a technique to do. However, in this era, computers like today were not developed, and although the method was theoretically established, practical implementation was impossible.
  • a computer network using a communication system is used to record customer product purchase data, track customer purchase trends, etc., and further, based on data obtained from these procedures and means, It discloses a method and means for communicating with customers, including means for communicating with customers, including, for example, direct mail (DM).
  • DM direct mail
  • the above-mentioned invention only discloses the idea of the invention in an extremely abstract manner, and lacks specificity. For example, how to record and store customer purchase data, how to link the organized data to sales, and how to target customers There is no specific disclosure on whether to conduct business. Therefore, the present invention seeks to provide an invention that solves the following problems.
  • RFM method to analyze customer's product purchase data, guess future trends of customers and divide customer groups into segments (cells) so that consumers' purchase trends can be easily determined in advance.
  • the customer's product purchase data is output as a two-dimensional table. From this table, consumers' purchasing trends can be determined.
  • the purpose is to automatically output the sales tactics for the target divisions and to provide the sales tactics to the sellers in order to implement the sales strategy predetermined for each of the above divisions (cells). .
  • a first aspect of the invention is that a seller has at least a customer data server for promoting product sales to a customer, a purchase data server connected to a P0S terminal device, a calculation server ', and a sales tactics server.
  • the past specific period is divided into a plurality of period segments, the calculated cumulative number of purchases of the product is divided into the number of segments, and the calculated cumulative purchase amount of the product is divided into a plurality of segments.
  • the customer's second purchase data database is created by allocating the purchase data of each customer from the first purchase data overnight base to the time period corresponding to the latest purchase date of the customer together with the customer's ID number.
  • (d) A two-dimensional table in which one of the two categories, term period, number of times, and amount of money, is selected from the second purchase date base, and these are set as columns on the vertical axis and columns on the horizontal axis. And outputting the other sections as a two-dimensional table configured as a table in each of the plurality of section frames defined by the vertical and horizontal axes.
  • the period division, the cumulative number of purchases division, and the cumulative amount division Is a method of promoting product sales characterized by being one of 3, 4, 5, 6, and 7 respectively.
  • each of the divisions is divided into five divisions, a specific period is set to 365 days, and the period divisions are set to 365 to 18 days before, to 180 to 91 days, and to 9 days. 0 to 45 days or before, 46 to 16 days or before, and 15 to 1 day or before 5 times, and the number of purchases is 1 time, 2 to 3 times, 4 to 9 times, 10 to 19 times Times, and 20 or more times, and the classification of the purchase amount is from 1 to; L 0, less than 000 yen, 10, 000 to 30, less than 30,000 yen, 30, 000 Up to 70,000 yen or less, 70,000 to 140,000 yen or less, and 140,000 yen or more. is there.
  • the two-dimensional table has a two-dimensional table in which a vertical axis represents a cumulative purchase category and a horizontal axis represents a period category, and a cumulative amount category is provided in each cumulative purchase category and the period category.
  • a fifth aspect of the present invention is a product sales promotion method, further comprising a step of outputting a sales tactic assigned in advance to each section of the two-dimensional table.
  • a DM based on the assigned sales tactics, a DM, an email, a log of merchandising power, a discount sale guide, a seasonal greeting, a thank-you letter, and an event message are sent.
  • a seventh aspect of the present invention is a product sales promotion method, further comprising a step of verifying a customer's reaction including a further product purchase of the customer with respect to the executed business activity.
  • An eighth aspect of the invention is that a seller has at least a customer data server, a purchase result data server connected to a POS terminal device, and a calculation server for promoting product sales to customers.
  • This is a sales promotion method using a computer system equipped with a server, a sales tactics server, and an input / output terminal device.
  • the sales promotion method includes the following procedures.
  • a ninth aspect of the present invention is characterized in that the method further includes a step of outputting, to a customer belonging to the outputted personal data, a sales tactic assigned in advance to the category.
  • This is a product sales promotion method.
  • any of the following items is transmitted: DM, mail, E,
  • a eleventh aspect of the invention is a sales promotion system using a combination system provided with the following means.
  • a first purchase data server that records first product purchase data including the customer's product purchase time, number of purchases, purchase price, and product type for the ID number;
  • the past specific period is divided into a plurality of period divisions, the cumulative purchase count is divided into a plurality of divisions, the cumulative purchase amount is divided into a plurality, and the cumulative purchase count of each customer's product from the purchase database.
  • the cumulative purchase price of the product calculate the purchase data of each customer, and convert the calculated data into the time period, the cumulative number of purchases, and the purchase price that correspond to the latest purchase date of the customer.
  • a calculation server that calculates and records the customer's second purchase data, which has been assigned with the customer's ID number,
  • a tactical server that records sales tactics that have been defined in advance corresponding to the two-dimensional table.
  • the number of sections of the period section, the cumulative number of purchases section and the cumulative amount section is any one of 3, 4, 5, 6 and 7. This is a system for promoting product sales.
  • a sales tactic is automatically read out from a predetermined sales tactic database for a division purchaser composed of a combination of the specific period division and a specific number of divisions. 13.
  • a fifteenth aspect of the present invention is a system for promoting sales of goods, further comprising a sales server for performing predetermined sales activities to customers with the sales tactics to the classified purchasers.
  • the sales server sends a product catalog, Product sales characterized by a sales server that carries out sales activities by DM, e-mail, e-mail, or telephone by using one of the following: sales guidance, seasonal greetings, thank-you letters, and event guidance. It is a promotion system.
  • a sixteenth aspect of the present invention is a recording medium recording a program for causing the following procedure for promoting the following product sales to be executed at a convenience store.
  • a seventeenth aspect of the present invention is a program for causing a convenience store system to execute the following procedure for promoting product sales.
  • FIG. 1 is a diagram showing a computer system of the present invention.
  • FIG. 2 is a diagram showing a procedure for carrying out the present invention.
  • FIG. 3 is a diagram illustrating an operation screen in a computer that implements the present invention.
  • FIG. 4 is a diagram showing an operation screen for outputting an RFM template of the present invention.
  • FIG. 5 is a view showing a screen for setting conditions of an RFM table of the present invention.
  • FIG. 6 is a diagram for explaining an example of an RFM table and an output operation according to the present invention.
  • FIG. 7 is a diagram illustrating an example of an RFM table according to the present invention.
  • FIG. 8 is a diagram showing details of an RFM table of the present invention.
  • FIG. 9 is a diagram showing details of an RFM tape of the present invention.
  • FIG. 10 is a diagram illustrating an RFM table as a graph according to the present invention.
  • FIG. 11 is a diagram showing an example of a sales tactic for sales promotion.
  • FIG. 12 is a diagram showing an example of a section in the RFM table of the present invention.
  • FIG. 13 is a diagram showing an example of a score of a section in the RFM table of the present invention.
  • FIG. 14 is a diagram showing a computer screen for outputting a customer list by dividing the RFM table of the present invention.
  • FIG. 15 is a diagram showing an example of a customer list targeted for the sales tactics of the present invention.
  • FIG. 16 is a diagram showing a range of target customers implemented to verify the effect of the RFM method of the present invention.
  • FIG. 17 is a diagram showing details of the verification result shown in FIG. 16; Embodiment of the Invention
  • R is the last purchase date, which means the date the customer last purchased. This date also means the time when the customer leaves the seller.
  • Figure 8A shows how to classify the categories when the category for R is 5.
  • the specified period is 365 days, and this period is divided into five periods: 365 to 181 days or earlier, 180 to 91 days or earlier, 90 to 45 days or earlier, 46 to: L 6 days or less, and 15 to 1 day or less. It is classified into 1 to 5.
  • the number of purchases shall be 1, 2, 3, 4, 9, 10, 19, and 20 or more, and 1 to 5 in addition.
  • the purchase price is divided into 1 to less than 10,000 yen, 10,000 to less than 30,000 yen, 30,000 to less than 70,000 yen, 70,000 to: L less than 40,000 yen, and 140 , 000 yen or more, and each category is from 1 to 5. It is important to note that if a particular customer purchases 3 times before 180 days, and purchases 1 time before 5 days, the R category is 5, the cumulative number is 4, and F (the number of times is 4) Is set to 3, and the cumulative purchase price is calculated by applying the cumulative value to the above category and determining the purchase date of the customer.
  • M is the accumulated purchase price.
  • M has been the element of direct marketing that has the least influence on the future among the three elements of RFM.
  • verification results that the effect of M is the strongest at department stores handling mainly high-priced products are disclosed.
  • the number of each category was 5, but the number of categories is preferably in the range of 3 to 7, and 5 categories are desirable in many analyses.
  • the accumulated amount is also divided into five categories, and the procedure for storing the data of a specific customer together with its ID number in each category is performed.
  • the above is the description of the RFM method.
  • the configuration of the computer system according to the present invention will be described. As shown in Fig. 1, when a customer card is issued, the data input from the terminal 10 is input to the customer ID server 11 and the personal characteristics of the customer, such as occupation, age, address, telephone number, etc. Store the data with the specified ID number.
  • the product purchase data of the customer is input from the POS input terminal 20 and recorded in the purchase data server 21 with a predetermined ID number.
  • These data are usually managed and stored by the RDS system. This makes it easy for a particular customer ID to retrieve that customer's purchase performance.
  • the customer data server 11 and purchase data server 21 are connected to the calculation server 12.
  • This calculation server calculates the purchase data for each customer based on the RFM method described above. Then, the calculation result is recorded in the directory of the specified calculation server.
  • the calculation server is connected to the sales tactics server 13, and when a specified RFM classification is specified from the terminal, the tactics data according to this can be called.
  • a store input / output terminal 14 and a shop input / output terminal 15 are connected as terminals for operating the calculation server 12.
  • the store input / output terminal 14 is, for example, a terminal of a head office or a branch office scattered in various places, and can call a result calculated by the calculation server.
  • the various databases described above and below are preferably constructed as a so-called relational database.
  • a specific store input / output terminal is used to grasp data of a specific store as a whole.
  • the shop input / output terminal is a terminal used for ascertaining data of a specific large category or middle category of a product, such as a women's clothes section and a men's clothes section in a department store, for example. That is, RFM data can be invoked for a particular product group, for example, men's clothing, women's clothing or sporting goods, or more specifically at a shop level (eg, a particular shop in a men's clothing section).
  • the FM store can be called for the entire store, regardless of individual sales floors, regardless of individual sales floors, and for specific sales floors and shops, the RFM data only for that sales floor can be displayed. Evening can be called.
  • a predetermined instruction is issued to the sales server 16 as necessary. That is, the store input / output terminal can designate a specific section (cell) or all sections, and call a sales strategy for this from the strategic server.
  • specific sales activities specified by the sales tactics server such as notification of special events, thank-you letters, notice of new product arrival, etc. Sending, other e-mails, e-mails, etc.
  • You can communicate with DM server 161, mail server 162, e-mail server 163, etc. to do business activities. These: DM servers, etc., can always be sent directly to customers, but can perform various actions.
  • the DM server is provided with various correspondences, such as putting out a list including the address of the customer who sends the DM, printing a letter in a lapel, printing a sealed letter directly, and attaching a necessary greeting letter. I have. The same applies to the mail server.
  • the mail server performs business activities such as putting out a list or writing an address.
  • an evaluation server 17 is provided in connection with the sales server.
  • the evaluation server records the results of the DM performed by the sales server and whether the customer who received the DM purchased more products. It is possible to perform evaluations such as calculating the ratio of visits or purchase results, the number of purchases, etc.
  • the evaluation server finally outputs the evaluation table in a predetermined format.
  • the above constitutes a computer system for implementing the present invention. Note that descriptions of the pudding, CRT, and other ancillary equipment naturally provided in each server are omitted for simplicity. In the above, each server exists individually, but it is possible to accommodate all servers in one large convenience store, and it is not necessary to exist independently.
  • Each server normally functions as a server provided that it is a computer having a CPU, a storage unit, an input unit, an output unit, and the like.
  • the purchase data server is preferably a large server with a storage unit of several terabytes.
  • the purchase data server is updated, for example, weekly or monthly, and the purchase behavior of a new customer during that time is input and updated.
  • the importance of the evaluation server is that the prescribed costs are incurred for the above-mentioned sales activities. It is.
  • Figure 2 shows the procedure for outputting the analysis result by the RFM method from the store input / output terminal or the shop input / output terminal and linking it to the sales activities.
  • Procedures include A routine and B routine.
  • a routine is a route that outputs calculation results mainly by the RFM method as a two-dimensional RFM table (RFM table) and links it with sales tactics.
  • the B route is a route for designating a specific FM segment, outputting the stored personal data of the customer in that segment, and linking with a sales tactic to carry out sales activities.
  • route A is selected.
  • route B is selected.
  • the conditions are set first. As will be described later in detail as the condition setting, selection of store-level data or shop-level data is performed (S11). Next, the customer and the purchase data matching this condition are searched (S12). A search is made for a customer ID that meets this condition (S13). Next, the RFM calculation (S14) is performed from a predetermined time.
  • the calculation result is created as an RFM table (S15) and output in a predetermined table format (S151). Furthermore, after checking the table, input a specific category (S16). A search is made for a sales tactic for the entered category (S17). Then, finally, the RFM table corresponding to the input RFM category and the sales tactic corresponding to this category are output. This completes the A routine. Next, the B routine will be described.
  • the B routine is a routine that outputs a customer list corresponding to a specific section as described above.
  • target sorting conditions are set (S21).
  • a search for purchase data that meets this condition is searched (S22).
  • the customer ID corresponding to this purchase data is searched (S twenty three ).
  • a customer list corresponding to the searched ID is output (S24).
  • the customer list outputs the data necessary for contacting the customer, such as the customer's ID number, address, and name.
  • a corresponding sales tactic is searched from the tactics server as to what sales tactics to perform on the above list (S25), and the result is output (S26).
  • business communication is performed (S27). This communication can be performed using hardware such as the DM server, mail server, and e-mail server described above. Thus, the routine ends.
  • the customer distribution is selected in FIG. 3A, and then the data existing in the predetermined directory is deleted.
  • condition setting S11
  • FIG. 4A shows the operation screen for the store output
  • FIG. B shows the operation screen for the shop output.
  • the store may be, for example, a head office or a branch in a specific area. This indicates that the above-mentioned merchandise purchase data base stores data for all stores including the head office.
  • the calculation or aggregation level can be selected for a store, a specific shop at a specific store, or a specific product level at a specific store.
  • the card category that is, include customers who use their own cards or customers who use general credit cards. Since purchase data is normally tabulated and updated every week, enter the end of each quarter or the nearest Sunday as the base date for calculation. Furthermore, on the screen, it is possible to specify whether or not to include foods overnight.
  • the purchase database has a first database, a second database, and a third database.
  • the first database is the so-called original database, which is recorded on the purchase data server 21 and includes the customer's ID number, the time of purchase, the number of purchases, the purchase price, and the type of product for that customer.
  • the calculation server summarizes and processes the original data and processes it, divides each customer's purchase data into a specific past period into multiple time periods, and calculates the calculated products. Is divided into multiple categories, the calculated cumulative purchase price of the product is divided into multiple categories, and the purchase date of each customer from the purchase database corresponds to the latest purchase date of the customer. This is the overnight data of each customer's purchase data, which is assigned to the customer's ID number along with the customer's ID number.
  • the third day is a database that stores personal data including customer ID numbers assigned to each section of the RFM table. The second database and the third database are recorded in each directory of the calculation server.
  • the data can be imported from the second purchase database and the output format can be selected.
  • Figure 5 shows a screen operation for capturing data and a screen for specifying the output format.
  • Figure 6 shows an example of the RFM template calculation result displayed on the screen (hidden behind the operation screen). To print the displayed screen, execute printing.
  • Figure 7 shows an example of outputting the RFM calculation results as a table (one part omitted).
  • the latest purchase period is divided into five stages from the left on the horizontal axis, the number of purchases is classified on the vertical axis, and the sales amount is further divided within the division (cell) divided by the vertical and horizontal axes. Is divided into five levels, and the number of customers and the accumulated value within that category and the percentage of the total are calculated and shown.
  • the rightmost column shows the subtotal for each cumulative purchase category.
  • the subtotals in columns F1 to F5 indicate the cumulative number of purchasers in each category, the cumulative amount, and% of the total.
  • Figure 7 shows a relatively large table with some parts removed.
  • the detailed data structure of each section is shown in Fig. 8 and subsequent figures.
  • scores of 1 to 5 are assigned according to the respective values of R, S, and M. Indicates the classification.
  • the most desirable number of divisions is 5, but is not limited to this. For example, 3, 4, 6, 7, etc., can be selected. For more detailed analysis, it is recommended that the number of categories is 7, and for more coarse evaluation, it is desirable to divide R, S, and M into three categories.
  • Important customers in terms of purchase frequency are customers who have purchased 20 or more times, followed by customers who have purchased 10 to 19 times, and give scores like 5 and 4 in the same way. -Give higher score to customers who have higher purchase price. In this way, the score is given according to importance.
  • FIG. 8B shows details of the section 1 shown at the left end of the table shown in FIG.
  • This category is for customers who purchased from 180 to 365 days before the evaluation point, that is, half a year or more ago.
  • the number of purchases is also selected for one customer.
  • the purchase price is divided into five levels in the above categories, and the number of customers, the cumulative purchase price, the percentage of the total number of purchases, the percentage of the total purchase price, and the purchase price per person are also added. it's shown.
  • This table shows that the number of customers is large, for example, in the layer where the amount of money is about 10,000 yen to 30,000 yen, so that it is possible to determine that products in such a price range are of interest to customers.
  • Figure 9 shows the distribution of R and M.
  • FIG. 9A shows the cumulative number of purchases corresponding to the categories R1 to R5 and the cumulative amount thereof. In this table, R
  • the population of 1 to R5 can be judged to have a tendency such as an increase or decrease in the number of customers. Similarly, it can be recognized that the trend in the amount of money shows the change over the past year.
  • Figure 9B it is possible to determine the cumulative monetary structure for one year.
  • the high composition ratio of M2 and M3 indicates that the product sales composition within this category is high. From such a point of view, the seller determines a sales tactic such as procurement of a product corresponding to the amount.
  • Can be Fig. 10 is a graph in which R and F are plotted on the horizontal axis, and the distribution of the number of customers and the distribution of the accumulated purchase price are plotted three-dimensionally on the vertical axis. These graphs make it easy to visually determine the trends in the number of customers or cumulative sales against the purchase time and the cumulative number of purchases.
  • Fig. 11 is an example that describes the characteristics and characteristics of the customer demographics for each category of RFM stored in the strategy server 13 and examples of sales tactics. As an example, it can be determined that among the most recently purchased customers (4-5), the customers with the highest number of purchases (3-5) are fixed customers and are also good customers. For these customers, it can be determined that trust has occurred. Therefore, as a sales promotion measure for this customer group, it is necessary to output a customer list and learn faces and names. It is also desirable to promote sales by giving information on related products or inviting to dinner parties.
  • a customer segment belonging to R with a score of 1 and F with a score of 1 can be determined to be a customer who has left or has fertil from the seller. Therefore, it is necessary for these customers to investigate why they fled, and for sales tactics to return these customers. In this way, it is a scientific sales promotion measure to determine in advance the appropriate sales tactics based on the analysis of the RFM method and to execute these sales tactics for the customer segment corresponding to each category.
  • the above is a description of the A routine described above.
  • the main purpose of this A routine is to calculate and output the RFM table shown in FIG. This is the route to determine the basic sales tactics for the customer segment that corresponds to the above.
  • the B route described below is a route for more specifically implementing the marketing tactics macro-judged in the A routine. This is the route to approach the target customers.
  • the B routine will be described. First, in Fig. 12, the purchase data is divided in advance into five categories for R, F, and M, and the purchase data is classified and stored for each category.
  • the latest purchase date is 1 to 15 days, 16 to 45 days, 46 to 90 days, 9 1-180 days, and 18 1-365 days are divided into 5 ranks, and for customers who purchased between the latest dates, that is, 1-15 days, a score cell score of 5 is given. Has been granted. Give a score of 4 to 1 in the same way.
  • point 1 for one purchase point 2 for 2 to 3 times, point 3 for 4 to 9 times, point 4 for 10 to 19 times, 20 points will be awarded 5 points or more.
  • points for less than 10,000 yen are points 1, points of less than 10,000 to 30,000 yen Points 2, points of 30,000 to less than 70,000 yen 3, points of 70,000 to less than 140,000 yen Points 4 and points 5 are given for more than 140,000 yen. With such a rating, the purchase data is stored.
  • this score is divided into five ranks for each category consisting of the horizontal axis R, the vertical axis F, and the combination of R and F, and as shown in Table 13 for each category, The score is determined. That is, R1, F1, and Ml are given a score of 1 1 1. Similarly, R 2 is given a score, and R 5, F 5, and M 5 are given a score of 5 5 5. That is, one score is given to one section of the RFM table.
  • a specific purchase data (third database) is already stored for each score when such a score and a customer ID number are combined. Therefore, when searching for customers for each category, first set the conditions. This condition setting is specifically performed on the screen shown in FIG.
  • the customer rank or RFM rank on the right side is not directly related to the present invention, but is a table in which a certain number of customers and a predetermined number of customers are ranked from conventional data, and these additional conditions may be added as necessary. You can enter ⁇
  • the customer who meets the above conditions is called together with the ID number, and this is output.
  • Figure 15 shows the customer ID number that meets the above conditions and the customer's name, address, telephone number, etc., as well as other R, F, and M rankings for that customer. Is output.
  • This table can be used to search for individual sales tactics for the customer after inspection, if necessary, and the sales tactics for each customer can be output. It is possible to implement sales tactics and promote sales, but ultimately it is necessary to verify the effectiveness of these sales tactics. In addition, the results of the verification require further verification of the sales tactics in order to link to the already established sales tactics or to establish new sales tactics. The method for that is described below.
  • FIG. 16 and FIG. 17 show examples of the above verification results.
  • a “beauty life” fair is held at a specific store, and DMs are sent out in advance. As shown in Fig.
  • Figure 17 shows the verification results.
  • Figure 17A shows the number of in-house credit cards covered by DM and other customers.
  • Figures 17B and C the overall DM collection rate is 22.2%, 21.5% for the F1 customer segment, 0.4% for the F2 customer segment, and 0 for the F3 customer segment. . 9% achievement.
  • the number of purchases based on the number of DMs sent was 8.3% for the F1 customer segment, 14.2% for the F2 customer segment, and 32.7% for the F3 customer segment. (See Figure 16). This also proves that the more frequent customers visit the guided event and purchase with a higher probability. In this way, it is possible to determine the product purchase behavior of the customer group to which the specific category belongs from the delivery of the DM, the collection rate thereof, the sales performance of the person who brought the DM, and the like. Therefore, it is also possible to judge the performance against the cost of sales activities, and finally, it is possible to change the sales tactics mentioned above. In this way, sales can be promoted by using the RFM approach.
  • the present invention sells a large number of products to a large number of customers by using the RFM method, which was known as a marketing method, in a concrete and practical manner by using a computer system.
  • a scientific business promotion method, a computer system therefor, and a program for causing a computer system to execute the business promotion method are provided.
  • the present invention can scientifically evaluate the effects of the implemented business promotion method and tactics, and can further develop a new business promotion method, so that the present invention has extremely high industrial applicability.

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Abstract

Procédé de promotion de la vente de marchandises reposant sur l'utilisation d'un système informatique destiné à promouvoir la vente de marchandises par analyse des données d'achat de marchandises relatives à des clients par la technique RFM. Ledit procédé consiste (a) à créer des données comportant les caractéristiques individuelles d'un client, (b) à organiser une première base de données d'achat dans laquelle sont mises en mémoire des données sur l'achat de marchandises par le client, (c) à organiser une seconde base de données d'achat en divisant les temps d'achats de marchandises globaux en divisions temporelles, en divisant le montant d'achat total en division de montant et en attribuant les données d'achat et le numéro d'identification du client à la division de période correspondant à la date la plus récente d'achat du client et (d) à sélectionner deux divisions parmi les divisions de période, temporelles et de montant dans la seconde banque de données d'achat, à établir un graphique en deux dimensions dont l'abscisse présente l'une des deux divisions et dont l'ordonnée présente l'autre, puis à sortir le graphique en deux dimensions.
PCT/JP2001/000290 2001-01-18 2001-01-18 Systeme et procede de promotion de la vente de marchandises WO2002057973A1 (fr)

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JP2005293130A (ja) * 2004-03-31 2005-10-20 Tsubasa System Co Ltd 理美容院用支援システム
JP2014081845A (ja) * 2012-10-17 2014-05-08 Nihon Unisys Ltd プロモーション管理システムおよびプロモーション管理用プログラム
WO2020217432A1 (fr) * 2019-04-25 2020-10-29 ヤマハ発動機株式会社 Procédé de traitement de données pour délivrer en sortie des données à utiliser pour fournir une marchandise ou un service adapté à un client et dispositif de traitement de données pour délivrer en sortie des données à utiliser pour fournir une marchandise ou un service adapté au client
JP2020184299A (ja) * 2019-04-26 2020-11-12 株式会社ミルプラトー ソリューション提案装置、ソリューション提案方法、およびソリューション提案プログラム
WO2021100089A1 (fr) * 2019-11-18 2021-05-27 シャープＮｅｃディスプレイソリューションズ株式会社 Dispositif de commande de publicité, procédé de commande de publicité et programme

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JPH0934873A (ja) * 1995-07-21 1997-02-07 Hitachi Ltd 顧客分類方法およびシステム
JPH11184926A (ja) * 1997-12-19 1999-07-09 Toshiba Tec Corp Ｐｏｓシステム及びこれに用いるプログラムを記録した記録媒体
JP2000187690A (ja) * 1998-12-24 2000-07-04 Dentsu Tec Inc 顧客価値マップの作成方法

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JPH0934873A (ja) * 1995-07-21 1997-02-07 Hitachi Ltd 顧客分類方法およびシステム
JPH11184926A (ja) * 1997-12-19 1999-07-09 Toshiba Tec Corp Ｐｏｓシステム及びこれに用いるプログラムを記録した記録媒体
JP2000187690A (ja) * 1998-12-24 2000-07-04 Dentsu Tec Inc 顧客価値マップの作成方法

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005293130A (ja) * 2004-03-31 2005-10-20 Tsubasa System Co Ltd 理美容院用支援システム
JP4602682B2 (ja) * 2004-03-31 2010-12-22 翼システム株式会社 理美容院用支援システム
JP2014081845A (ja) * 2012-10-17 2014-05-08 Nihon Unisys Ltd プロモーション管理システムおよびプロモーション管理用プログラム
WO2020217432A1 (fr) * 2019-04-25 2020-10-29 ヤマハ発動機株式会社 Procédé de traitement de données pour délivrer en sortie des données à utiliser pour fournir une marchandise ou un service adapté à un client et dispositif de traitement de données pour délivrer en sortie des données à utiliser pour fournir une marchandise ou un service adapté au client
JP2020184299A (ja) * 2019-04-26 2020-11-12 株式会社ミルプラトー ソリューション提案装置、ソリューション提案方法、およびソリューション提案プログラム
JP7348646B2 (ja) 2019-04-26 2023-09-21 株式会社ミルプラトー ソリューション提案装置、ソリューション提案方法、およびソリューション提案プログラム
WO2021100089A1 (fr) * 2019-11-18 2021-05-27 シャープＮｅｃディスプレイソリューションズ株式会社 Dispositif de commande de publicité, procédé de commande de publicité et programme
JPWO2021100089A1 (fr) * 2019-11-18 2021-05-27
JP7324861B2 (ja) 2019-11-18 2023-08-10 シャープＮｅｃディスプレイソリューションズ株式会社 広告制御装置、広告制御方法、及びプログラム

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