JP2002259667A - Numerical value customer managing system by cell group - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide data for specifying an excellent customer, predicting the estrangement of the customer (an estrangement presumption group) and effectively contributing to an object to be propagandized by dividing the present tendencies of the customers into cell groups concerning a visit date, a visit frequency and a usage money amount and grasping the positions of the customers and the movement of the group. SOLUTION: A numerical value customer management system is constituted by adding an usage money amount evaluation to the cell group which is obtained by dividing a table in nine where the visit date of the customer is made to be a Y axis and the visit frequency is to be an X axis. The system is also constituted of a visit date input process for inputting the visit date, a process for inputting visit times, a process for inputting the usage money mount, a dividing process for making respective elements into the cell group in multiple stages and a nine-division process for classifying seven-stage evaluations into three divisions, i.e., two upper and lower stages and a middle stage at each element in the three elements. A cell group evaluation is displayed at each stage of the stage classification analysis table of a usage money amount analysis table and a visit frequency analysis table and, then, the customers of the cell group are displayed at each administrative area on a map.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system for evaluating and managing customers by analyzing numerically trends of customer visits and usage amounts, and the like. The present invention relates to a numerical customer management system based on a cell group, which evaluates a group, classifies a customer who needs special care, a customer who needs care, and the like, and applies it to a DM countermeasure for a customer.

[0002]

2. Description of the Related Art In a store or the like, it is a long-awaited desire to accurately grasp the trends of customers and to effectively take measures such as the trends of visiting customers and the stopping of customers who are good customers or customers who may leave.
Often, the evaluation of customers is not constant, so even when advertising or distributing service tickets, they sometimes do not work effectively, and often do not directly affect the improvement of business results. Even if the customer is likely to be treated as a good customer, the expectation will be disappointed if the store does not accurately grasp the information. It is well understood that customer information is accumulated as electronic data, but it is not unclear how to use the data.

At present, it is difficult to find effective advertising means or advertising methods without accurately understanding the trends of customers. At first, non-discriminatory advertising has some effect, but indiscriminate advertising in ongoing advertising activities often has no effect on costs, and costs are borne by stores. Is big. Although it is difficult to judge the customer's trend or the possibility of returning to the store, it is possible to make some predictions by accurately grasping the customer's data.

[0004] In particular, it is an indispensable condition for effective advertising to know which customer group the departing customer group is specifically about. In addition, customers can be counted as 1
It is necessary to analyze the actual situation of customers at each stage by performing a zero-level evaluation, and to check the geographic distribution and trends of the specialty customers. Therefore, it has been expected that a conventional method of managing and using customer data, such as a search for a spare group that is a customer who leaves and a customer group that may be a good customer, is expected.

[0005]

SUMMARY OF THE INVENTION The present invention relates to a system relating to evaluation and management of customers, which is divided into cell groups so that current trends of customers can be accurately grasped from the date and time of visit, the frequency of visits, and the amount of use. , By ascertaining the location of the customer's existing cell group, or knowing the actual state of moving the cell group, helps identify good customers, predict customer churn (spare reserve group), and identify effective advertising targets The purpose is to provide a customer management system with numerical values from which data can be obtained.

[0006]

In order to achieve the above object, a numerical customer management system based on a cell group according to the present invention provides a numerical customer management system which manages a customer visit trend based on a visit date / time, a visit frequency, and a use amount. This is an evaluation management system, and shows a table in which the visit date and time are set on the Y axis and the visit frequency is set on the X axis.
As a divided cell group, the usage amount evaluation is added to each cell group.

[0007] Further, there is provided a customer management system based on numerical values for managing customer trends based on a visit date and time, a visit frequency, and a use amount, wherein a visit date input step of inputting customer trends into a computer as electronic data on the visit date and time; A number of visits input process of inputting the number of customer visits to a computer as electronic data, a use amount input process of inputting a single use amount to a computer as electronic data, and a visit date and time, a visit frequency, and a use amount are each performed in multiple stages. And a step of classifying the above three-element evaluations into three sections for each element and dividing it into nine sections. Grouping process in which each element is evaluated in a plurality of levels and divided into groups, and each element is evaluated in seven steps. , Evaluation two stages of upper and lower rating 2
In addition to the steps, each step is defined as one section, and the evaluation of the other parts is set as an intermediate third section.

The cell group, which is a numerical customer evaluation, is displayed for each stage of the analysis table for each stage of the usage amount analysis table and the visit frequency analysis table, and further, the customer is ranked in the order of the use amount and the visit frequency and the evaluation order of the cell group. Data can be displayed. It is also possible to display the customers of the 9 divided cell groups on a map for each administrative district at the address.

[0009]

The date and time when the customer has recently visited the store, the frequency of visits to the store over a certain period of time, and the amount of one use or the total amount of use are input to the computer and managed. Computer inputs for sales and date and time are converted into electronic data each time they are processed by the register, so to operate this system, it is sufficient to add customer data to the electronic data in the register. In order to evaluate and manage customers, they are divided into cell groups so that trends of customers up to the present can be accurately grasped from the date and time of visit, the frequency of visits, and the amount of use. Here, 7
It is divided into stages, and each is given an evaluation point. Assuming that the top cell group of each item is 7 out of 7 levels, 777, in which all elements are all 7, is the highest evaluation.

[0010] Two-dimensionally, a table in which the date and time of visit is set on the X axis and the frequency of visits is set on the Y axis is divided into nine cell groups.
The usage amount evaluation is added in each cell group. Specifically, among the above-mentioned evaluation groups, 7.6 high-order groups A and 5.4
-Classification into 3 middle-order groups B and 2.1 lower-order groups C. When expressed as a two-dimensional table, AA, AB, and A represent the latest visit date and time on the X axis and the visit frequency on the Y axis, respectively.
The cell is divided into nine cell groups of C, BA, BB, BC, CA, CB, and CC. Furthermore, by adding a usage amount evaluation to each cell group, three evaluation elements are displayed in a complex manner, and a three-dimensional evaluation table can be displayed in two dimensions. This makes it possible to accurately evaluate customers, predict the separation of customers (reserved reserve army), and enable effective advertisement targeting those customers.

It is also possible to display a cell group evaluation as a result of evaluating a customer by a numerical value in a detailed analysis table of usage amount and an analysis table of visit frequency. For example, use amount and visit frequency are 1
When the evaluation is divided into the 0-level evaluation, the cell group evaluation of the customer can be displayed in the ranking order for each level. In order to analyze the distribution of customers, numerical evaluations were conducted.
Plot the customers of the split cell group on a map,
The total can be displayed for each administrative section along the customer's address.

[0012]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A numerical customer management system using cell groups according to the present invention will be described below with reference to an embodiment shown in the drawings. FIG. 1 is a table showing the entire numerical values of a numerical customer management system using cell groups according to the present invention. FIG. 2 is a flowchart showing the steps of the numerical customer management system using cell groups. FIG. FIG. The numerical value of the numerical customer management system 10 based on the cell group includes a visit date and time 11, a visit frequency 12, and a usage amount 13. In addition, the numerical customer management system 10
It includes a store visit day input step 20, a store visit number input step 30, a use amount input step 40, a cell group division step 50, and a nine division step 60.

FIG. 1 is a table showing all the numerical values of the numerical customer management system based on cell groups.
Is represented by R (recency = newness), and the visit frequency 12 is F
(Frequency), and the usage amount 13 is represented by M (monetary). In the embodiment shown in the figure, the visit date and time (the latest visit date) are displayed on the Y axis which is the vertical axis, and the visit frequency is displayed on the X axis which is the horizontal axis. All customers who visited the store were evaluated on a seven-point scale, and the date and time of visit R
7 and a visit frequency F7. In FIG. 1, R7
Customers who have received the rating of / F7 are classified into AA in the upper right. R7 / F6, R6 / F in AA group at the same time
7, R6 / F6 are also conveniently classified into the same category. All customers are evaluated on a seven-point scale, the number of customers belonging to each cell group is input, and the percentage of the total is shown as a percentage. It is also possible to display the visit frequency F (frequency) on the vertical axis and the usage amount M (monetary) on the horizontal axis, and put R (recency = newness) which is the latest visit date and time 11 in each cell group. Is also possible. The method of displaying the RFM is not limited to this.

Next, an element of the usage amount 13 is introduced into each cell group. Thus, although it is a two-dimensional table,
Having three elements together, it is possible to more specifically grasp the trends of customers. In other words, by adding the number of customers who evaluated the use amount 13 in the AA group in seven steps, it is possible to grasp how many of the top customers have the use amount. Even if you are good at it, you can make a reflection on the fact that you need to raise the amount of money used and make a strategy for the future. In this,
The AA group is a good customer, and the closer it is to CC, the more unfavorable the customer group is for the store management.

It can be judged from the information obtained from the data that (1) customers who have a high possibility of returning to the store or reusing the store are higher as the visit date and time are newer. (3) In the case where the above (1) and (2) have the same evaluation, it is determined that the higher the cumulative usage amount, the higher the possibility of the next use. As an example, the M5 customer of the BC group on the right side of the table only visits the store occasionally, but if you come to the store, you can evaluate that it is a customer who can expect reasonable sales. And so on.

Further, by plotting the location of the customer on a map as shown in FIG. 6, it is possible to determine in which district the customer resident is relatively good. In addition, a usage method of selecting a district and examining the opening of a new store can be considered.

FIG. 2 is a flowchart showing the operation procedure of the numerical customer management system 10 using the cell group of the present invention. The store visit day input step 20 is a step of inputting the day when the customer visited the store as electronic data. Simply enter the date of visiting the store, but if the store is directly linked to sales, the store will automatically issue the date and time when issuing the receipt issued by the store from the register and store it as electronic data. It is possible. If the visit is not a product or service that is always linked to purchase, it is necessary to input the date of each visit as electronic data by another operation. In this case, means for confirming the same person is required, and a magnetic strap, a card with a barcode, and the like are required.

The store visit number input step 30 is a count of the number of times the customer has visited the store, and is inputted for each visit. If a visit to a store is always linked to purchases or expenses as described above, it is possible to automatically record the visit when a receipt is issued from a register. If the visit is not always linked to the purchase, it is necessary to input each visit as electronic data by another operation, and an electronic card or the like is required to confirm that the visitor is the same person.

The use amount input step 40 is for inputting the amount paid by the customer. If the cash amount is linked to the cash register, the use amount is always input each time a receipt is issued to the customer. The troublesome work can be saved. The usage amount is a concept including a single usage amount and a total usage amount up to the present, and it is also possible to simply divide the total usage amount by the number of visits to calculate an average value of one usage amount.

The cell group sorting step 50 stores a lot of data on the visit date and time, the visit frequency and the use amount input in the above-mentioned steps, by using the visit date and time (R), the visit frequency (F) and the use amount (M), respectively. This is a process of evaluating each data in a plurality of stages and classifying the data. In the embodiment shown in FIG. 1, each value is divided into seven grades in the cell group dividing step. As the evaluation, 7 is the highest customer, and the evaluation is sequentially given up to 1. Although it is divided into a plurality of stages, it may be roughly divided into three or more detailed stages. 3 elements each 7
By combining the evaluation categories into stages, it is possible to create 343 different categories when combined. For example, 77
7 is the best customer and is the target of the service. 577 is a bit far off recently but is good at it. 277 requires immediate action because there is some reason not to visit the store.

In the nine-division step 60, the values of the visit date and time (R), the visit frequency (F), and the amount of use (M) divided into seven stages as described above are divided into nine equal parts (R) in FIG. This is a step of fitting into the table of the relationship F) and further adding data on the amount of use (M) to each of the nine sections. In this embodiment, the visit date and time (R) and the visit frequency (F) are divided into seven stages.
Has been reclassified into three categories. Although any number of methods are conceivable, in this embodiment, the data of the evaluations of 7 and 6 are included in the first group, and the data of the evaluations 5 and 3 are included in the second intermediate group. Is assigned the data of the last two and one evaluations. By classification, visit date and time (R) and visit frequency (F)
Are shown in FIG. 1 as AA, AB, AC, B
A, BB, BC, CA, CB, and CC are divided into nine cell groups. Each of the divided cell groups is given a seven-level evaluation on the amount of use (M). Also, AA
It is also possible to capture changes in the number of people in the group in chronological order and show the change status only with numerical data (for example, AA current month: 20 people, last month's 15 people, etc.), but if the number of people increases, smile It is also conceivable that the state of the customer can be grasped at a glance by a picture or a diagram, such as indicating an increasing trend of good customers with a niconico mark, or expressing a dissatisfied state or a crying face mark when decreasing.

With the above configuration, the data divided into 9 parts by this system are good customers and trusted customers group (for example, AA), and the frequency of visits to the store was high, but dissatisfied with a slight loss of interest. It is possible to evaluate a group of customers (BA), a group of untrusted customers (CA) who came well in the past but were far away, and a group of test customers (AC) which have recently started coming with new customers. Further, since the usage amount (M) is also added, it is possible to identify a customer who has a small usage number but has a high usage amount if the number of visits is small.

As shown in FIG. 3, as for correspondence to each cell group, personal services, anniversary notices, individual proposals and monitoring of new products, personal letter visits to AA (reliable customers). For AB (credit customers), sample fairs, request menus, sample privileges, handwritten direct mail, for AC (test customers), benefits for the next visit, discount coupons, etc. A coping method is conceivable.

As still another embodiment of the present invention, there is a configuration in which a cell group is introduced into a usage amount analysis table or a store visit frequency analysis table. A case in which a cell group obtained as a result of evaluating customers by numerical values is introduced into, for example, a usage amount analysis table will be described in detail. The customer's sales at each store for the current term include the amount of use each time they visit the store and the total amount of use for the current period. All customers are ranked in the order of sales, and when this is analyzed in decyl, it is equally divided into ten as shown in FIG. As a result, the customer segment is divided into ten. This means that 1 in 10 of the total number of customers is classified as a top group. Furthermore, since a cell group is assigned to each customer, the customer as shown in FIG. 5 can be evaluated by evaluating the top 10 customers in the cell group by the cell group.

Thus, while the sales are in the top 10% of the top 10%, the fact that the current customer status is different is displayed at a glance. For example, a customer who has visited the store recently, frequently visits the store, and uses a large amount of money. In addition, it is possible to distinguish customers who have a large usage amount but a low frequency of visiting the store or customers who have a high frequency of visiting the store but have a relatively low usage amount per transaction. In addition, it is clear that customers who need to visit the store recently have dropped their attention. In addition, by making this table, the former regular customers who need to encourage returning customers can be identified at a glance.

As still another embodiment of the numerical customer management system using cell groups according to the present invention, as shown in FIG. 6, the customers of the cell group divided into nine are displayed on the map for each administrative district at the address. Becomes possible. As a result, the distribution of customers and the opening of new stores can be considered, and the areas and priority areas requiring measures can be more clearly identified, which can be used for future store development.

[0027]

As described above, according to the numerical customer management system based on the cell group, (1) the latest visit date can be determined, the total number of visits can be determined,
The biggest advantage is that you can know the total usage amount or the average usage amount per transaction. Detailed analysis is possible wherever there is data. It is up to each store how to use the analysis results, and it can be used for strategy meetings and sales promotions, as well as grasping customer mobilization trends for each store. As an example, there is an advantage that it is useful for stabilizing a customer, performing a special service by specifying a good customer, preventing a customer from leaving, or specifying a target to be effectively advertised. Also, the analysis table can be browsed at any time and from any place via the Internet, and information can be managed in real time.

(2) Electronic data can be easily accumulated, stored, and used by operation of an instrument for inputting a receipt.
In addition, the data can be divided into three elements and can be three-dimensionally evaluated instead of two-dimensionally, which is epoch-making. 3 It is not just a multi-stage evaluation, but it is consistent with the actual economic activity that evaluates the data of visit date and time (R), visit frequency (F) and usage amount (M) separately for each cell group,
It is possible to easily catch the departure preparatory group and the like and to effectively carry out advertisement.

4. Since the evaluation order by cell group can be added to the ranking order of the usage amount and the visit frequency, it can be used as more effective customer management data. 5. In addition, since the customers of the cell group divided into nine can be appropriately displayed on the map, the distribution of the customers can be visually examined in terms of quantity and quality. It can be used effectively when considering regional development.

[Brief description of the drawings]

FIG. 1 is a diagram of a numerical customer management system using cell groups according to the present invention.

FIG. 2 is a flowchart showing the flow of a numerical customer management system using cell groups.

Fig. 3 Example of measures for each cell group

[Figure 4] Sales Decyl Analysis Table

[Figure 5] Sales decyl analysis table with cell group introduced

[Fig. 6] Region map with cell groups introduced

[Explanation of symbols]

 Reference Signs List 10 Numerical customer management system by cell group 11 Visit date and time 12 Visit frequency 13 Usage amount 20 Visit date input process 30 Visit count input process 40 Usage amount input process 50 Cell group classification process 60 9 division process

Claims (5)

[Claims] 1. A customer evaluation management system based on numerical values for managing customer visit trends based on visit date / time, visit frequency, and usage amount, wherein a cell in which a visit date / time is set on the Y axis and a visit frequency is set on the X axis is divided into nine cells. Numerical customer management system based on cell groups, characterized in that a usage amount evaluation is added to each cell group as a group 2. A customer management system based on a numerical value for managing customer trends based on a visit date and time, a visit frequency, and a usage amount, comprising: a visit date input step of inputting customer trends into a computer as electronic data on the visit date and time; Entering the number of visits to the computer as electronic data, entering the number of visits to the computer, entering the amount of use to the computer as electronic data, and evaluating the visit date and time, visit frequency, and use amount at each of multiple levels A cell group dividing step of dividing the plurality of evaluations of the above three elements into three sections for each element and dividing it into nine parts, and numerical customer management by a cell group. system 3. The cell group dividing step of evaluating a visit date and time, a visit frequency, and a use amount in each of a plurality of levels, and performing a grouping step in which each element is evaluated in seven steps; 3. The cell group according to claim 2, further comprising: a step and two lower-level evaluations, each of which is a single section, and wherein the evaluation of the other parts is a third section located in the middle. Numerical customer management system 4. The cell group, which is the numerical customer evaluation, is displayed for each stage of the use amount analysis table or the analysis table for each stage of the store visit frequency analysis table. 2. The numerical customer management system according to claim 1, wherein the customer data is displayed in the order of evaluation. 5. The cell group-based numerical customer management system according to claim 1, wherein the customer of the cell group divided into nine is displayed on a map for each administrative division of an address place. Numerical customer management system