JP4750573B2 - Calculation method, calculation device, and calculation program - Google Patents

Description

The present invention relates to a calculation method, a calculation device, and a calculation program , and more particularly to a calculation method, a calculation device, and a calculation program for calculating an index for evaluating a product advertisement or a product.

  In order to urge the user to purchase products displayed in the store, the store owner generally takes various measures such as issuing a product advertisement or changing the product lineup. As important information that can be used as a basis for deciding which measures should be taken, what is the current state of the product, that is, whether or not the current advertisement is effective, and purchases are expected in the future. It is necessary to grasp whether the product is a product (whether it is an attractive product) or the like.

In particular, evaluating the effect of advertising when a new product is introduced and making a decision such as a change greatly affects the sales of the product and is an important issue for both the manufacturer and the seller of the product.
Here, as a method for grasping the information on the product, a method for grasping information based on the information POS data about the actually purchased product, or information on the product not purchased (information on sales opportunity loss) is collected. A method for grasping information is known (for example, see Patent Document 1).
JP 2001-331875 A

  However, with such a method, it is difficult to grasp more specific information about advertisements and products, such as whether the current advertisement is effective or whether the product is expected to be purchased in the future. There was a problem of being.

The present invention has been made in view of these points, and an object of the present invention is to provide a calculation method, a calculation device, and a calculation program for calculating an index for accurately grasping the effect of an advertisement on a product.
Another object of the present invention is to provide a calculation method, a calculation device, and a calculation program for calculating an index for accurately grasping the attractiveness of a product.

  In the present invention, in order to solve the above-mentioned problem, in a calculation method for calculating an index for evaluating a product advertisement, the number of shoppers who have entered a store and a predetermined product department among the shoppers are predetermined. Receiving information on the number of stayers who have stayed for more than an hour and the number of immediate purchasers who have purchased the product after staying in the product store for a time shorter than the predetermined time, And the number of immediate purchasers of the product is calculated as the number of product interest holders who are considered interested in the product among the store visitors, and the product interest with respect to the number of shoppers A calculation method characterized by calculating a ratio of the number of holders is provided.

  According to such a calculation method, when information on the number of shoppers, the number of stayers, and the number of immediate purchasers is received, the sum of the number of stayers and the number of immediate purchasers Is calculated as the number of merchandise interest holders who are thought to be interested in the merchandise among the shoppers, and then the ratio of the number of merchandise interest holders to the number of shoppers is calculated.

  Further, in the present invention, in order to solve the above-described problem, in a calculation method for calculating an index for evaluating a product, the number of shoppers who have entered the store and a predetermined product department among the shoppers. The number of product purchasers who have purchased the product, the number of stayers who stayed at the product sales floor for a predetermined time or more among the shopkeepers, and stay for a shorter time than the predetermined time at the product sales floor among the shoppers. And accepting information on the number of immediate purchasers who have purchased the product, and the sum of the number of stayers and the number of immediate purchasers is interested in the product among the shoppers. There is provided a calculation method characterized by calculating the number of possible product interest holders and calculating the ratio of the number of purchasers who have purchased the product to the number of product interest holders.

  According to such a calculation method, when information on the number of shoppers, the number of product purchasers, the number of staying people, and the number of immediate product purchasers is received, The sum of the number of buyers is calculated as the number of product interest holders who are likely to be interested in the product, and then the ratio of the number of product buyers to the number of product interest holders is calculated. The

  Further, in the present invention, in order to solve the above-described problem, in a calculation method for calculating an index for evaluating a product, the number of shoppers who have entered the store and a predetermined product department among the shoppers. Receives information regarding the number of product purchasers who have purchased products and the number of product purchasers who have stayed at the product sales floor for a time shorter than a predetermined time among the product purchasers, and the products with respect to the number of product purchasers There is provided a calculation method characterized by calculating a ratio of the number of immediate purchasers.

  According to such a calculation method, when information on the number of shoppers, the number of product buyers, and the number of product immediate purchasers is received, the number of product immediate purchasers relative to the number of product purchasers is calculated. A percentage is calculated.

  In addition, in order to solve the above-described problems, the present invention is a program for causing a computer to execute a calculation method for calculating an index for evaluating a product advertisement. And the number of stayers who stayed at a predetermined merchandise store for a predetermined time or more among the shoppers, and purchased the products by staying at the product shop among the shoppers for a time shorter than the predetermined time. Receives information on the number of immediate purchasers of the product, and sums the number of stayers and the number of immediate purchasers of the product among those who are interested in the product among the shoppers. There is provided a program characterized in that processing is performed to calculate a number and calculate a ratio of the number of merchandise interest holders to the number of shoppers.

  If the computer is operated according to such a program, the processing related to the above-described calculation method is realized on the computer.

According to the present invention, by calculating the ratio of the number of merchandise interest holders to the number of shoppers, the effect of the merchandise advertisement for the merchandise can be grasped easily and accurately.
Further, according to the present invention, it is possible to easily and accurately grasp the quality of the product package (appearance: shape, design, etc.) by calculating the ratio of the product purchaser to the number of product interest holders. .

  Furthermore, according to the present invention, it is possible to easily and accurately evaluate the quality of the product itself by calculating the ratio of the number of product immediate purchasers to the number of product purchasers.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is a plan view of a store to which the calculation system of the embodiment is applied.
Corresponding to the sensor mat 2 installed in the store 1 and the product mating section 3 on which products are displayed, and the merchandise display section 3. Sensor mat 4 installed at the site to be used, cameras 51, 52, 53 that mainly photograph the flow of the customer after entering the store (arrows in FIG. 1), and a POS register (POS register) for accounting for the goods 6 are provided.

The sensor mat 2 is laid out at predetermined intervals (for example, every 1 cm ² ), and a plurality of weight sensors 21 that detect a change in weight, that is, a customer's passage, and detection information detected by each weight sensor 21 are transmitted to the network 10. And a wireless transmission unit (not shown) for transmitting to a PC (personal computer) 40 via the computer. The network 10 is not limited to a wireless network, and may be a wired network.

  The merchandise display section 3 is provided with a sheet-like sensor shelf 31 that detects a change in weight. In FIG. 1, a plurality of products are displayed on the sensor shelf 31. The sensor shelf 31 includes a weight sensor having the same function as the sensor mat 2 and a wireless transmission unit, and when detecting a change in weight in units of individual products, that is, taking out a product from a display unit by a customer, The wireless transmission unit transmits the detection information to the PC 40 via the network 10.

  The sensor mat 4 detects a customer who stops at the product display unit 3, passes in front of the product display unit 3, or stops (stays) in front of the product display unit 3. Note that the configuration (structure) of the sensor mat 4 is substantially the same as that of the sensor mat 2, and thus the description thereof is omitted.

Detection information detected by each weight sensor of the sensor mat 4 is transmitted to the PC 40 in time series.
In the example of FIG. 1, the sensor mat 2 and the sensor mat 4 are illustrated as separate sensor mats, but the present invention is not limited to this, and the sensor mat is installed in the entire store, and each customer's You may grasp the stay in front of each product shelf and the flow line in the store. In this case, the flow line of the customer is measured by the reaction of a sensor mat (for example, the entrance portion, the front portion of the shelf to which the product A belongs, or the front of the POS register 6) laid at the site of interest. Each of the cameras 51 to 53 is installed on a ceiling portion of the store 1, and has a transmission unit (not shown) that transmits the obtained imaging signal, that is, an image including a customer's flow line to the PC 40.

  Each of the cameras 51 to 53 detects the customer by, for example, photographing the customer's head by a conventionally known method, and the transmission unit transmits the detection result to the PC 40. Specifically, the camera 51 images a store entrant and a store exit passing through the sensor mat 2, and the camera 52 captures a customer after entering the store passing through the sensor mat 4 (in front of the sensor shelf 31). The camera 53 photographs a customer (product purchaser) passing through the POS cash register 6. By using these cameras 51 to 53 together with the sensor mats 2 and 4 and the sensor shelf 31, the detection accuracy can be improved. Note that the cameras 51 to 53 may be omitted.

  The POS cash register 6 includes a POS (Point Of Sales) 61, and the customer's product purchase information including the number of each product purchased by the customer (the number of product purchasers) and sales date / time information is transmitted via the network 10. To the PC 40.

  The sensor mat 2, the sensor shelf 31, the sensor mat 4, the cameras 51 to 53, and the POS 61 constitute a main part of a detection system that detects a flow line of a customer (where a person is and what kind of movement). Yes. Note that the detection system may be realized by other means such as an infrared detection means as another detection means for detecting the trend of goods and shoppers.

  The PC 40 includes a storage unit 42 that stores (stores) information transmitted from the CPU 41, the sensor mat 2, the sensor shelf 31, the sensor mat 4, and the cameras 51 to 53, an input unit 43, and an output unit 44. And have. FIG. 2 is a functional configuration diagram of the PC 40. The PC 40 is connected in a communicable manner with each detection system means installed in the store via the network, receives the measurement result transmitted from each detection system means, and registers it in the storage means 42.

The CPU 41 includes data management means 411, interest level calculation means 412, attractiveness calculation means 413, fixing degree calculation means 414, and result display means 415.
The data management unit 411 is a program to be executed by the CPU 41 for registering data received by the PC 40 or input from the input unit 43 in the storage unit 42 and reading the registered data. Each detection system means transmits a value as a detection result to the PC 40. The data management unit 411 summarizes the received data for each predetermined period and for each product to be focused on as a processing target, and registers the data in the storage unit 42.

  When the data management means 411 is executed by the CPU 41, the CPU 41 judges the moving direction of the customer based on the detection information transmitted from the sensor mat 2, and enters the store 1 and stores from the store 1. The number of store openings is counted and registered in the storage means 42 as the number of store visitors. Further, the CPU 41 counts the change in the quantity of the product (the quantity of the product taken out from the product display unit 3) in the product unit (for each product type) based on the change in the measured weight transmitted from the sensor shelf 31.

  In addition, the CPU 41 defines “the number of people staying before the product”, “the number of product purchasers”, “the number of customers who immediately purchased the product”, and “the number of interested customers” by using each piece of information stored in the storage unit 42. . Details of each value will be described later with reference to FIG.

  The degree-of-interest calculation unit 412 is a program to be executed by the CPU 41 that calculates the degree of interest of the customer for the product of interest based on the data read from the storage unit 42 by the data management unit 411.

  The attractiveness calculating means 413 is a program to be executed by the CPU 41 that calculates the attractiveness to the customer for the product of interest based on the data read from the storage means 42 by the data management means 411.

  The fixing degree calculation unit 414 is a program to be executed by the CPU 41 that calculates the fixing degree of the customer for the product of interest based on the data read from the storage unit 42 by the data management unit 411.

  The result display unit 415 displays the results calculated by the interest level calculation unit 412, the attractiveness calculation unit 413, and the fixing level calculation unit 414 in a form such as a graph or a table, and instructs the output unit 44 to output the result. This is a program to be executed by the CPU 41.

  The input means 43 is a means for a user of this system to input an instruction to the PC 40, such as a keyboard, a mouse, and a microphone. The output means 44 is a display, a printer, a speaker, etc., and the PC 40 directs data to the user. It is means for outputting.

  FIG. 3 is an example of data stored in the storage means 42. Based on information received from each detection system unit, the data management unit 411 calculates and registers the number of stayers, the number of purchasers, and the number of immediate purchasers for each predetermined period and for each product of interest as a processing target. The number of persons is detected every predetermined period that can be arbitrarily set by the user of the system.

“Number of customers” represents the total number of customers who visited the store during a predetermined period, and is a value measured by the sensor mat 2 and transmitted to the PC 40.
“The number of customers before the product” is the number of customers who have stayed in the sensor mat 4 installed in front of the product display unit 3 on which the product of interest is displayed for a predetermined period (time t1) or more (cumulative). It is. The “number of people staying before the product” can be counted based on the detection information from the sensor mat 4 and the imaging signal from the camera 52.

  The “number of merchandise purchasers” is the number (total) of customers who took the product of interest from the merchandise display unit 3 and left the sensor mat 4. This number is the number of customers who have detected the removal of the product of interest in the sensor shelf 31 and have left the sensor mat 4 without moving the product back to the product display unit 3 (having moved the product). Be counted.

  “Number of immediate purchasers” is the number of customers (cumulative total) among the above-mentioned “number of purchasers” who have stayed on the sensor mat 4 for a predetermined time or less (time t2 shorter than time t1). . This number is a value calculated from the customer residence time detected by the sensor mat 4 installed in the product display unit 3, the customer flow line measured by the camera 52, and the sales information registered in the POS 61. is there.

  Specifically, for a customer who has detected staying for less than a predetermined time in the sensor mat 4 in front of the product display section 3 where the product of interest is displayed, whether the customer stayed in front of the POS register 6 according to the flow line data (that is, payment) If the product of interest is included in the sales information of the POS 61 registered at the time when the customer stopped before the POS register 6, the customer is counted as a purchaser immediately. The customer who purchased the product without stopping for a certain time (time t2) such as 30 seconds before the product display unit 3 decided to purchase the product from the beginning (purchased the product for the purpose). Can be considered a customer.

  In addition, in counting the number of product purchasers, an example is given in which the case where the product is taken out from the product shelf and the customer moves from the corresponding product sales floor in that state is counted as purchase. However, in actuality, since the time when the product is finally settled at the cash register is the purchase, if strictly expressed, the “number of product purchasers” in the present embodiment is the “number of product temporary purchasers”. In the present embodiment, it is assumed that the difference between the temporary purchase and the purchase is small, and the state of the temporary purchase (when the product is taken out from the product shelf and the customer moves as it is) is regarded as purchase. If the sales information related to the customer who has taken out and moved the product and does not include information on the product, the customer may make corrections such as not counting the number of purchasers.

  The number of stayers is equal to the sum of the number of people who purchased the product (the number of purchasers) after the stay and the number of people who did not purchase the product. The number of purchasers is equal to the sum of the number of people who have purchased the product after having stopped for a predetermined time or more and the number of people who have purchased the product after having stopped for less than a predetermined time (the number of immediate purchasers). In addition, the number of people indicated by the sum of the number of stayers and the number of immediate purchasers can be regarded as a customer who has shown some interest in the product, regardless of whether or not the product has been purchased. Sometimes referred to as interested customer.

  FIG. 4 is a flowchart showing processing for calculating an index for accurately grasping the effect of the advertisement of the present invention. In this process, the CPU 41 uses the “number of customers before product”, “number of product purchasers”, and “number of product immediate purchasers” to “product interest”, “product attractiveness”, and “product fixing degree”. Are calculated (calculated). By performing this process every predetermined period, the system detects consumer trends for the product to be processed and evaluates the advertisement.

  First, the interest level calculation means 412 calculates a “product interest level” (step S1). “Product interest” is defined by (“Number of customers staying before product” + “Number of customers who purchased the product immediately”) / “Number of customers visiting the store”, and mainly evaluates the effect of the advertisement after advertising the product. It is an indicator.

  It is thought that the customer's interest in the product is improved when the advertisement of the product (for example, an advertisement using a wide-area media such as a television / newspaper and an advertisement in a store / store (signboard, poster, POP, etc.)) is performed. Due to this, the number of people staying in front of the product shelves where the product is displayed or the product is displayed to determine the product is the number of people staying before the product, or a specific product It is considered that the “number of immediate purchasers”, which is the number of people who have left the product in front of the product shelves and left without being lost because they have decided to purchase, that is, the purchase, is increasing. Those who stay before the product and those who immediately purchase the product can be regarded as customers who are interested in the product in some form, and the sum of these can be called the “number of interested customers”.

  Therefore, in step S1, based on the number of pre-product stayers, the number of product purchasers, and the number of store visitors calculated by the data management means 411, (“number of staying before product” + “number of immediate purchasers of product”) / The “number of customers”, that is, the ratio of the number of interested customers to the number of customers is calculated.

  For example, when calculating the degree of interest for the period from 11:00 to 11:59 on January 1, 2006 for product A, refer to the data shown in FIG. As a ratio, (5 + 1) / 20 is calculated to obtain a value of 0.3. When the interest level calculation unit 412 calculates the interest level in this manner, the interest level calculation unit 412 registers the value calculated as the product interest level data of the corresponding product and the corresponding period in the storage unit 42.

Next, the CPU 41 determines whether or not the “commodity interest level” is equal to or greater than a predetermined value (step S2).
After advertising the product, first calculate the “product interest”, and if the “product interest” is increasing, it can be determined that the advertising effect is high (continues) When the “product interest level” tends to decrease, it can be determined that the advertising effect is low.

  Therefore, in step S2, the product interest level for the previous period that has already been calculated and stored is set as a predetermined value, and it is determined whether the product interest level calculated in step S1 is greater than or equal to the predetermined value. If it is equal to or greater than the predetermined value (Yes in step S2), it means that the percentage of customers interested in the product is increasing, and if it is small (No in step S2), the percentage of customers interested in the product. Means that is decreasing. In this way, by comparing the previous calculated value with the current calculated value, it is possible to grasp the trend of increasing or decreasing the product interest level. By calculating the product interest level in this way, It is possible to easily and accurately determine the effect of the advertisement on the product.

  When the “product interest level” is smaller than the predetermined value (No in step S2), the process proceeds to step S6, the calculation result of the “product interest level” is displayed, and the calculation process is terminated. On the other hand, when the “product interest level” is equal to or greater than the predetermined value (Yes in step S2), the CPU 41 calculates the “product attractiveness” (step S3).

  When the advertisement is effective (when the “product interest level” is equal to or higher than a predetermined value), the possibility that the customer who saw the advertisement is interested in the product increases. In particular, when the product is a new product, there are many people who do not know the contents of the product, and it is often considered whether or not to purchase the product by appearance. Therefore, in order to calculate an index for evaluating whether the product package is good or bad, the attractiveness calculating means 413, in step S3, reads from the storage means 42 the “number of product purchasers”, the “number of people staying before product”, and the “immediate purchase”. The number of customers is read out and expressed by the number of buyers / (“number of customers before the product” + “number of customers who purchased the product immediately”), that is, the number of customers who actually purchased the product against the number of interested customers. The “product attractiveness” that is the ratio of

  For example, when calculating the attractiveness for the period from 11:00 to 11:59 on January 1, 2006 for product A, refer to the data shown in FIG. Calculate 3 / (5 + 1) to obtain a value of 0.5. When the attractiveness calculating unit 413 calculates the attractiveness in this way, the attractiveness calculating unit 413 registers the value calculated as the product attractiveness data of the corresponding product and the corresponding period in the storage unit 42.

  As the “product attractiveness” is higher, as a result of interest in the product (that is, staying in front of the product), it can be determined that the percentage of purchasers is large, that is, the package of the product is attractive. Further, it can be determined that the lower the “product attractiveness” is, the less preferable the current package is. By calculating the product attractiveness in this way, it is possible to easily and accurately determine whether the product package (appearance) is attractive.

  Next, the attractiveness calculating means 413 determines whether or not the “commodity attractiveness” is equal to or greater than a predetermined value (step S4). When the “product attractiveness” for the previous period that has already been calculated and stored is a predetermined value, and the “product attractiveness” calculated in step S3 is smaller than the predetermined value (No in step S4), the process proceeds to step S6. Then, the calculation result of “product interest level” and “product attractiveness” is displayed, and the calculation process is terminated. On the other hand, when the “product attractiveness” is equal to or greater than the predetermined value (Yes in step S2), the CPU 41 calculates the “product fixing degree” (step S5).

  In addition to the attractiveness of the product package (appearance) (when the “product attractiveness” is greater than or equal to a predetermined value), the value of the product itself, for example, if the product is food, taste or if the product is a device If ease of use, cost performance, etc. are excellent, repeaters (re-purchasers) are considered to increase. These repeaters can be determined to purchase the product without hesitation when visiting the store. Therefore, in order to calculate an index for determining whether or not the customer has visited the store with the purpose of purchasing the target product, the fixing degree calculating means 414 reads “number of immediate purchasers” and “from the storage means 42” in step S5. The value of “the number of product purchasers” is read out and expressed by “the number of product purchasers” / “the number of product purchasers”, that is, the ratio of the customers who have purchased the product for the purpose of purchasing the product. “Fixing degree” is calculated.

  For example, when calculating the fixing degree for the period from 11:00 to 11:59 on January 1, 2006 for the product A, refer to the data shown in FIG. , 1/3 is calculated to obtain a value of 0.3. When the fixing degree is calculated in this way, the fixing degree calculating unit 414 registers the value calculated as the fixing degree data for the corresponding product and the corresponding period in the storage unit 42.

  It can be determined that the higher the “product fixing degree” is, the more buyers of the product, the more valuable the product itself. Further, it can be determined that the lower the “product fixing degree”, the fewer repeaters and the lower the value of the product itself.

By calculating the product fixing degree in this way, it is possible to easily and accurately determine whether the product has its own value.
When the processing from step S1 to step S5 is completed, the result display unit 415 causes the output unit 44 to display one or more of “product interest level”, “product attractiveness level”, and “product fixing level” (step S41). S6) The process is terminated. In step S6, the result obtained in any of steps S1 to S5 may be displayed. For example, when a decreasing tendency of the merchandise interest level is detected in step S2, the merchandise interest level state is displayed in step S6. When a decreasing tendency of the product attractiveness is detected in S4, the state of the product attractiveness may be displayed.

  FIG. 5 is a line graph representing the change tendency of the value output from the result display means 415. In FIG. 5, as an example, the change (transition) of “product interest level” for 4 hours from 9:00 to 13:00 increases “product interest level” from 0.3 at 9:00 to 0.5 at 13:00. An example is shown. By presenting such a graph, it becomes possible to let the user of this system know the change tendency of the value at a glance.

  The user who is notified of the effect determination result in step S6 reviews the advertisement, changes the layout of the store 1, for example, if the “product interest” is low based on the notified content, When the “degree” is low, for example, the necessity of reviewing the package can be recognized, and when the “product fixing degree” is low, for example, the necessity for reviewing the contents (contents) of the product can be recognized.

  The “product attractiveness” is calculated when the “product interest” is a predetermined value or more, and the “product fixing degree” is calculated when the “product attractiveness” is a predetermined value or more. However, the product attractiveness and the product fixing degree may be calculated even when the value is not equal to or greater than the predetermined value.

  According to this system, “product interest level”, “product attractiveness level”, and “product retention level” can be calculated at any time (every time period) as necessary. Can be applied.

  Note that the calculation timings of “product interest level”, “product attractiveness level”, and “product retention level” are not particularly limited, but “product interest level” is preferably calculated on the first day of advertisement, for example. . For example, when an advertisement for a certain product is started from 12:00, as shown in the data example of FIG. 3, the product interest level that was 0.3 in the period from 11:00 to 11:59 is from 12:00. In the period up to 12:59, when it rises to 0.5, it can be considered that the customer's interest in the product is raised by the advertisement. Thereby, a more accurate “product interest level” can be calculated, and the quality of the advertisement can be evaluated.

  Of course, the calculation timing is not limited to this, and when the data management unit 411 registers the data for each predetermined period received from each detection system unit in the storage unit 42, the product interest level, the product attractiveness level, and the product fixing level are registered. It is also possible to calculate the degree and determine the variation tendency of each value.

  In the present embodiment, when any one or more of “product interest level”, “product attractiveness level”, and “product fixing level” reach a predetermined value, the CPU 41 notifies that fact. It is preferable to be configured to do so. Thereby, the notified user can quickly take measures according to the contents. In addition, it is possible to evaluate and verify pre-developed marketing measures, and the following effective measures can be formulated easily and quickly.

  The calculation method and program of the present invention have been described based on the illustrated embodiment. However, the present invention is not limited to this, and the configuration of each part is of an arbitrary configuration having the same function. Can be substituted. Moreover, other arbitrary structures and processes may be added to the present invention.

In addition, the present invention may be a combination of any two or more configurations (features) of the above-described embodiments.
(Supplementary note 1) In a calculation method for calculating an index for evaluating a product advertisement,
The number of shoppers who have entered the store, the number of stayers who have stayed at a predetermined product department for a predetermined time or more among the shoppers, and shorter than the predetermined time at the product department among the shoppers. Receive information about the number of immediate purchasers who have spent time and purchased products,
The sum of the number of stayers and the number of immediate purchasers is calculated as the number of product interest holders who are considered interested in the product among the store visitors, Calculating a percentage of the number of product interest holders,
A calculation method characterized by the above.

(Appendix 2) Further accepting information on the number of product purchasers who have purchased the product at the product sales floor among the shoppers,
The calculation method according to appendix 1, wherein, when the ratio is equal to or greater than a predetermined value, a ratio of the number of the product purchasers to the number of the product interest holders is calculated.

  (Additional remark 3) When the ratio of the number of the said product purchasers with respect to the number of said product interest holders is more than predetermined value, the ratio of the number of the said goods immediate purchasers with respect to the number of said product purchasers is calculated, It is characterized by the above-mentioned. The calculation method according to Supplementary Note 2.

(Supplementary note 4) The calculation method according to supplementary note 1, wherein when the ratio reaches a predetermined value, the fact is notified.
(Supplementary Note 5) In a calculation method for calculating an index for evaluating a product,
The number of shoppers who have entered the store, the number of product purchasers who have purchased products at a predetermined product department among the shopkeepers, and the stay that has remained at the product department among the shoppers for a predetermined time or more Receiving information on the number of buyers and the number of immediate purchasers who have purchased the product while staying at the product store among the shoppers for a time shorter than the predetermined time,
The sum of the number of stayers and the number of immediate purchasers is calculated as the number of product interest holders who are considered interested in the product among the shoppers, and the number of product interest holders. Calculating the ratio of the number of product buyers to
A calculation method characterized by the above.

(Supplementary note 6) The calculation method according to supplementary note 5, wherein when the ratio reaches a predetermined value, the fact is notified.
(Supplementary note 7) In a calculation method for calculating an index for evaluating a product,
Receiving information on the number of product purchasers who have purchased products at a predetermined product store and the number of product buyers who have stayed at the product store for a time shorter than a predetermined time among the product buyers;
Calculating the ratio of the number of immediate purchasers to the number of purchasers;
A calculation method characterized by the above.

(Supplementary note 8) The calculation method according to supplementary note 7, wherein when the ratio reaches a predetermined value, the fact is notified.
(Supplementary note 9) In a calculation system for calculating an index for evaluating a product advertisement,
The number of shoppers who have entered the store, the number of stayers who have stayed at a predetermined product department for a predetermined time or more among the shoppers, and shorter than the predetermined time at the product department among the shoppers. Receiving means for receiving information on the number of immediate purchasers who have purchased the product after a long period of time;
The sum of the number of stayers and the number of immediate purchasers is calculated as the number of product interest holders who are considered interested in the product among the store visitors, Calculating means for calculating a ratio of the number of product interest holders;
A calculation system comprising:

(Supplementary Note 10) A program for causing a computer to execute a calculation method for calculating an index for evaluating a product advertisement.
The number of shoppers who have entered the store, the number of stayers who have stayed at a predetermined product department for a predetermined time or more among the shoppers, and shorter than the predetermined time at the product department among the shoppers. Receive information about the number of immediate purchasers who have stayed for hours and purchased the product,
The sum of the number of stayers and the number of immediate purchasers is calculated as the number of product interest holders who are considered interested in the product among the store visitors, Calculating a percentage of the number of product interest holders,
A program characterized by causing processing to be performed.

It is a top view of a store to which the calculation system of an embodiment is applied. It is a functional block diagram of PC. It is an example of the data which the memory | storage means has stored. It is a flowchart which shows the process which calculates the parameter | index which grasps | ascertains exactly the effect of the advertisement of this invention. It is a line graph showing the change tendency of a value which a result display means outputs.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Store 2, 4 Sensor mat 3 Goods display part 6 POS cash register 10 Network 21 Weight sensor 31 Sensor shelf 40 PC
41 CPU
42 storage means 43 input means 44 output means 51, 52, 53 camera 61 POS
411 Data management means 412 Interest calculation means 413 Attractiveness calculation means 414 Fixation degree calculation means 415 Result display means

Claims (5)

In a calculation method for calculating metrics for evaluating product ads,
Computer
The number of shoppers who have entered the store, the number of stayers who have stayed at a predetermined product department for a predetermined time or more among the shoppers, and shorter than the predetermined time at the product department among the shoppers. Receive information about the number of immediate purchasers who have spent time and purchased products,
The sum of the number of stayers and the number of immediate purchasers is calculated as the number of product interest holders who are considered interested in the product among the store visitors, Calculating a percentage of the number of product interest holders,
A calculation method characterized by the above. In a calculation method for calculating an index for evaluating a product,
Computer
And a number of commodity buyers who purchased a product of Jo Tokoro of goods department, the number of residence who have residence equal to or greater than a predetermined hours before Symbol goods department, said before Symbol and short residence time than the predetermined time in the commodity sales floor merchandise Receive information about the number and immediate purchasers who purchased
To calculate the sum of the number of the number and the commodity immediately purchaser of the residence who, as a pre-Symbol number of products interest holder who seems to be interested in the product, the product purchaser with respect to the number of the commodity interest holder Calculate the percentage of the number of
A calculation method characterized by the above. In a calculation device that calculates an index for evaluating a product advertisement,
The number of shoppers who have entered the store, the number of stayers who have stayed at a predetermined product department for a predetermined time or more among the shoppers, and shorter than the predetermined time at the product department among the shoppers. Storage means for storing information relating to the number of immediate purchasers of the product who have stayed for a while and purchased the product;
The number of stayers and the number of immediate purchasers are acquired from the storage means, and the sum of the acquired number of stayers and the number of immediate purchasers of goods is calculated among the shoppers. A calculation means for calculating the number of product interest holders who are thought to be interested in the product, and calculating a ratio of the number of product interest holders to the number of shoppers;
A calculation device comprising:   A calculation program for causing a computer to execute a calculation method for calculating an index for evaluating a product advertisement,
  On the computer,
  The number of shoppers who have entered the store, the number of stayers who have stayed at a predetermined product department for a predetermined time or more among the shoppers, and shorter than the predetermined time at the product department among the shoppers. Receive information about the number of immediate purchasers who have stayed for hours and purchased the product,
  The sum of the number of stayers and the number of immediate purchasers is calculated as the number of product interest holders who are considered interested in the product among the store visitors, Calculating a percentage of the number of product interest holders,
  A calculation program characterized by causing processing to be performed.   In a calculation program that calculates metrics for product evaluation,
  On the computer,
  The number of merchandise purchasers who have purchased merchandise at a predetermined merchandise store, the number of stayers who have stayed at the merchandise store for a predetermined time or more, and the merchandise store that has stayed for a time shorter than the predetermined time to purchase the merchandise. Receive information about the number of immediate purchasers,
  The sum of the number of stayers and the number of immediate purchasers is calculated as the number of product interest holders who are considered interested in the product. Calculate the percentage of numbers,
  A calculation program characterized by causing processing to be performed.

Images