KR20090010042A - A shopping method and system - Google Patents

Abstract

A shopping method and system is disclosed which provides inducement to shoppers with a view to increasing the value of a shopping basket to a shopper and the size of a shopping basket containing marketer's products. Data relating to purchases made by individual shoppers is collected and is analysed to determine core products and related products which show some correlation with the purchase of the core products. Promotional lists are created based on promotions which are desired by marketers to induce people to purchase related products to a particular core product. The purchase cycle for particular products is determined so that the cycle length of a promotion for a particular product can be determined and also the size of the pool of people who are likely to fall within that promotion cycle is considered to determine whether a promotion is worthwhile and the nature of the promotion.

Description

Shopping method and system {A SHOPPING METHOD AND SYSTEM}

The present invention relates to a shopping method and system for inducing shopping to shoppers.

Promotional offers that marketers offer to shoppers on a large scale or in a way that targets specific shoppers are common. Usually, the promotional offer is not adopted by shoppers. One of the main problems is the timing of the offer. Even in targeted offers targeted to the right buyer, it is difficult to get the right promotion time, because the promotion offer does not match the purchase demand. For example, if a consumer purchased a product last week and the product's use cycle is two months, the consumer will not try to accept the promotional offer. Thus, most promotional offers are sub-optimal and cause inefficiencies in promotional planning, product ordering and inventory management. For marketers, this inefficiency will be opportunity costs in associated promotional costs such as advertising costs, material costs, and promotional invention costs. For retailers, more optimized promotions can give better sales returns. Even as a shopper, promotional profits cannot be realized. In addition to the timing of promotions, shoppers do not just buy a single product, but a basket of goods. Ideally, the basket should contain the best value. Lack of understanding of the purchasing relationship between the products in the product basket prevents shoppers from getting the best out of the promotional offer, choosing sub-optimal values, and causing dissatisfaction.

Another consequence of the above is that marketers and retailers infuse large amounts of promotional offers that generate further inefficiencies to shoppers, which is very costly. As a result, shoppers' baskets cannot contain good goods. That is, they are filled with cheap and worthless goods, and shoppers can buy them anywhere. As a result, the overall system becomes inefficient.

One known method is to target shoppers using past purchase history to minimize losses. That is, to provide shoppers with things that have been made by them before. However, the timing problem is still in the most conjectured area. Likewise, it is impossible to obtain optimal value from the products in the basket. Thus, shoppers have no incentive to buy more.

Another known method is to provide loyalty points that can be converted into vouchers for redemption of purchases. The idea is to give shoppers the freedom to lower the value of their purchases from redemption of vouchers / pointers. However, this is not done with marketers providing the best product, as shoppers 'purchases may not match the marketers' goals. Since purchase patterns and habits may not be considered in such a generic method of providing value, the total value of the items in the basket will still be very low.

SUMMARY OF THE INVENTION An object of the present invention is to provide a method and system for dealing with the above problems and to provide handouts for shoppers to better choose in order to increase the value and / or scale of a shopping basket in a single shopping trip. will be.

The present invention provides a shopping method for providing handouts to shoppers, the shopping method,

Collecting data about products purchased by individual shoppers;

Determining core product categories from the collected data and establishing relevant product categories associated with the core product categories;

Generating a promotional offer list associated with the core products and related products; And there may be a step of providing handouts to shoppers to purchase products from the list.

By determining the core products and then establishing relevant product categories, the relevance of the items to shoppers' demands is more appropriately determined, thus allowing an individual to purchase many products from the core product categories and related product categories. Promotional offers can be made based on the likelihood of accepting handouts. This in turn increases the value and / or scale of the items contained in the shopper's shopping basket in a single shopping trip. On the shopper's side, this is a benefit, since the shopper gets more value than the product purchased due to the handouts provided. And for the marketer, as more products are sold, the return to the marketer is increased. This in turn promotes possible customer satisfaction, and marketers pay only for what the shoppers adopt, thus reducing the discounts that are due to general inventory promotions.

Advantageously, the method includes determining a shopper's purchase frequency in the core related products and product categories, classifying their purchases into a promotion cycle frequency and a group of recent purchases, and the cycle frequency and recent purchase. There may be further steps to generate promotional offer lists and promotional handouts based on the group.

Advantageously, the method may further comprise determining the size, quantity, and value of the product purchased for each core product category.

Advantageously, the method may further comprise collecting data relating to shoppers, wherein said data comprises historical purchase data, and geo-demographic data and socio-economic data (socio). consumer profile data, including economic data and information.

Advantageously, said shopper data is obtained at least in part by requesting said data and information from shoppers when shoppers participate in a loyalty program.

Preferably, the handouts may be one or more vouchers, leaflets, coupons, promotional samples, points, sweepstake tickets and gifts.

The present invention also provides a shopping system for providing handouts to shoppers, which shopping system,

A processor for analyzing data about products purchased by individual shoppers, determining key product categories from the data in the database, and determining related product categories associated with the key product categories;

The processor is also for generating a promotional offer list for the core products and the related products for providing to the consumers; And an output device for providing shoppers with handouts for purchasing the related products.

The output device may be a card reader and a printer located at a location where key products are offered for sale and the device may thus be operated to provide a handout that allows a shopper to purchase the related products.

In an alternative embodiment the output device may consist only of a printer.

In another embodiment, the output may be provided by a person distributing a list to shoppers who purchase products from the core product category, thereby providing a handout to purchase the related products.

Preferably, the processor collects consumer related data, which may be historical purchase data and consumer profile data including geological-demographic data and socio-economic data and information.

Advantageously, said shopper data is obtained at least in part by requesting said data and information from shoppers when shoppers participate in a loyalty program.

Preferably. The handouts may be one or more vouchers, leaflets, coupons, promotional samples, points, race tickets and gifts.

Advantageously, the processor also determines the purchase frequency of shoppers in the core relevant products and categories of related products, classifies these purchases into promotion cycle frequency and recent purchase group, and the cycle frequency and recent purchase group. To generate promotional offer lists and handouts provided.

Preferably, the processor also determines the size, quantity and value of the product purchased for each core product category.

The present invention still further provides a shopping method for providing handouts to shoppers, wherein the shopping method includes:

Analyzing the purchases made by individual shoppers to determine core products and related products related to the core products;

Generating promotion offer lists relating to the core product and its related products based on the frequency of purchase of the core products by the shoppers; And

If a shopper purchasing a core product also purchases related products in that core product, there may be a step of outputting a list providing handouts to the core product purchase shopper.

Advantageously, the method comprises analyzing data relating to products purchased by individual shoppers to determine correlations, wherein the categories of related products that are below a predetermined correlation point are defined by the core products defined above. And further removing from related products.

Advantageously, the method may further comprise determining a cycle period for promotion based on a purchase cycle of key products by shoppers.

Preferably, the method uses a cycle basis to determine a recent purchase date, to determine a potential size or group of shoppers who are likely to purchase a core product within a given timeframe, and to select a shopper who is expected to purchase a hub product. There may still be further steps in developing promotional offer lists based on potential size or group.

Advantageously, the method may further comprise collecting historical purchase data and data relating to shoppers, including geological-demographic data and socio-economic data and information.

Preferably, the shopper data is obtained at least in part by requesting the shopper the data and information when the shopper participates in a loyalty program.

Preferably, the handouts may be one or more vouchers, leaflets, coupons, promotional samples, points, race tickets and gifts.

The present invention still further provides a shopping system for providing handouts to shoppers, wherein the shopping system,

A processor for analyzing the purchases made by individual shoppers to determine the core products and related products related to the core products, wherein the processor is also based on the frequency of purchase of the core product by the shoppers; To generate promotional offer lists for its related products; And

If a shopper who purchases a core product also purchases related products to that core product, the output may be provided to provide the shopper with a list of handouts to the key product shopper.

Advantageously, the processor analyzes data relating to products purchased by individual shoppers to determine correlations, and categories of related products that are below a predetermined correlation point from the core products and related products defined above. Remove

Advantageously, the processor determines a cycle duration for promotion based on a purchase cycle of hub products by shoppers.

 Advantageously, the processor uses the cycle criteria to determine a recent purchase date and to determine a potential size or group of shoppers who are likely to purchase a core product within a given time, and a potential size or group of shoppers expected to purchase a hub product. Develop a promotional offer list based on

Preferred embodiments of the present invention will be described by way of example with reference to the accompanying drawings.

1 is a schematic diagram depicting the concept of the present invention.

2 is a block diagram of a system embodying the present invention.

3 is a flow chart illustrating a method of a preferred embodiment of the present invention.

1, a preferred embodiment of the present invention is schematically illustrated. The essence of this preferred embodiment of the present invention lies in determining the core product categories, for the purpose of the following description, the core product categories will be referred to as the hub category and the related product categories as the spoke category. .

In connection with FIG. 1, data related to products purchased by individual shoppers is collected and analyzed. The data will be collected by a checkout terminal that scans or otherwise collects data related to products purchased by individual shoppers. And all of the products purchased by the shopper can be associated with the particular shopper above at this checkout terminal.

Shoppers may register to participate in the handout program and some method of identifying the shopper may be provided such that the shopper may be identified when the consumer goes shopping and pays for the product. This can be done via a card containing an identification code read by the checkout terminal or any other data associated with the shopper. In alternative embodiments, existing loyalty programs may also be associated with shoppers that may be used as a basis for determining shopper demographic data, shopping habit data, lifestyle data, and products of interest to shoppers. It can be used to provide consumer information such as data. Such programs are disclosed in International Patent Application Nos. PCT / SG2005 / 000185 / and PCT / SG2005 / 000224. The contents of these two international patent publications are incorporated herein by reference.

Herbal products and spoke products are determined based on the actual purchase of shoppers. In order to determine the high correlation categories products that will make the hub products and the spoke categories, the shopping basket contents of individual shoppers will be analyzed and the entirety of the basket contents of all shoppers will be analyzed. As will be described in more detail with respect to FIG. 2, the data is captured in a retailer's database by a retailer's electronic point-of-sales system (EPOS) 14 (FIG. 2). This time, to determine hub categories and spoke categories, frequency of purchase / cycle, date of last purchase, value, volumes, number of items purchased per basket, and each product / category, It is transmitted via electronic data transmission to a central authority, which is the place to be analyzed in the processor 30 (FIG. 2). Independently, the shopper's profile database 120 (FIG. 3) is established when shoppers sign a loyalty / reward card that includes personal data and other socio-economic information related to the shopper. Therefore, the data contained in this personal database 120 includes shopper identifiers and will include geological-demographic data and other socio-economic data that may be combined with purchase data from an EPOS relating to the same shopper.

Thus, the data used to determine hub categories and spoke categories is data relating to the actual purchase made by the shopper.

For example, the herb category may be a baby diaper. The hub category of the product will be associated with a number of spoke categories purchased by those who also buy baby diapers. In the embodiment shown in FIG. 1, the spoke categories consist of infant milk, baby food, baby bath products, cereals, coffee, sweets, and chilled meat. In another example not shown, the herbal category may be a herbal product, such as herbal tea, and many spoke categories, such as face wash, sugar, cereal, natural products, will be associated with the herb category. Although spoke products may not have a strong correlation with herbal products in the actual shopping basket, spoke products will also be included. For example, a new product, such as a new baby handkerchief to be introduced to the market, can produce spokes, even if people have never purchased it since it is a new product.

2 is a schematic block diagram of a system for implementing the method of the above preferred embodiment.

2, a block diagram of a system embodying the present invention is shown. The output printer and card reader 10 are visible near the shelf 12 containing hub products such as diapers. The checkout terminal 14 is provided where the shopper pays for the product. Typically, when a shopper buys a product, the shopper will be located at the checkout terminal 14 and the shopper's product will be scanned so that the purchased product can be identified. A particular shopper may also be supplied by way of a card read by the card reader 15 at the terminal 14 or by a credit card or the like at the retail outlet 70. Can be identified by an input code. However, the specific identification of the shopper is not the essence of the embodiment of the present invention and the embodiment may be practiced without the specific identification of the shopper. What is required is that the nature of the products purchased by a particular shopper is collected by the terminal 14 at a retail outlet 70 and is located at a remote retailer central location or back end. supplied to a retailer data warehouse processor system 60 at office 80. One backend office 80 may be associated with many different stores, or the like, in a chain of department stores.

The data associated with the purchase made by the shopper is collected at the terminal 14 and maintained at the retail outlet 70 by a communication link 28, which may be a LAN or the like. Processor 51 and Retail Store Server 50 are supplied. The data is now supplied from the server 50 to the retailer central database and processor system 60, which comprises a database 62 and a processor 64. The retailer central portion 80 also includes a retail server and database system 90 that includes a database 120 and a server 140. The system 90 stores data about shoppers in order to promote promotions with a general loyalty rewards system, which data can be combined with shopping purchase data collected by the system 60 and is a wide area network. May be supplied to the remote operator central location 100 via a communication link 85, which may be an internet communication link, or any other suitable link.

Thus, purchase data and other data about the shopper, stored in the system 60, is sent to the database 32 of the central portion 100 operated by a program provider.

The central processor 30 analyzes the data in the database 32. Therefore, the database 32 is a working database used by the processor 30 while analyzing the purchase data. When the data is received by the database 32, the data is analyzed by the processor such that all products purchased by shoppers in a single basket transaction undergo a correlation analysis. The products are ranked in order of purchase frequency and therefore the hub category is determined from this data. Each hub category is usually the most frequently purchased product and has high customer penetration in accordance with predetermined marketing intent. Each herbal product is now correlated with other categories, and the initial outcome is a list of correlation scores from the strongest to the weakest. The weakest correlation can be deleted and ignored. The weakest correlation is determined with reference to a given correlation point or value and thus all correlations below that point or value are considered to be weak correlations. Therefore, the processor 30 interrogates the entire purchase made by the shopper so that a correlation can be made between the shopper's purchases to determine hub products and spoke products associated with the hub product. ). This continually allows herb products that are strongly correlated with their spokes to be retained and herb products that are weakly correlated.

The processor 30 may then generate preference lists of hub products and related products, and determine groups of shoppers in a cycle based on purchases made by specific shoppers. . The decision can now be made in purchasing cycles related to specific herbal products, from which a period for a particular promotion can be determined.

The processor 30 also determines a recent purchase and compares it to a cycle basis. For example, when the purchase cycle of a diaper is usually about two weeks for an individual shopper, the timing of the promotion may be the same as the purchase cycle, and the period for promotion may also be determined. For example, for a product purchased on a two-week basis, the promotion will be provided for two weeks.

For each hub category of products, a determination is made regarding the potential size of a group of buyers who are likely to purchase the hub product within the next predetermined period (such as two weeks). If the potential size of the shopper group is large enough, promotions can be developed for those who will be provided with some handouts to buy herbal products and also to purchase related spoke products. The processor 30 may therefore generate promotion offers for the hub products and spoke products, and generate preference list promotion offers for each hub category and spoke category based on offers ready for marketers to make. do. As noted above, such handout offers may be price reductions, offering separate products at no extra cost, or giveaways, samples, horse racing tickets, bonus points for later shopping, or the like. . The preference lists are forwarded by the processor 30 to the retailer server 50 via the communication link 36.

Alternatively, the lists may be routed through the communication link 85 such that the EPOS data processor and database system 60 may forward the lists to the retail store server 50 via the communication link 35. It may be forwarded backwards to the retailer central portion 80 by the processor 30.

The store processor 51 then loads the list into the reader / printer 10 and the EPOS checkout terminal 14.

The preference lists are loaded from the processor 51 to the printer 10 by a communication link 38 or manually loaded into the printer 10 by a flashcard storage device.

Therefore, when a buyer is placed on the shelf 12 to purchase a diaper, the buyer has the option of activating the printer 10 to receive the preference list regarding that hub category of products. The preference list will indicate that if the buyer purchases all of the additional products shown in Figure 1, that particular handout will be provided. Other handouts may be provided if only some of the spoke products are purchased. In an alternative embodiment, instead of providing a printer 10 for generating the preference list, the permanent preference list may simply be passed to everyone who purchases a diaper by a person located on the shelf 12. will be.

Therefore, in order to enable the shopper to receive handouts based on what they actually purchased, the products purchased by the shopper when the shopper is located at the checkout terminal 14 are determined and provided by the output device 10. Will be compared to the handout.

The shopper database 120 and server 140 may also provide input data about individual shoppers such as geological-demographic data, socio-economic data, shopper profile information, past purchase history data, and similar data. . The data is based on their own preferences, demographic data, etc., along with what herbal products they actually bought, preference lists and promotion offer lists to better direct the promotion to different classes of shoppers. It may be supplied to the processor 30 for use in the. The data may be collected through questionnaires to those who apply to participate in a loyalty program offered as part of the shopping system or other type of loyalty program.

The structure shown in FIG. 2 is merely an example. If the system is provided through a number of different retail outlets, a single central processor 30 and database 32 will be provided that communicate with our output device printer 10 at each store location. It is obvious. Furthermore, a number of such printers 10 may be provided at each store location. Furthermore, the processor 30 may be generated by a central processor that in turn communicates with store base processors.

Although the embodiment of FIG. 2 relates to an actual store, the store may be a virtual store, such as a store connected via the Internet or other remote access device, mail, food outlets, and the like, and the store May be a lifestyle enterprise that provides, for example, a gym, entertainment or the like rather than a place where a particular item is purchased.

The method of this preferred embodiment of the present invention will be explained more fully with reference to the flowchart of FIG. 3.

With reference to FIG. 3, the basket 30 of the shopper is determined by the processor 30 in a manner referred to above to identify the products being purchased by the shopper at step 301. In step 301 the processor 30 determines whether there is a strong correlation between the hub category and the spoke categories. Using the example referenced above, analyzing multiple shopping baskets from different shoppers may show that a certain number of people buy baby diapers, and that many other products are also purchased from them. Thus, the herbal product may be a baby diaper, and the spoke categories may likewise be a product purchased by a number of people who purchase a baby diaper.

The processor 30 processes the products purchased by shoppers through a correlation analysis into each single transaction. Other analysis tools can be used if desired. However, in the preferred embodiment the products are ranked in order of purchase frequency and categories are determined. Each hub category is usually one that is most often purchased or has high consumer permeability depending on a predetermined marketing intent. Each hub is now associated with other categories. The initial outcome is a list of correlation scores from the strongest to the weakest. A correlation point is determined somewhere between the strongest and the weakest and is used to cut-off strong correlations from weak correlations.

 Several methods can be used to determine the hub categories and spoke categories, which include:

(a) simply correlating with the category with the highest permeability or frequently purchased category; The method here allows shopping baskets to show significant correlations between purchases of various products, and allows for the removal of weakly correlated shopping baskets as in step 304, and

(b) There may be ways in which other statistical and analytical tools can be used together in correlation analysis.

The manner in which the hub categories and spoke categories are determined depends on the final result required by the marketers. For example, it may only be necessary to simply provide an understanding of the hub category and spoke categories, or additionally need to know how many optimal hub categories there should be in order to operate the method and system of the preferred embodiment most effectively. There can be.

For example, the hub categories may be the following.

(a) frequency of purchase;

(b) the main item or base item;

(c) high shopper permeability;

(d) to be led by the subject or to a particular interest, such as a baby-thus, a baby diaper as a herb, health-food, etc .;

(e) Destination category.

All other categories will be ranked in order based on the strength of the correlation. For example, if the herb category is baby diapers, the marketing intent is to increase the basket size of shoppers (mothers) who buy diapers, which may be additionally needed by moms if the basket size is small. That's because they might be underperforming. The correlation point or value is strongly related when the spoke product is purchased with the hub product. Therefore, the spoke categories are related to the purchase of the hub category baby diaper, and those categories which are higher than a certain correlation percentage, for example,

(a) baby milk;

(b) baby food;

(c) cereal;

(d) coffee;

(e) frozen meat / breakfast ham;

(f) sweets-for example biscuits;

(g) baby powder;

(h) salt.

Can be.

The results of the analysis in step 301 are considered in step 302. In the case of strong correlation, the process may move to step 303. If the correlation is weak, the process moves to step 304 where relatively weak correlations or cases where there is no correlation at all are ignored and effectively removed from the system.

In step 303, decisions on hub and spoke categories are considered for the promotional offer. Recent promotions are now considered, and if baby powder was the subject of a recent promotion, the product can be removed from the proposed promotion while analyzing the hub categories and spoke categories in step 303.

In step 303, the analysis may determine the hub categories as frequently purchased product categories or as products with high consumer permeability. For example, many shoppers have tried or purchased these product categories. In general, the herbal products will be major items in each of the shoppers' baskets representing top items purchased by all shoppers for a period of time, for example, for one year. However, certain variations may also be determined, such as the women's baskets specifically related to the needs of women and lifestyle products such as dishes or meals where sauces, meat, or wine may be hubs. It can be something like dividing it further, such as the lifestyle basket associated with the field.

In step 305, the initial preference list is compiled based on the analysis of step 303. The potential size of qualifying shoppers is determined. For example, 'Is the list a list that recruits potential marketers to participate in that particular promotion?' 'Do you agree with the marketers that are short-listed to allow retailers to participate in the promotion?' Issues such as 'What promotion strategies can be used?'

Concurrent with the steps of 307 to 309, a determination is made regarding the group of shoppers with a cycle in step 306.

From the group of hub and spoke categories, the system now identifies the number of shoppers. (And if a card reader is used to identify people on shelf 12, it identifies shoppers, if necessary.) In step 307, an analysis of the shopper's buying cycle is performed, so that the system may perform step ( As in 308, the cycle duration for the promotion can be determined. If the hub category baby diapers were purchased every two weeks by shoppers and yesterday no shoppers bought them, the promotion cycle period would also have to be two weeks. In step 306, if salt is purchased every eight weeks, it is also determined whether all spoke categories fall within the two-week cycle so that this spoke category can be dropped.

Therefore, in step 305, the initial preference list is compiled based on the data collected in step 301. The initial preference list is an initial view of the appropriate hub categories and spoke categories. The most important aspect at this stage is to determine qualified shoppers for each of the categories and count them to assess the size of a particular group.

 In step 306, the group of shoppers will be reduced to those shoppers making purchases within the average purchase cycle and shoppers outside the cycle will have an opportunity for specific promotions and the likely value for providing such promotions. Will be removed to determine.

Simultaneously with step 307, purchase patterns for each of the categories will be analyzed to determine the average purchase cycle, usually expressed in weeks. Individual shoppers themselves do not need to be identified, but shoppers of that particular category can be analyzed for their purchase cycle patterns.

In step 308, a determination is made regarding the cycle period for the particular promotion. The cycle period will be the same as the purchase cycle period for the product. For example, if the promotion relates to a baby diaper that is usually purchased in a two week cycle, the cycle period of the promotion will be two weeks. The cycle duration of the promotion in step 308 depends mainly on two factors: the shopper's last purchase date for each category, and the affordibility to execute a particular promotion. Ideally, if the margin is not a constraint and the purchase cycle is two weeks, the cycle period is two weeks. This covers both shoppers who bought yesterday and shoppers who are likely to return in the next two weeks. Therefore, a recent purchase date is needed to determine the cut-off point for which the promotion cycle will cover the bulk of shoppers.

In step 309, a determination is made regarding the last purchase date of a purchaser who purchases a particular herbal product. Therefore, from the collected data, there may be a decision that the herbal product was purchased only a few days ago and therefore the shopper would not want to purchase all of the spoke category products. However, if the purchase was less recent, such as a week ago, the buyer would also want to purchase the other products shown in FIG. However, the budgetary constraints of marketers are also considered. Budgetary constraints will make marketers want to offer the program for only seven days, and shoppers who have purchased a week ago will not make a purchase within the seven-day promotional program cycle. All shoppers of the particular category are considered and the spread and how many purchases have been made within the purchase cycle in order to determine whether the promotion cycle is likely to cover or miss them. It was decided whether there was. Therefore, the initial shopper group for each hub category and spoke category will be reduced when checked and screened against the purchase cycle, recent purchase date, and promotion cycle.

Therefore, in step 310, a decision is made regarding the potential size or group of shoppers likely to be attracted by a particular promotion and accordingly it is worthwhile to provide the promotion or the size of the group is so small that such promotion offers Consideration may be given as to whether or not any benefit is likely to be provided. If it is determined at step 310 that the potential size of shoppers likely to be attracted by a particular promotion is sufficient, then a promotional offer list for each of the herbal and spoke products is established at step 311. The promotional offer list is a working list that works for marketers and retailers to determine the appropriate strategy for each hub category or spoke category. This list is agreed to all marketers and is approved by the retailer for activation.

In step 311 a promotional offer list based on the hub categories (baby diapers and spoke categories (a)-(f) mentioned above) along with the marketing tactics of marketers to increase the shopping basket size of shoppers in this group. Now in final form for approval by the retailers. This can be sent to the retailer and matched with the offer for inclusion in the retailer's promotional list of the EPOS terminal 14 and redemption at the terminal 14 when shoppers take any of the handouts. This can be confirmed.

In step 312 a provision list is created for each hub category and spoke categories to provide to shoppers when the hub product is purchased. The preference list includes a list of offers and a similar set of handouts that informs vouchers or coupons or spoke offers available to shoppers. They must be purchased at the same time as the hub category product.

As shown in step 313, providing a list can be accomplished by way of a printout or manual feed of the list. The printer may be located where the hub category product is offered for sale, so that a shopper who purchases the hub category may insert a card or similar to identify the shopper and may print out the handouts that are being offered when purchasing the spoke category product. You can get it. For example, the offer would be that if a person purchases each of the spoke category products, that person will be discounted a certain percentage of the price of that product. Alternatively, the handout may be that person receives additional products. Other handouts may be bonus points and free gifts or other giveaways for ticketing and other purchases to provide handouts to the shopper to purchase those products that the shopper also wants to buy.

Therefore, the result in step 314 is that shoppers are likely to buy products from the related spoke categories because of the handout being made and also because of the fact that shoppers are likely to need the products in any case. will be. Therefore, the total value of the shopping trip on an increased basket size or on a particular date by the shopper is likely to increase. This is clearly a benefit to the marketer selling the spoke category products and a benefit to the shopper. This is because the shopper is provided with a handout for purchasing the additional product that the shopper may need in any case. This may allow the shopper to receive the best value from the adopted promotional offer and thus increase customer satisfaction. Therefore, through offers associated with the shopper near the appropriate point in time, the handouts provided will allow the shopper to purchase more products and get the best value from the purchase. Step 314 also analyzes the products purchased with the data collected at the terminal 14 to determine the amount of hub products and spoke products actually purchased by the shoppers during the promotion process to determine the success of the promotion. Allows you to determine a measure.

Therefore, reference to these products should be understood to include the purchase of services such as joining a gym and entertainment such as movies, sporting events and the like.

Modifications can be readily made by those skilled in the art within the spirit and scope of the invention, and the invention is not limited to the specific embodiments described by way of example.

In the foregoing description of the invention and in the claims that follow, such term as "comprises / comprises" or "comprising", except where the context otherwise requires, due to language expression or necessary implications. Change has been used to mean everything inclusive. That is, to characterize the mentioned features and not to exclude other features of the various embodiments of the present invention.

Claims (24)

As a shopping method for providing handouts to shoppers, Collecting data related to the product purchased by the personal shopper; Determining core product categories from the collected data and establishing relevant product categories related to the core product categories; Generating promotional offer lists related to the core products and related products; And Providing a handout to shoppers to purchase a product from the list. The method of claim 1, The method includes determining a shopper's purchase frequency in the core related products and product categories, classifying the purchases into a promotional cycle frequency and a recent purchase group, and based on the cycle frequency and the recent purchase group. To generate promotional offer lists and handouts. The method of claim 1, The method further comprises determining, for each of the core product categories, the size, quantity and value of the purchased product. The method of claim 1, The method further comprises collecting data relating to the shopper consisting of past purchase data and consumer profile data, including socio-economic data and socio-economic data and information. The method of claim 4, wherein The shopper data is obtained at least in part by requesting the shopper the data and information when the shopper participates in a loyalty program. The method of claim 1, Wherein said handouts comprise one or more vouchers, leaflets, coupons, promotional samples, points, race tickets and gifts. As a shopping system for providing handouts to shoppers, A processor for analyzing data about products purchased by individual shoppers, determining key product categories from the data in the database, and determining relevant product categories related to the key product categories; Wherein the processor is also for generating a list of key products to provide to consumers and promotional offer lists for the related products, and  And an output device for providing shoppers with handouts for purchasing the related products. The method of claim 7, wherein The output device may comprise a card reader and a printer located at a location where the core products are offered for sale and the device may therefore be operated to provide a handout that allows a shopper to purchase the related products. system. The method of claim 7, wherein And the output device comprises a printer. The method of claim 7, wherein The processor also determines the purchase frequency of shoppers in the core related products and categories of related products, categorizes these purchases into promotion cycle frequency and recent purchase group, and promotes based on the cycle frequency and recent purchase group. Shopping system characterized by generating offer lists and handouts provided. The method of claim 8, The processor further determines product size, quantity, and value for each core product category. The method of claim 1, The processor is located at a supplier center and connected via a communication link to a retail store server of a retail store, the processor is also connected to a retail center via a communication link, and the central portion is connected to the retail store server via a communication link. Connect to receive purchase data via an EPOS checkout terminal and the storage server, provide the data to the processor in the provider central portion so that the processor generates the list for presentation to the retail store server, and And a database and a processor system for loading the EPOS checkout terminal. As a shopping method for providing handouts to shoppers, Analyzing the purchases made by individual shoppers to determine core products and related products related to the core products; Generating promotion offer lists relating to the core product and its related products based on the frequency of purchase of the core products by the shoppers; And And if the shopper purchasing the core product also purchases related products in the core product, outputting a list providing handouts to the core product purchase shopper. The method of claim 13, The method comprises the steps of analyzing data relating to products purchased by individual shoppers to determine correlations, and the categories of related products that are below a certain point of correlation to the core products and related products defined above. And removing from the field. The method of claim 13, The method further comprises determining a cycle period for promotion based on a purchase cycle of key products by shoppers. The method of claim 13, Cycle criteria are used to determine the latest purchase date, determine the potential size or group of shoppers who are likely to purchase a core product within a given timeframe, and generate a promotional offer list based on the potential size or group of shoppers expected to purchase a hub product. A shopping method, further comprising the step of developing. The method of claim 13, The method further comprises collecting data relating to the shopper including past purchase data, consumer profile data including geological-demographic data, socio-economic data and information. The method of claim 17, Advantageously, the shopper data comprises at least in part obtained by requesting the shopper the data and information when the shopper participates in a loyalty program. The method of claim 13, Wherein the handouts comprise one or more vouchers, leaflets, coupons, promotional samples, points, race tickets and gifts. As a shopping system for providing handouts to shoppers, A processor for determining the core products and related products related to the core products by analyzing purchases made by individual shoppers; Wherein the processor is also for generating promotional offer lists relating to the core product and its related products based on the frequency of purchase of the core product by shoppers; And And an output device for providing the shopper with a list providing handouts to the core product purchase shopper if the shopper purchasing the core product also purchases products related to the core product. The method of claim 20, The processor analyzes data relating to products purchased by individual shoppers to determine correlation and removes categories of related products that are below a predetermined correlation point from the core products and related products defined above. Shopping system. The method of claim 21, The processor is further to determine a cycle period for promotion based on a purchase cycle of hub products by shoppers. The method of claim 21, The processor is intended to determine a recent purchase date using a cycle basis and to determine a potential size or group of shoppers who are likely to purchase a core product within a given timeframe, and to a potential size or group of shoppers expected to purchase a hub product. A shopping system for developing a promotional offer list based on that. The method of claim 20, The processor is located at a supplier center and connected via a communication link to a retail store server of a retail store, the processor is also connected to a retail center via a communication link, and the central portion is connected to the retail store server via a communication link. Connect to receive purchase data via an EPOS checkout terminal and the storage server, provide the data to the processor in the provider central portion so that the processor generates the list for presentation to the retail store server, and And a database and a processor system for loading the EPOS checkout terminal.

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