JP2009532752A - Shopping method and system - Google Patents

Abstract

  A shopping method and system for providing incentives to a shopper for the purpose of increasing the value of the shopping basket to the shopper and the size of the shopping basket containing the merchant's product is disclosed. Data about purchases made by individual shoppers is collected and analyzed to determine the core product and related products that have some correlation with the purchase of the core product. A promotion list is created based on promotions required by the seller to purchase products related to a particular core product. The purchase cycle for a particular product is determined so that the promotion cycle length for a particular product can be determined, and the size of the group of people likely to fall within that promotion cycle is also worth the promotion Whether it is considered to determine the nature of the promotion.

Description

  The present invention relates to a shopping method and system for providing shoppers with shopping incentives.

  It is common to see promotional offers offered to shoppers by merchants in bulk or targeted ways. Often, promotional offers are not accepted by shoppers. One critical issue is the timing of delivery. Even with targeted offerings (to the right buyers), it is difficult to get the timing of promotions right, such as the deliverables do not meet purchase needs. For example, if a consumer purchases a product last week and the product usage cycle is, for example, two months, the person is unlikely to accept promotional offers. Therefore, most promotional offerings are not optimal in promotional planning, product ordering and inventory management, resulting in inefficiencies. For a merchant, it will be an opportunity cost with respect to related promotional costs such as advertising costs, material costs and promotional inventory costs. For retailers, more optimal promotions can lead to better sales revenue. For shoppers, they can't realize the benefits of sales promotions. In addition to the issue of promotional timing, shoppers buy merchandise in the basket, not just one product. Ideally, the basket should be the best value. Lack of understanding of the relationship of purchases in basket products results in shoppers who do not make the best use of promotional offers, resulting in sub-optimal value and dissatisfaction.

  Another result of the above is the way in which shoppers and retailers attack a shopper with a large array of promotional offers, which is very wasteful and leads to more inefficiencies. As a result, the shopper's basket is rarely a good purchase, is under-purchased and under-valued, and the shopper may purchase elsewhere, resulting in inefficiencies in the entire system.

  One known method is to use the past purchase history to target shoppers to minimize waste, i.e. to provide to previously purchased people. However, timing is still speculation. Similarly, it is not possible to obtain the optimal basket value. Therefore, shoppers have no motivation to purchase more.

  Another known method is to provide royalties points that can be converted into vouchers for purchase redemption. The idea is to give shoppers the freedom to reduce their purchase price by redeeming vouchers / points. But it does not work well for merchants who offer the best value because the purchase of the shopper may not meet the merchant's objectives. Since purchase patterns and habits are not considered in such general ways of providing value, the overall basket value may still be quite low.

  It is an object of the present invention to address the above problems and provide an incentive that is more likely to be received by the shopper, thereby increasing the value and / or scale of the shopping basket in a single purchase and Is to provide a system.

  The present invention collects data about products purchased by individual shoppers, determines core product categories from the collected data, and builds related product categories that are related to the core product categories Shopping to provide incentives to the shopper, including creating a list of promotional offers for the core product and related products, and providing incentives to the shopper who purchases the product from the list Provide a method.

  By determining the core product and then building the category of related products, the relevance of the item to the shopper's needs is better determined. Thus, provision can be made based on the expectation that a person will accept incentives to purchase many products from the core product category and related product categories. This in turn increases the value and / or scale of the shopper's shopping cart in a single purchase. From the shopper's point of view, this is beneficial because the shopper gains more value for the purchased product because of the incentive at the offering. And from the merchant's perspective, more products are sold, thereby increasing revenue to the merchant. This in turn improves the potential consumer satisfaction, and the merchant pays only for what the shopper receives, thus reducing the price of pre-purchasing inventory in a typical large-scale promotion. To reduce.

  Preferably, the method determines shopper purchase frequency in core related products and product categories, classifies those purchases into promotion cycle frequency and purchase recency grouping, and promotion cycle frequency and purchase. Further comprising creating a list of promotional offers and providing incentives based on the latest groupings.

  Preferably, the method further comprises determining the size, quantity and price of the product purchased for each core product category.

  Preferably, the method further comprises collecting data relating to shoppers including historical purchase data and consumer profile data and information including geo-demographic data, socio-economic data.

  Preferably, the data relating to the shopper is obtained at least in part by asking the consumer profile data and information from the shopper when the shopper joins the loyalty program.

  Preferably, the incentive includes one or more of vouchers, leaflets, coupons, promotional samples, points, lottery tickets and prizes.

  The present invention also analyzes data relating to products purchased by individual shoppers, determines core product categories from the data in the database, and determines related product categories associated with the core product categories; A shopper comprising a processor that creates a list of promotional offers for core products and related products for delivery to consumers, and an output device for providing incentives to shoppers who purchase the related products. Provide a shopping system to provide incentives.

  The output device can include a card reader and printer located at a location where the core product is sold so that it can be activated to incentivize the shopper to purchase the relevant product.

  In another embodiment, the output device may include only a printer.

  In a further embodiment, the output may be provided by a person handing a list to a shopper who purchases products from the core product category, thereby providing an incentive to purchase related products.

  Preferably, the processor collects data relating to shoppers including historical purchase data as well as consumer profile data and information including geo-demographic data, socio-economic data.

  Preferably, the data relating to the shopper is obtained at least in part by asking the consumer profile data and information from the shopper when the shopper joins the loyalty program.

  Preferably, the incentive includes one or more of vouchers, leaflets, coupons, promotional samples, points, lottery tickets and prizes.

  Preferably, the processor also determines the shopper's purchase frequency in the core related product and related product categories, classifies those purchases into promotion cycle frequency and purchase recency grouping, and the cycle frequency and purchase update. This is to create a list of promotional offers based on grouping and provide incentives.

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

  The present invention still further determines the core product and related products related to the core product by analyzing purchases made by individual shoppers, and the core product based on the frequency of purchase of the core product by the shopper. Create a list of promotional offers related to the product and its related products, output the list to the shopper, and if the shopper who purchased the core product also purchased the related product of the core product, Providing a shopping method for providing an incentive to a shopper, including providing an incentive.

  Preferably, the method analyzes data relating to products purchased by individual shoppers to determine correlations and removes categories of related products that do not meet a predetermined correlation point from the predetermined core products and related products. Further comprising.

  Preferably, the method further includes determining a cycle length for promotion based on a purchase cycle of the core product by the shopper.

  Preferably, the method determines a purchase recurrence according to a reference cycle, determines a potential size or grouping of shoppers likely to purchase the core product within a predetermined time period, and expects to purchase the core product. Further comprising creating a list of promotional offers based on the potential size or group of shoppers to be promoted.

  Preferably, the method further comprises collecting data relating to shoppers including historical purchase data and consumer profile data and information including geo-demographic data, socio-economic data.

  Preferably, the data relating to the shopper is obtained at least in part by asking the consumer profile data and information from the shopper when the shopper joins the loyalty program.

  Preferably, the incentive includes one or more of vouchers, leaflets, coupons, promotional samples, points, lottery tickets and prizes.

  The present invention further determines the core product and related products associated with the core product by analyzing purchases made by individual shoppers, and also determines the core product and its product based on the frequency of purchase of the core product by the shopper. A processor that creates a list of promotional offerings for related products and provides incentives to shoppers who supply the list to the shopper and purchase the core product if the shopper also purchases a related product for the core product A shopping system for providing an incentive to a shopper, comprising an output for providing.

  Preferably, the processor analyzes data relating to products purchased by the individual shopper to determine a correlation and removes categories of related products that do not meet a predetermined correlation point from the predefined core products and related products.

  Preferably, the processor determines a cycle length for promotion based on a purchase cycle of the core product by the shopper.

  Preferably, the processor determines the recency of purchases according to a baseline cycle, determines the potential size or grouping of shoppers likely to purchase the core product within a predetermined time period, and is expected to purchase the core product Create a list of promotional offers based on the potential size or group of shoppers.

  Preferred embodiments of the present invention will now be described by way of example with reference to the accompanying drawings, in which:

  With reference to FIG. 1, the concept of a preferred embodiment of the present invention is schematically illustrated. The essence of the preferred embodiment of the present invention is to determine the category of the core product referred to as “hub category” and the category of related products referred to as “spoke categories” in the following description. .

  With reference to FIG. 1, data relating to products purchased by individual shoppers is collected and analyzed. Data can be collected by a checkout terminal that scans or otherwise collects data about products purchased by individual shoppers, and all products purchased by shoppers can be associated with individual shoppers.

  The shopper can register to participate in the incentive program and be given some way of identifying the shopper so that the shopper can be identified when the consumer goes shopping and pays for the item. This can be done with a card containing an identification code read by the checkout terminal or any other data related to the shopper. Other embodiments include consumer information such as shopper demographic data, shopping habits data, lifestyle data, and other shopper information that can be used as a basis for determining products that are likely to be of interest to the shopper. In order to provide this data, data relating to existing loyalty programs can also be used. Such a program is disclosed in our international patent application numbers PCT / SG2005 / 000185 and PCT / SG2005 / 000224. The contents of these two international applications are incorporated herein by this reference.

  Hub products and spoke products are determined based on what the shopper actually purchases. The shopping basket content is analyzed for the individual shopper and the total shopper basket is analyzed to determine the hub product and the products in the highly correlated category that will form the spoke category. The data is stored in the retailer's database by the retailer's electronic POS system 14 (FIG. 2), as described in more detail with respect to FIG. This is in turn transferred to the central location by electronic data transfer, where the data is analyzed in the processor 30 (FIG. 2), where hub and spoke categories, purchase frequency / purchase cycle, purchase freshness, price, quantity, per car Determine the number of items purchased and the respective product / category. Alternatively, a shopper's profile database 120 (FIG. 2) is established when a shopper applies for a loyalty / point card containing personal data about the shopper and other socio-economic information. Thus, the data contained in this personal database 120 includes shopper identifiers, geographic demographics, and other socio-economic data that can be merged with purchase data from an electronic POS system for the same shopper. Therefore, the data used to determine the hub and spoke categories is data about the actual purchase made by the shopper.

  For example, the hub category is a baby diaper. The product's hub category is associated with many spoke categories that are also purchased by people who purchase baby diapers. In the embodiment illustrated in FIG. 1, the spoke categories include infant milk, baby food, infant cleaning, cereal, coffee, confectionery and chilled meat. In another example not shown, the hub category is a herbal product such as herbal tea, and many spoke categories such as facial cleansers, sugar, cereals and natural products are associated with the hub category. Spoke products can still be included even if they do not have a strong correlation with the hub product in the actual shopping basket. For example, a new product, such as a new baby towel that is put on the market, can form a spoke product even if people have not previously purchased the product because it is a new product. However, the majority of spoke products have a strong correlation with hub products.

  FIG. 2 is a schematic block diagram of a system for performing the method of the preferred embodiment.

  With reference to FIG. 2, a block diagram of a system embodying the present invention is illustrated. An output printer and card reader 10 is shown in the vicinity of a shelf 12 containing a hub product such as a diaper. The checkout terminal 14 is provided at a place where the shopper pays for the product. Generally, when a shopper purchases a product, the shopper is at the checkout terminal 14 and the product is scanned to identify the purchased product. A particular shopper can also be identified by an input code provided by a card read by the card reader 15 of the checkout terminal 14, a credit card at the retail store 70, or the like. However, the specific identification of the shopper is not essential for embodiments of the present invention, and the embodiment can be implemented without a specific identification of the shopper. What is needed is that the types of products purchased by individual shoppers are collected by the terminal 14 of the retail store 70 and fed to the retailer data warehouse processor system 60 at the remote retailer central location or back office 80. It is to be done. A single back office 80 may be associated with many different stores, etc. in a department store chain.

  Data relating to purchases made by the shopper is collected at the terminal 14 and supplied to the store processor 51 and the retail store server 50 held in the retail store 70 via a communication link 28 such as a LAN. The data is then provided from the server 50 to a retailer central location database and processor system 60 that includes a database 62 and a processor 64. The retailer central office 80 also includes a retail server and database system 90 that includes a database 120 and a server 140. The system 90 stores data relating to the shopper to operate a general loyalty point system and promotions, and that data can be merged with the shopping purchase data collected by the system 60, again. It can be provided to the remote supplier center 100 via a communication link 85, which is a wide area network, an internet communication link, or any other suitable link.

  In this manner, purchase data and other data relating to shoppers stored in the system 60 is supplied to the database 32 of the central location 100 operated by the program supplier.

  The central base processor 30 analyzes data in the database 32. Thus, database 32 is a work database used by processor 30 during analysis of purchase data. Once the data is received by the database 32, the data is analyzed by the processor so that all products purchased by the shopper in a single basket transaction are subjected to correlation analysis. Products are ranked in order of purchase frequency, so the hub category is determined from this data. Each hub category is typically the most frequently purchased product or has a high consumer penetration depending on a given marketing intent. Each hub product is then correlated with other categories. The initial result is a list of correlation scores from strongest to weakest. The weakest correlation is truncated and can be ignored. A weak correlation is determined with respect to a given correlation point or value so that any correlation below that correlation point or value is considered a weak correlation. In this way, all purchases made by the shopper can be queried by the processor 30, thereby creating a correlation between the products purchased by the shopper to determine hub products and their associated spoke products. This allows a hub product that constantly shows a strong correlation with the spoke product to be maintained and a weak correlation to be removed.

  The processor 30 can then create a favorites list for the hub product and related products and can determine a grouping of shoppers within the cycle based on purchases made by individual shoppers. Thereafter, purchase cycle decisions can be made for individual hub products, from which individual promotional length determinations can be made.

  The processor 30 also determines the freshness of the purchase made and compares it to the reference cycle. For example, if the diaper purchase cycle is typically about two weeks for an individual shopper, the timing of the promotion can be equal to the purchase cycle and the length of the promotion can also be determined. For example, in the case of a product purchased every two weeks, sales promotion can be performed for two weeks.

  For each product hub category, a determination is made regarding the potential size of the group of buyers likely to purchase the hub product within the next predetermined time period, such as two weeks. If the potential size of the group of shoppers is large enough, promotions can be developed for people who purchase hub products and receive some incentive to purchase related spoke products. Thus, the processor 30 can generate promotional offers for hub and spoke products, and promotes favorites lists for each hub and spoke category based on the vendor's ready offering. Offerings can be generated. As mentioned above, these incentive offerings may be other incentives such as price discounts, provision of additional products at no additional charge, or prizes, free samples, lottery tickets, bonus points for subsequent shopping, etc. unknown. The favorites list is transferred to the retailer server 50 by the processor 30 through the communication link 36.

  Alternatively, the favorites list can be sent back to the retailer central location 80 by the processor 30 via the communication link 85 so that the EPOS data processor and database system 60 forwards the favorites list to the retail store server 50 via the communication link 35. can do.

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

  The favorites list can then be loaded into the printer 10 from the processor 51 by way of the communication link 38, or manually by the flash card storage device, to the printer 10.

  Thus, when the purchaser is on the shelf 12 to purchase a diaper, the purchaser has the option of operating the printer 10 to receive a favorites list associated with that hub category of product. The favorites list may indicate that certain incentives are provided if the purchaser purchases all of the additional products shown in FIG. Different incentives can be provided if only part of the spoke product is purchased. In another embodiment, rather than providing a printer 10 to generate a favorites list, the favorites list can simply be handed over to anyone who purchases diapers by a person located on the shelf 12.

  In this way, the product purchased by the shopper when the shopper is at the checkout terminal 14 is determined and compared to the incentive presented by the output device 10 so that the shopper actually purchased the shopper. Receive the incentive based on.

  The shopper database 120 and server 140 are also provided for the input of data relating to individual shoppers such as geo-demographic data, socio-economic data, shopper profile information, past purchase history data, and the like. The data is based on their likes and dislikes, demographic data, etc., along with what hub products they actually purchase to better promote to different levels of shoppers. Can be provided to the processor 30 for use in a favorites list and a list of promotional offers. The data may be collected by questionnaires to people who have applied to participate in a royalty program or other type of royalty program provided as part of a shopping system.

  The configuration illustrated in FIG. 2 is merely exemplary. Of course, if the system is provided through many different retail outlets, a single central processor 30 and database 32 may be provided that communicate with the printer or output device 10 at each store location. In addition, many such printers 10 can be provided at each store location. Still further, the processor 30 may be formed by a central processor in communication with the store processor.

  Although the embodiment of FIG. 2 relates to an actual store, the store may be a virtual store, a mall, a food store, etc., such as a store accessed via the Internet or other remote access device. . Still further, the nature of the store may provide services related to daily life, such as sports gyms, amusement parks, etc., rather than where specific products are purchased.

  The method of the preferred embodiment of the present invention will be described in more detail with reference to the flowchart of FIG.

  With reference to FIG. 3, at step 301, the shopper's basket components are determined by the processor 30 in the manner described above for identifying the product being purchased by the shopper. At step 301, processor 30 determines whether there is a strong correlation between the hub category and the spoke category. Using the example above, an analysis of a large number of different shopping baskets for shoppers shows that a certain number of people purchase baby diapers, and among those people, many other products are also purchased. Show. Thus, the hub product may be a baby diaper and the spoke category may also be a product purchased by many people who purchase baby diapers.

  The processor 30 performs a correlation analysis on the products purchased by the shopper in each single transaction. Other analytical tools may be used as needed. However, in the preferred embodiment, the products are ranked in order of purchase frequency and the category is determined. Each hub category is typically most frequently purchased or has a high consumer penetration, depending on a given marketing intent. Each hub is then correlated with other categories. The initial result is a list of correlation scores from strongest to weakest. A correlation point somewhere between the strongest and weakest is determined and used to determine the separation of strong correlations from weak correlations.

Several methods can be used to determine hub and spoke categories, including:
(A) Simple correlation with highest penetration or frequent purchase category. This allows shopping baskets that show significant correlations between purchases of various products to be included, and those with weak correlations can be excluded according to step 304.
(B) Other statistical and analytical tools can be used with the correlation analysis.

  The method of determining the hub and spoke category depends on the end result required by the merchant. For example, it may only be necessary to provide a simple understanding of hub and spoke categories, or in addition, how many optimal hub categories to operate the method and system of the preferred embodiment most efficiently. It may be required to know what must exist.

For example, the hub category can be as follows.
(A) Frequently purchased items (b) Major or basic items (c) High shopper penetration (d) Thematic (impulsive or special interests such as babies) and therefore as a hub Baby diapers, health foods, etc. (e) Purpose categories

All other categories are ranked in order based on the strength of the correlation. For example, if the hub category is a baby diaper, the marketing intent is to increase the size of the shopper's (mother) basket that purchases the diaper, as it can be an unprofitable shopper. The correlation point or value indicates a strong relationship when the spoke product is purchased with the hub product. Thus, the spoke category can be a spoke category that exceeds a predetermined percentage correlation with the purchase of baby diapers in the hub category, for example:
(A) Milk for infants (b) Baby food (c) Cereals (d) Coffee (e) Refrigerated meat / Breakfast ham (f) Confectionery (eg biscuits)
(G) Baby powder (h) Salt

  The result of the analysis in step 301 is examined in step 302. In the case of strong correlation, the process can continue to step 303. If the correlation is weak, the process moves to step 304, and cases with relatively weak correlation or no relationship are ignored and effectively removed from the system.

  At step 303, decisions regarding hub and spoke categories for promotional offerings are considered. At this time, recent promotions are considered, so if baby powder is a recent promotion subject, this product is excluded from the promotions that were proposed during the analysis of hub and spoke categories at step 303. Can be done.

  In step 303, the analysis may determine the hub category as a frequently purchased product category or a product with high consumer penetration. For example, a product category that many shoppers have tried or purchased. In general, a hub product is the primary item in each shopper's basket and represents the top item purchased by all shoppers over a period of time, such as a year. However, certain variations may also exist, such as further segmentation into lifestyle baskets related to lifestyle products such as dishes or meals that can be a hub for women's baskets, particularly those relating to women's needs. It can also be determined.

  In step 305, the initial favorite list is edited based on the analysis in step 303. A potential shopper potential size is determined. For example, a list where potential sellers can be recruited to participate in an individual promotion, or that a retailer agrees with a listed seller to participate in a promotion, what sales The question is whether you can use promotional tactics.

  Simultaneously with steps 307-309, a determination is made at step 306 regarding grouping of shoppers by cycle.

  From the hub and spoke category groups, the system now identifies the number of shoppers (and identifies them as needed if card readers are used to identify people on the shelf 12). . At step 307, an analysis of the shopper's purchase cycle is performed, so the system can determine the cycle length for the promotion according to step 308. If a hub category baby diaper is purchased by a shopper every two weeks and no shopper has purchased yesterday, the promotion cycle length must also be two weeks. Step 306 also determines whether all spoke categories fall into the two week cycle, so if the salt is purchased every 8 weeks, this spoke category will be removed.

  Thus, in step 305, the initial favorite list is edited based on the data collected in step 301. The initial favorites list is an initial view of the appropriate hub and spoke categories. The most important aspect of this step is to determine eligible shoppers for each category and to count them to assess the size of individual groups.

  At step 306, the group of shoppers is reduced to those shoppers who make purchases in an average purchase cycle, and shoppers outside that cycle will see the individual promotion opportunities and the promising value providing those promotions. Excluded to decide.

  Concurrently with step 307, the purchase pattern for each category is analyzed to determine an average purchase cycle, typically expressed in weeks. Individual shoppers themselves do not need to be identified, but shoppers of a specified category are analyzed for their purchase cycle patterns.

  At step 308, a determination is made regarding the individual promotion cycle length. The cycle length may be the same as the product purchase cycle length. For example, if the promotion is for a baby diaper that is typically purchased in a two week cycle, the promotion cycle length may also be two weeks. The promotion cycle length at step 308 depends mainly on two factors: the shopper's purchase renewal of each category and the affordability of individual promotions. Ideally, if the affordability is not a constraint and the purchase cycle is 2 weeks, the cycle length is 2 weeks. This covers all shoppers who bought yesterday and will probably return to buy in the next two weeks. Thus, purchase freshness is necessary to determine separation points such that the promotional cycle covers a large number of shoppers.

  At step 309, a determination is made regarding the recency of the purchaser who purchases the individual hub product. Thus, from the collected data, there may be a decision that a shopper has purchased a hub product at most a few days ago, so that the shopper is willing to purchase all of the spoke category products. First unlikely. However, if the purchase is not as up-to-date as, for example, a week ago, the purchaser may want to purchase other products identified in FIG. However, the budget constraints of sellers are also taken into account. Shoppers who purchased one week ago are unlikely to purchase within a seven-day promotional program cycle if the seller wants to offer the program for only seven days due to budget constraints. Therefore, the potential size or group of shoppers targeted by the promotion is determined in order to estimate potential opportunities for the promotion.

  In the preferred embodiment of the present invention, it is not necessary to identify a particular shopper to determine the recency of a purchase. All shoppers in each category are considered, and the spread within the purchase cycle and the measurement of the number of recent purchases allow the promotion cycle to cover those shoppers recently purchased or to afford to miss them. Determined to determine if there is. Therefore, the initial group of shoppers at each hub and spoke shrinks when verified and sorted against the purchase cycle, purchase recency and promotion cycle.

  Thus, at step 310, a determination is made regarding the potential size or group of shoppers likely to be attracted by an individual promotion, thereby determining whether it is worth providing a promotion, or such a sale. Considerations can be made as to whether the group is so small that the promotional offering is unlikely to gain any benefit. If it is determined at step 310 that the potential shopper population likely to be attracted by a particular promotion is sufficient, a list of promotional offers for each hub product and spoke product is provided. Established at step 311. The list of promotional offers is a working list for merchants and retailers to determine the appropriate strategy for each hub or spoke category. This list is jointly agreed by the seller and the activity is approved by the retailer.

  At step 311, the list of promotional offers based on the hub category (baby diapers and spoke categories (a)-(f) above) is to increase the size of the shopping basket for this group of shoppers. It has a promotional strategy from retailers and is in the final form for approval by retailers. This is sent to the retailer to be included in the promotion list at EPOS terminal 14 so that when the shopper accepts any of the incentives, EPOS terminal 14 adapts the offer and redemption is authorized at terminal 14 Can be done.

  At step 312, a favorite list of offers for each hub and spoke category is generated to provide to the shopper when the hub product is purchased. The favorites list includes a list of offers, a set of vouchers or coupons, or a flyer that informs shoppers of spoke offers that are available when they are purchased at the same time as the hub category product.

  As shown in step 313, the list can be provided by printing or handing over the list. The printer is placed where the hub category product is available for sale, so that the shopper who purchases the hub category product inserts a card etc. that identifies the shopper and is provided for the purchase of the spoke category product You can get an incentive print. For example, the incentive may be that if a person purchases each of the spoke category products, that person will receive a certain percentage discount on the price of the product. Alternatively, the incentive may be that a person is given an additional product. Other incentives may be a lottery ticket, bonus points for other purchases, giveaways or other service items, thereby giving shoppers an incentive to purchase such products that shoppers may also want. give.

  Therefore, the result at step 314 is that the shopper category that the shopper is associated with is due to the provision of incentives and the fact that the shopper will definitely need those products anyway. It is thought that it will purchase the product from. Thus, the scale or total amount of baskets that are increased for shopping by the shopper on that particular day is likely to increase. This is obviously a benefit to the merchant selling the spoke category product, and a benefit to the shopper because the shopper receives an incentive to purchase any additional product that he would need anyway. In turn, this results in shoppers receiving the best value from the promotional offers they receive, thereby increasing consumer satisfaction. In this way, the adequacy of the timely and relevant offerings provided to the shopper will allow the shopper to purchase more products and get the best value for the purchase because of the incentive provided. Let's go. Step 314 also analyzes the products purchased with the data collected at the terminal 14 to measure the amount of hub and spoke products that are actually purchased by the shopper during the promotion process, Allows the degree of promotion success to be determined.

  Thus, reference to a product in this specification and claims should be understood to encompass purchases of services such as sports gym applications, movies, sports events and other entertainment.

  It should be understood that the invention is not limited to the specific embodiments described above by way of example, as modifications within the spirit and scope of the invention can be readily made by those skilled in the art.

  In the claims and the foregoing description of the invention, the term "comprise" or variations such as "comprises" or "comprising" are included unless the context requires otherwise for explicit language or the required meaning. Is used in the sense of, i.e. used to specify the presence of a defined feature, and does not exclude the presence or addition of additional features in various embodiments of the invention.

It is the schematic which illustrates the concept of this invention. 1 is a block diagram of a system embodying the present invention. 6 is a flowchart illustrating the method of the preferred embodiment of the present invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Output printer and card reader 12 Shelf 14 EPOS settlement terminal 15 Card reader 28 Communication link 30 Supplier center base processor 32 Supplier center base database 35 Communication link 36 Communication link 38 Communication link 50 Retail store server 51 Store processor 60 Retailer Central location database and processor system 62 Retailer central location database 64 Retailer central location processor 70 Retail outlet 80 Retailer central location 90 Retail server and database system 85 Communication link 100 Supplier central location 120 Shopper profile database 140 Server

Claims (24)

A shopping method for providing incentives to shoppers,
Collecting data about products purchased by individual shoppers;
Determining a category of core products from the collected data and building a category of related products associated with the category of core products;
Creating a list of promotional offers for the core product and related products;
Providing an incentive to a shopper who purchases the product based on the list. Determining the shopper's purchase frequency in core related products and product categories and classifying those purchases into promotion cycle frequency and purchase recency groupings;
The shopping method of claim 1, further comprising: creating a list of offers for promotion and providing incentives based on the promotion cycle frequency and the latest grouping of purchases.   The shopping method of claim 1, further comprising determining a purchased product size, quantity and price for each of the core product categories.   The shopping method of claim 1, further comprising collecting data relating to a shopper including past purchase data and consumer profile data and information including geo-demographic data, socio-economic data.   5. The shopping method of claim 4, wherein the data relating to the shopper is obtained at least in part by asking the consumer profile data and information from the shopper when the shopper subscribes to a royalty program.   The shopping method of claim 1, wherein the incentive includes one or more of a voucher, a leaflet, a coupon, a promotional sample, a point, a lottery ticket, and a prize. A shopping system for providing incentives for shoppers,
Analyzing data on products purchased by individual shoppers, determining a category of core products from the data in the database, determining a category of related products related to the category of core products, and A processor for creating a list of promotional offers for the core product and related products for delivery;
An output device for providing an incentive to a shopper who purchases the related product.   8. The output device of claim 7, wherein the output device includes a card reader and printer located at a location where the core product is sold so as to be operable to cause a shopper to purchase the related product. Shopping system.   The shopping system of claim 7, wherein the output device comprises a printer.   The processor also determines purchase frequency of shoppers in the core related product and category of the related product, classifies the purchases into promotion cycle frequency and purchase freshness grouping, the promotion cycle frequency and the 8. The shopping system of claim 7, wherein the incentive is provided by creating a list of promotional offers based on the latest grouping of purchases.   9. The shopping system of claim 8, wherein the processor also determines the product size, quantity and price purchased for each of the core product categories.   The processor is located at a supplier-centric base and is connected to a retail outlet server of a retail outlet by a communication link; the processor is also connected to a retailer-centric base by a communication link; The base has a database and a processor system connected to the retail store server by a communication link, and the database and the processor system receive purchase data via the EPOS checkout terminal and the store server, and the purchase data is sent to the store. The shopping system of claim 1, wherein the shopping system is provided to the processor at a supplier-centric location, the processor creating the list for supply to the retail store server and loading at the EPOS checkout terminal. A shopping method for providing incentives to shoppers,
Determining a core product and related products related to the core product by analyzing purchases made by individual shoppers;
Creating a list of promotional offers for the core product and related products based on the frequency of purchases of the core product by shoppers;
Outputting the list to a shopper and providing an incentive to the shopper when the shopper who purchased the core product also purchased the related product of the core product.   Analyzing data relating to products purchased by individual shoppers to determine a correlation and removing categories of the related products that do not meet a predetermined correlation point from the predetermined core product and the related products. The shopping method according to claim 13.   The shopping method of claim 13, further comprising determining a cycle length for sales promotion based on a purchase cycle of the core product by a shopper.   A reference cycle is used to determine the latest purchases, determine the potential size or grouping of shoppers who are likely to purchase the core product within a given time period, and the potential of shoppers who are expected to purchase the core product. 14. The shopping method of claim 13, further comprising: creating a list of promotional offers based on size or group.   14. The shopping method of claim 13, further comprising collecting data relating to a shopper including past purchase data and consumer profile data and information including geo-demographic data, socio-economic data.   18. The shopping method of claim 17, wherein the data related to the shopper is obtained at least in part by asking the consumer profile data and information from the shopper when the shopper subscribes to a royalty program.   The shopping method of claim 13, wherein the incentive includes one or more of a voucher, a leaflet, a coupon, a promotional sample, points, a lottery ticket, and a prize. A shopping system for providing incentives for shoppers,
Analyzing purchases made by individual shoppers to determine the core product and related products related to the core product, and based on the frequency of purchase of the core product by the shopper, the core product and its related products A processor for creating a list of promotional offers for
A shopping system comprising: providing the list to a shopper and providing an incentive to a shopper who purchases the core product when the shopper also purchases a related product of the core product.   The processor also analyzes data relating to products purchased by individual shoppers to determine correlations and removes categories of the related products that do not meet a predetermined correlation point from the predetermined core product and the related products. The shopping system of claim 20.   The shopping system of claim 21, wherein the processor also determines a cycle length for promotion based on a purchase cycle of the core product by a shopper.   The processor is also expected to determine the renewal of purchases according to a baseline cycle to determine the potential size or grouping of shoppers likely to purchase the core product within a predetermined time period, and to purchase the core product. 22. The shopping system of claim 21, wherein the list of promotional offers is created based on a potential size or group of shoppers.   The processor is located at a supplier-centric base and is connected to a retail outlet server of a retail outlet by a communication link; the processor is also connected to a retailer-centric base by a communication link; The base has a database and a processor system connected to the retail store server by a communication link, and the database and the processor system receive purchase data via the EPOS checkout terminal and the store server, and receive the purchase data. 21. The shopping system of claim 20, wherein the shopping system is supplied to the processor at the supplier-centric location and the processor generates a list for supply to the retail store server and loading at the EPOS checkout terminal.

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