WO2001015033A2 - Dynamic propagation of promotional information in a network of point-of-sale terminals - Google Patents

Dynamic propagation of promotional information in a network of point-of-sale terminals Download PDF

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Publication number
WO2001015033A2
WO2001015033A2 PCT/US2000/019426 US0019426W WO0115033A2 WO 2001015033 A2 WO2001015033 A2 WO 2001015033A2 US 0019426 W US0019426 W US 0019426W WO 0115033 A2 WO0115033 A2 WO 0115033A2
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WO
WIPO (PCT)
Prior art keywords
offer
pos terminal
pos
terminals
additional
Prior art date
Application number
PCT/US2000/019426
Other languages
French (fr)
Other versions
WO2001015033A3 (en
Inventor
Jay S. Walker
Raymond J. Mueller
Andrew S. Van Luchene
Daniel E. Tedesco
Keith Bemer
Stephen C. Tulley
Dean Alderucci
Jeffrey E. Heier
Anna Rath
Original Assignee
Walker Digital, Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Walker Digital, Llc filed Critical Walker Digital, Llc
Priority to EP00947442A priority Critical patent/EP1208506A2/en
Priority to AU61051/00A priority patent/AU6105100A/en
Priority to CA002381387A priority patent/CA2381387A1/en
Publication of WO2001015033A2 publication Critical patent/WO2001015033A2/en
Publication of WO2001015033A3 publication Critical patent/WO2001015033A3/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00Payment architectures, schemes or protocols
    • G06Q20/38Payment protocols; Details thereof
    • G06Q20/387Payment using discounts or coupons

Definitions

  • the present invention relates generally to point-of-sale terminals, and is more specifically concerned with dissemination of promotional information among networked point-of-sale terminals.
  • POS terminals such as cash registers
  • POS terminals are used in a wide variety of businesses for performing such processes as calculating a total price of a purchase of goods and/or services, and calculating an amount of change due to a customer.
  • POS terminals also are frequently interfaced to card authorization terminals, such as credit card validation devices, or themselves incorporate the functions of such devices.
  • POS terminals may also be used to perform other functions, such as inventory management performed by tracking purchases made and adjusting a database of store inventory accordingly.
  • Some POS terminals are arranged to exchange information with other POS terminals and/or central computer systems located at the same store as the terminals or at a remote location.
  • POS terminals It has also been proposed to use POS terminals to make sales offers or otherwise to aid in marketing promotions aimed at customers present at the POS terminal.
  • Modern large-scale retail organizations are exceedingly complex. Some organizations include hundreds or even thousands of stores, located throughout the United States, and in some cases in foreign countries as well. In some retail chains, all stores are owned by a single entity. In other chains, and particularly in the restaurant industry, most or all of the outlets may be owned by franchise owners.
  • the amount of data that may be collected and information that may be generated therefrom in a network of POS terminals in a large retail organization is immense and may encompass hundreds of thousands or millions of transactions per day.
  • the present invention introduces systems and methods for the propagation of information in a network of POS terminals.
  • performance data relating to a transaction at a first POS terminal is identified.
  • transaction information is transmitted to at least one additional POS terminal.
  • a method of communicating information in a network of POS terminals includes the following: a) receiving, generating, collecting or otherwise identifying performance data relating to an offer at a first POS terminal; b) determining if the performance data meets at least one criterion, such as a predetermined criterion indicating if the offer was successful; and c) automatically transmitting to at least one additional POS terminal, or otherwise making available to the additional POS terminal, data indicative of an offer which may be the same as the offer made at the first POS terminal or otherwise based on that offer.
  • the step c) referred to above may include transmitting offer rules or message content related to the offer to the additional POS terminal, or may encompass sending a pointer or other indication to direct the additional POS terminal to implement an offer for which data has already been stored in the terminal.
  • the selection of the additional POS terminal may be based on a predetermined list of other terminals to which an offer is to be propagated if success is achieved with the offer made at the first POS terminal.
  • the selection of the additional POS terminal may be based on some relationship between the first POS terminal and the additional POS terminal. For example, propagation of the offer made at the first terminal or a similar offer may be made to other terminals at locations that are near the location of the first POS terminal.
  • a rule for selecting the additional POS terminal may call for selecting terminals having a customer base similar in demographic characteristics to that of the first POS terminal.
  • a rule for selecting the additional POS terminal may also be based on a similarity with a cashier operating the POS terminal or the physical location of the POS terminal (e.g., whether the POS terminal is located in a mall or on a busy street).
  • data indicative of an offer may be transmitted to all POS terminals. Note that when a POS terminal receives such data, the POS terminal may evaluate the data before using it to determine an offer (e.g., by comparing a performance criteria associated with the received data to a performance parameter associated with a stored offer).
  • the steps listed above may be performed, for example, by one or more of the first POS terminals referred to above, one or more other POS terminals, and/or a server computer which is connected to the network of POS terminals.
  • successful offer programs may be permitted to propagate throughout a network of POS terminals, while unsuccessful offer programs are suppressed after testing.
  • the propagation of successful programs may be made under the control of a central authority by means of a server computer or master POS terminal.
  • the decision-making required for propagation of offers may be carried out in a decentralized manner, based on rules applied at many individual POS terminals.
  • the aggregate processing capacity of a complex POS network may be utilized to achieve successful outcomes, and a dynamically responsive distribution of offer programs, which would be difficult to achieve through central planning and/or human intervention.
  • Another embodiment comprises: means for identifying performance data relating to an offer made at a first POS terminal; means for determining if the performance data meets at least one predetermined criterion; means for automatically selecting at least one additional POS terminal in said network based at least in part on a result of the determining step; and means for automatically making available to said selected at least one additional POS terminal an indication of an offer based on the offer made at the first POS terminal.
  • Fig.l is a block diagram, which shows a POS network in which the present invention may be applied.
  • Fig. 2 is a schematic block diagram of a central server shown in Fig. 1.
  • Fig. 3 is a schematic block diagram of a typical one of the POS terminals shown in Fig. 1.
  • Fig. 4 is a tabular representation of a promotion rules database which may be stored in accordance with the invention in one or more of the central server and/or the POS terminals.
  • Fig. 5 is a tabular representation of a database generated in accordance with the invention and indicative of the performance of a number of offer programs.
  • Fig. 6 is a tabular representation of a propagation rules database which may be stored in accordance with the invention in the central server and/or in one or more of the POS terminals of Fig.l.
  • Fig. 7 is a tabular representation of a store database that may be stored in accordance with the invention in the central server and/or in one or more of the POS terminals.
  • Fig. 8 is a flow chart, which illustrates a process carried out in accordance with the invention for propagating successful offer programs.
  • Fig. 9 is a tabular representation of an offer database according to one embodiment of the present invention.
  • Fig. 10 is a flow chart, which illustrates a method according to one embodiment of the present invention.
  • Fig. 11 is a tabular representation of calculations made on the basis of product characteristics and weighting factor data associated with a dynamically-priced upsell offer program.
  • Figs. 12A and 12B together form a flow chart, which illustrates a process for carrying out the dynamically-priced upsell offer program.
  • Fig. 13 is a flow chart, which illustrates a process for propagating a successful configuration of the dynamically-priced upsell offer program.
  • POS terminal - a cash register or other device (e.g., a personal computer, a portable computer, or a wired or wireless telephone) used in association with a purchase transaction and having some computing capabilities and/or being in communication with a device having computing capabilities; also includes vending machines and card authorization terminals such as credit card validation terminals.
  • a POS terminal may also be, for example, a portable computing device such as a Personal Digital Assistant (PDA), a communication device such as a wireless telephone, or any other device or devices (e.g., a customer's personal computer in communication with a Web-based server) used in association with a purchase transaction.
  • PDA Personal Digital Assistant
  • Offer - an offer, promotion, proposal or advertising message communicated to a customer at a POS terminal includes upsell offers (such as dynamically-priced upsell offers), suggestive sell offers, switch-and-save offers, conditional subsidy offers, coupon offers, rebates, and discounts.
  • upsell offers such as dynamically-priced upsell offers
  • suggestive sell offers such as dynamically-priced upsell offers
  • switch-and-save offers such as conditional subsidy offers
  • coupon offers such as rebates, and discounts.
  • Upsell Offer a proposal to a customer that he or she add an additional product or service to a transaction.
  • the round-up amount may also be based on the difference between a value associated with the transaction total and any other transaction total. For example, if the transaction total without the upsell is $87.50, the round-up amount may be $ 11.50, resulting in a new transaction total of $99.00. Other information, such as an amount of sales tax associated with the transaction, may also be used to determine the round-up amount.
  • Switch-and-save offer - a proposal to a customer that another product be substituted for a product already included in a transaction, typically the substitute product is discounted from its standard price.
  • Cross-subsidy offer also referred to as a "conditional subsidy offer” - an offer to provide a benefit (e.g., to subsidize a purchase price) from a third-party merchant in exchange for the performance of a task by the customer (e.g., applying for or subscribing to a service offered by the third-party, receiving information such as an advertisement, or providing information such as answers to survey questions).
  • a benefit e.g., to subsidize a purchase price
  • a third-party merchant in exchange for the performance of a task by the customer (e.g., applying for or subscribing to a service offered by the third-party, receiving information such as an advertisement, or providing information such as answers to survey questions).
  • Base product(s - a product or group of products which, when included in a transaction, may trigger, for example, an upsell offer, a switch-and-save offer, or a cross-subsidy offer.
  • Propagation also referred to as "spreading" - transmitting an offer, or information associated with an offer, to additional POS terminals through a POS network after evaluating performance of an offer at a first POS terminal or group of POS terminals in a network.
  • Weighting factors also referred to as “weights” and “weighting configurations" - multipliers used by a POS system to determine which of several offers to make to a customer in a given transaction. Note that weighting factors may be applied to offers and/or to rules used to generate offers. In addition to weighting factors, any genetic algorithm may be used to determine an offer and/or to propagate information in a network.
  • Performance data - digitally stored information which indicates results or effects of an offer and/or circumstances in which the offer was made. Identifying performance data - includes generating, receiving, collecting, analyzing and categorizing performance data.
  • Target POS terminal - an additional POS terminal in which an offer may be implemented after the offer or a similar offer has been evaluated in a first POS terminal or group of terminals.
  • Performance characteristic of a target POS terminal - includes any information associated with a target POS terminal.
  • performance characteristics may include one or more of (a) volume of sales in a predetermined period transacted through the target POS terminal or a store in which the target POS terminal is located; (b) profitability of sales in a predetermined period transacted through the target POS terminal or a store in which the target POS terminal is located; (c) number of transactions in a predetermined period; (d) average number of items purchased per transaction in a predetermined period; (e) demographic information associated with customers who make purchases at the target POS terminal; (f) demographic information associated with an employee operating the target POS terminal; and (g) information associated with the store at which the POS terminal is located (e.g., the size of the store, the address of the store, whether the store is located in a mall).
  • FIG. 1 illustrates, in the form of a block diagram, a simplified view of a POS network in which the present invention may be applied.
  • reference numeral 20 generally refers to the POS network.
  • the network 20 is seen to mclude a plurality of POS terminals 22, of which only three are explicitly shown in Fig. 1. It should be understood that the number of POS terminals in the network may be as few as two, or, in a more realistic application of the invention, may number in the hundreds or thousands.
  • the POS terminals 22 in the POS network 20 may, but need not, all be constituted by identical hardware devices. Any standard type of POS terminal hardware may be employed, provided that it is suitable for programming in accordance with the teachings of this invention.
  • the terminals 22 may, for example, be "intelligent" devices of the types which incorporate a general purpose microprocessor.
  • the POS terminals 22 may be "dumb" terminals, which are substantially controlled by a separate computer which is either in the same store with the terminal or located remotely therefrom. Although not indicated in Fig.l, two or more of the POS terminals 22 may be co-located in the same store. Indeed, it can be expected that a typical network of the type in which the invention is applied may include numerous store locations each of which has a small or large number of POS terminals 22 installed therein.
  • the POS terminals 22 may be of the type utilized at restaurants; in this case, it can be expected that the POS terminals 22 number in the thousands, with a relatively small number of terminals, say three to six, installed in each of hundreds or thousands of different restaurant locations.
  • POS terminals 22 in a store communicate with a store controller device (not shown in Fig. 1), which in turn communicates with the central server 24.
  • Central server computer 24 is connected for data communication with the POS terminals 22 via a communication network 26.
  • the central server 24 may be constituted by conventional computer hardware, programmed in accordance with the invention.
  • the data communication network 26 may also interconnect the POS terminals 22 for communication with each other.
  • the network 26 may be constituted by any combination of conventional data communication channels, including terrestrial lines, radio waves, infrared, satellite data links, microwave links and the Internet.
  • Fig. 2 is a simplified block diagram showing some details of the central server computer 24.
  • the server 24 may be embodied as an RS 6000 server, manufactured by IBM Corporation, as programmed to execute functions and operations of the present invention.
  • the server 24 includes known hardware components such as a processor 28 which is connected for data communication with each of a data storage device 30, one or more input devices 32 and a communication port 34.
  • the communication port 34 may connect the server 24 to each of the POS terminals 22, thereby permitting the server 24 to communicate with the POS terminals.
  • the communications port 34 may include multiple communications for simultaneous connections.
  • the data storage device 30 of the server 24 which may be a conventional hard disk drive, stores a program 36.
  • This program is, at least in part, provided in accordance with the invention and controls the processor 28 to carry out functions which will be described below.
  • the program 36 may also include other program elements, such as an operating system and "device drivers" for allowing the processor 28 to interface with peripheral devices such as the input devices 32 and the communication port 34. Appropriate device drivers and other necessary program elements are known to those skilled in the art, and need not be described in detail herein.
  • the storage device 30 may also store application programs and data that are not related to the functions described herein.
  • a propagation rules database 38 and a store database 40 are also stored in the data storage device 30 .
  • a propagation rules database 38 and a store database 40 are also stored in the data storage device 30 .
  • a central server 24 that is, methods of the present invention may be performed by the POS terminals 22 themselves in a distributed, de-centralized manner.
  • Fig. 3 illustrates in the form of a simplified block diagram a typical one of the POS terminals 22.
  • the POS terminal 22 includes a processor 50 which may be a conventional microprocessor.
  • the processor 50 is in communication with a data storage device 52 which may be constituted by one or more of semiconductor memory, a hard disk drive, or other conventional types of computer memory.
  • the processor 50 and the storage device 52 may each be (i) located entirely within a single electronic device such as a cash register/terminal or other computing device; (ii) connected to each other by a remote communication medium such as a serial port, cable, telephone line or radio frequency transceiver or (iii) a combination thereof.
  • the POS terminal 22 may include one or more computers or processors that are connected to a remote server computer for maintaining databases.
  • One or more input devices 54 which may include, for example, the key pad for transmitting input signals such as signals indicative of a purchase, to the processor 50.
  • the input devices 54 may also include an optical bar code scanner for reading bar codes and transmitting signals indicative of the bar codes to the processor 50.
  • Another type of input device 54 that may be included in the POS terminal 22 is a touch screen.
  • the POS terminal 22 further includes one or more output devices 56.
  • the output devices 56 may include, for example, a printer for generating sales receipts, coupons and the like under the control of processor 50.
  • the output devices 56 may also include a character or full screen display for providing text and/or other messages to customers and to the operator of the POS terminal.
  • the output devices 56 are in communication with, and are controlled by, the processor 50.
  • Also in communication with the processor 50 is a communication port 58 through which the POS terminal 22 communicates with other components of the POS network 20, including the central server 24 and other POS terminals 22.
  • the storage device 52 stores a program 60.
  • the program 60 is provided at least in part in accordance with the invention and controls the processor 50 to carry out functions in accordance with the teachings of the invention.
  • the program 60 may also include other program elements, such as an operating system and "device drivers" for allowing the processor 50 to interface with peripheral devices such as the input devices 54, the output devices 56 and the communication port 58. Appropriate device drivers and other necessary program elements are known to those skilled in the art, and need not be described in detail herein.
  • the storage device 52 may also store one or more application programs for carrying out conventional functions of POS terminal 22. Other programs and data not related to the functions described herein may also be stored in storage device 52. Also stored in the storage device 52 are a promotion rules database 62, a promotion performance database 64, and a dynamically- priced upsell database 220. The functions and constitutions of these databases will be described below.
  • Fig. 4 is a tabular representation of the promotion rules database 62 referred to in connection with Fig. 3.
  • the rules database 62 may include the information shown in the associated Fig. or a pointer indicating the information.
  • the table of Fig. 4 includes columns 120 and 122 which have the same content as columns 80 and 82 shown in Fig. 6.
  • Column 124 in Fig. 4 includes data which is indicative of messages to be conveyed to customers for the purpose of making the offers.
  • Column 126 contains information indicative of rules for determining circumstances in which the offers are to be made.
  • the promotion offer content 124 contains information related to the offer as it is presented to the customer.
  • this field may contain the text of a prompt a cashier is directed to read to a customer, the prompt including a placeholder that may be filled in based on the product being offered.
  • the field may comprise text or image information (e.g., video information) to be displayed on a screen, or audio information to be played for the customer.
  • an offer may include an offer to purchase more than one additional item (e.g., "would you like to add a soda or desert to your order?") or no item at all (e.g., "would you like to donate your $0.37 change to charity?").
  • the upsell offer is not to be made unless a customer has purchased a sandwich and the total transaction and amount tendered call for change to be returned to the customer in an amount of at least one cent and no more than 33 cents.
  • Other factors may be taken into account in addition to or instead of those just described, including the total amount of the transaction, the quantity of inventory on hand and/or its age, and/or whether certain items are about to be discarded.
  • Further rules may take into account additional factors relating to the mix of products included in the transaction. The further rules may be employed to determine which product or products should be included in the upsell offer.
  • the entry in column 126 prescribes a simple rule in which the offer is to be made whenever a customer purchases a sandwich and has not purchased fries.
  • other or additional rules may be applied to a suggestive sell, which may be related to factors such as the identity of the customer, the time of day, whether or not the store is busy, and so forth.
  • the promotion rules require that the customer is not already subscribed to the service provided by the third-party merchant, and that an offer of a cross-subsidy from the merchant not previously have been made to the customer. It will be appreciated that in order to determine whether a customer qualifies under these promotion rules, the customer must be identified, and a database which includes the information needed to determine qualification must be available and must be accessed.
  • the promotion rules prescribe that the product to be substituted for must have been included in the transaction and the potential substitute product must be within 7 minutes of being discarded. Variations upon or substitutions for all of these rules could be contemplated. For example, a minimum purchase total may be required as a qualification in the case of any of these offers, or, alternatively, if the purchase total is greater than a given amount, then the transaction may be considered to be disqualified from applying an offer.
  • the rules governing the upsell offer may include imminent expiration of a potentially upsold product. The rules governing the switch and save offer need not have anything to do with imminent expiration of the potential substitute product.
  • Fig. 5 is a tabular representation of an example of a promotion performance database 64, previously referred to in connection with Fig. 3. The purpose of this database is to store data indicative of the effectiveness of the offer made at the POS terminal 22 in which the performance database 64 is stored.
  • the performance database 64 includes four columns: 140, 142, 144 and 146.
  • Column 140 lists the offers for which the performance data is stored, by identification code number.
  • Column 142 stores data which indicates what percentage of the time each of the offers was accepted.
  • Column 144 stores data which indicates the total amount of the purchase, on average, for the transactions in which the respective offers were made and accepted.
  • the data of columns 140 and 142 and 144 taken alone or in combination, may be used to determine whether the respective promotions are considered successful (e.g., whether the promotions increased number of items being sold, increased an average total transaction amount, and/or increased an amount of profit earned by a merchant).
  • Column 146 lists data indicative of circumstances under which the offers were successful, particularly the time of day when the offers were popular. As will be seen, data of this type, including other data indicative of circumstances in which the offers were accepted or were not accepted, may be used to determine targets for propagating the offers, as well as modifications that may be made in the offer as propagated.
  • Fig. 6 represents in tabular form the propagation rules database 38 referred to in connection with Fig. 2.
  • the table of Fig. 6 includes columns 80, 82, 84 and 86 which respectively include a code for identifying an offer or promotion, a brief description of the type of the offer, one or more criteria for determining whether the offer was successful, and rules for propagating the offer in the network of POS terminals if the offer was found to be successful.
  • the first entry in Fig. 6 carries the offer identifying code "01" and is concerned with a dynamically-priced upsell offer.
  • a dynamically-priced upsell offer is a type of promotion in which an operator of a POS terminal offers to sell to a customer an additional product in exchange for a round-up amount that may be, for example, the amount of change which was calculated as being due to the customer at the end of the transaction. Details of an example of a dynamically-priced upsell offer will be described below. For present purposes it is sufficient to note that the product or products to be suggested for an upsell may depend on such factors as which products have already been included in the transaction, and the value of the round-up amount.
  • the criteria for determining whether the offer was successful are stated as “no dilution” and "increase in demand for upsell products".
  • the first criterion, "no dilution” means that the quantity of sales made of the upsold product at full price are not decreased significantly (e.g., unprofitably) during the period when the upsell offer is in effect, as compared to a comparable period.
  • the second criterion indicates that the overall demand for the upsold products must significantly increase during the period of the offer. Note that the criteria associated with the success of an offer may not be the same for every offer. For example, different upsell offers may have different criteria for success.
  • an offer does not need to be categorized as either "successful" or "unsuccessful,” but instead may be rated based on a range of effectiveness. For example, information associated with a highly successful offer may be propagated to twenty additional POS terminals 22 while information associated with a moderately successful offer may only be propagated to three additional POS terminals 22.
  • the entry for the upsell offer in column 86 sets forth a rule for propagating the offer to additional POS terminals if the offer is found to be successful at a first POS terminal.
  • the rule prescribes that the offer is to be propagated to the three nearest POS terminals relative to the first POS terminal.
  • the location of the three nearest terminals is to be determined by reference to zip codes which identify the locations of other POS terminals.
  • the second entry in the table of Fig. 6 has the identifying code "02" and is concerned with a suggestive sell offer.
  • the operator of a POS terminal simply suggests to the customer at the end of the transaction or at some other point in the transaction that the customer purchase an additional product.
  • the suggestive sell message may be delivered by a screen display and/or a speaker which is part of or connected to the POS terminal.
  • the entry in column 84 for this offer indicates that the offer is to be considered successful if it is accepted more than 30% of the time.
  • the entry in column 86 specifies, by an Internet Protocol (IP) address, two particular POS terminals to which the suggestive sell offer is to be propagated if it is found to be successful at a first POS terminal.
  • IP Internet Protocol
  • the information in column 86 further specifies by IP address three other POS terminal locations to which the suggested sell offer is to be propagated if found to be successful at the group of POS terminals to which it was propagated after the initial successful test.
  • the POS terminals specified to receive the offer may be specified by data other than an IP address.
  • data may be, for example, an identifying code for the target POS terminals. Whether in the form of an identifying code, an IP address, or in some other format, data which specifically identifies a particular target POS terminal may be referred to as a "target identifier".
  • the third entry in the table of Fig. 6 has an identifying code "03" and is concerned with a cross-subsidy offer.
  • this type of offer the customer is advised that some or all of the cost of the transaction will be paid for by a third party merchant if the customer agrees to enter into a transaction or otherwise do business with the third party merchant.
  • One system for providing such a benefit is disclosed in U.S. Patent Application Serial No. 09/282,747 entitled “Method and Apparatus for Providing Cross-Benefits Based on a Customer Activity” and filed March 31, 1999.
  • a customer at a restaurant may be told that his or her meal is free if he or she agrees to transfer his or her long distance service to a telecommunications company subsidizing the offer.
  • the entry in column 84 for the cross-subsidy offer indicates that the offer is to be deemed successful if it is accepted more than 15% of the time.
  • the entry in column 86 for this offer indicates that it is to be propagated to POS terminals in other stores which have a customer base which is similar in its demographic characteristics to the store at which the offer was found to be successful. Ways in which other stores may be determined to have similar demographic characteristics relative to a first store will be described below.
  • the last entry shown in the table of Fig. 6 has an offer identification code "04" and is concerned with a "switch-and-save" offer.
  • the operator of the POS terminal suggests to the customer that he or she substitute, for a product that has been ordered, another similar product, normally sold at a higher price, but at a reduced price which may be the same as that of the product to be substituted for.
  • An example of a switch and save offer might be, "How about a cheeseburger instead of that hamburger, for the same price?"
  • whether an offer will be deemed successful may be based on whether sales of a promotional item increases by a predetermined amount (e.g., a predetermined amount associated with a local advertising campaign).
  • the rule for propagating the offer is to spread the offer to other stores having a customer base with a demographic characteristic similar to that of customers who were found to accept the offer at stores where the offer was successful.
  • Collection of customer characteristics may be accomplished in accordance with conventional practices by identifying customers who shop at the store where the offer is being made, collecting information about the customers, issuing bar coded or magnetic stripe cards, smart cards or the like to customers to identify the customers, and then reading the customer identification cards at the time of transactions with the customers.
  • customers may identify themselves via a frequent shopper card, a payment card (e.g., a credit card), a customer identifier (e.g., entered by the customer at a POS terminal), or any other method.
  • the simplified example of the propagation rules database 38 shown in Fig. 6 only lists four offer programs; however, a smaller or larger, number of offer programs may be stored in the propagation rules database 38.
  • a dynamically-priced upsell offer, a suggestive sell offer, a cross-subsidy offer and a switch-and-save offer are listed in Fig. 6, it is contemplated to include in the database two or more varieties of some or all of these types of offers, instead of a database storing predetermined offers, a POS terminal may store information associated with a process used to determine an offer. This may be accomplished via rules, a genetic algorithm, a neural network, and/or other programming techniques.
  • Offers may be displayed on POS terminals and/or Web sites (e.g. as banner advertisements displayed while customer access a Web site or adjust the contents of a virtual shopping cart).
  • the propagation rules database may include other types of data in addition to those illustrated in Fig. 6. For example, there may be identified for each offer the POS terminal or terminals at which the offer is currently being evaluated or is to be evaluated in the future.
  • the database may also indicate a time period during which the evaluation is being carried out for each relevant POS terminal or terminals. The time period could be specified in terms of a starting date and time and an ending date and time.
  • the present invention also contemplates types of criteria for determining success in addition to those indicated in Fig. 6.
  • an offer may be deemed successful if it increases revenue, either on a per transaction basis and/or on an aggregate basis, for either or both of the POS terminal at which the offer is being made or at the store location.
  • the criteria may also be targeted so as to be based on an increase in revenue for a particular portion of the selling day, week or month; e.g., an increase in revenue at lunch or on weekends.
  • Another criterion for determining success may be based on an increase in profit in addition to or instead of an increase in revenue.
  • Other criteria that may be considered to indicate success would be an increase in the number of customer visits and/or the number of transactions and/or the number of items purchased in each transaction.
  • Still another criterion that might be employed would be a reduction in the level of inventory.
  • Other possible criteria for determining success may be a decrease in labor costs required to produce products sold in connection with the offer or in staffing the POS terminal or terminals at which the offer is made, an increase in the rate at which inventory turns over at the store at which the POS terminal or terminals are located, a reduction in the amount of waste or the average quantity of items of inventory in the store, or an increase in customer retention rates for the store and/or frequency of customer visits at the store.
  • Other criteria for success may include the amount of time required to handle transactions, on average, at the POS terminal or terminals at which the offer is made; the average amount of time that customers wait for service at the POS terminal or terminals; and/or the amount of time required to produce products referred to in the offer. It is also contemplated to use, as a criterion of success, combinations of and/or trends in the factors which have been enumerated above. There may be other useful criteria of success not listed above that fall within the scope of the present invention.
  • Fig. 7 is a tabular representation of the store database 40, previously referred to in connection with Fig. 2.
  • the table of Fig. 7 includes a column 100 which identifies store locations, columns 102, 104 and 106, which list demographic characteristics of the customer bases for the respective stores, column 108 which indicates the average dollar amount per transaction at the stores, and column 109 which indicates the IP address or address of POS terminals associated with each store.
  • the particular demographic data in columns 102, 104 and 106 respectively is average customer age, average per capita income for the customers, and percentage of customers who are male.
  • the data in columns 102, 104 and 106 may be gathered by surveys or other conventional means, and the data in column 108 can be gathered by conventional techniques for keeping track of store operations.
  • the system may use individual customer history and select those offers that are more likely to be accepted based on the customer's proclivity to accept certain types of offers under certain conditions (e.g., order content, time of day, location, and/or change amount due).
  • Other information that may be stored in the store database 40 may be associated with, for example, a destination of an order (e.g., eat-in, take-out, or drive-through), a total number and/or a frequency of customer visits, an average check-out amount, a contribution margin, and/or c rent product advertising information.
  • information associated with particular customers may be used by the POS network 20 to determine an offer and/or to propagate information.
  • entries for only three stores are shown in Fig. 7, it is to be understood that, in practice, data for a much larger number of stores may be maintained in the store database 40. It is also contemplated to include many additional types of data in addition to that shown in Fig. 7. Other types of information that may be included in the store database include the size of the store, proximity to other stores of the chain and/or competitors' stores, types of facilities at the store, including capabilities for producing and/or selling certain types of product, whether the store has drive-through selling capabilities, and whether the store has been recently remodeled.
  • sales history of the store may be provided in addition to or instead of the average transaction amount.
  • types of data may be total revenue, total profitability, various types of revenue or profitability figures broken down by time of day, month, week and/or year, number of transactions per day, number of items per transaction.
  • Other store performance indicators such as labor and inventory costs, inventory level and inventory turns may also be included.
  • additional characteristics of the customer base may be included, such as distribution of customers among various age categories, which may also be broken down by gender. Additional information could include marital status, number of children, home ownership versus renting, type of car owned, shopping habits and any of the other numerous ways in which customer populations are segmented for marketing analysis.
  • the terminal addresses 109 may be used, for example, by other POS terminals 22 when transmitting transaction information (e.g., a modified offer rule) through the POS network 20.
  • transaction information may instead be broadcast to every POS terminal 22 in the POS network 20.
  • the transaction information may include information associated with an offer's past success (e.g., how successful and in what environments).
  • the target POS terminal 22 may compare the success information and information associated with the target POS terminal 22 to determine if an order should be modified. According to another embodiment, each target POS terminal 22 may simply use the received information without an evaluation.
  • the individual stores may receive the information and may apply some, all, or modified portions of the information based on its own history. For example, offers may be received by a store that contains pricing information that does not apply to the particular store. In this case, the system would receive and apply some of the information (e.g., the rules or weights) without applying the conflicting information (e.g., the price).
  • a first step 160 represents the central server receiving offer performance data from a POS terminal at which an offer has been evaluated.
  • the performance data may be transmitted from the POS terminal to the central server in response to a query from the central server.
  • the POS terminal may transmit the performance data at its own instigation, say at the end of a predetermined period during which the evaluation of the offer was to occur.
  • the performance data may include all of the data for the given promotion as listed in the performance database 64 in the POS terminal, or may only be selected data (e.g., the rules, weights, and script text) requested by the central server after consulting the data in column 84 of the propagation rules database 38 (Figs. 2 and 6) to ascertain what information is needed to determine success of the offer.
  • Step 160 may include receiving performance data from one POS terminal, or from more than one POS terminal, either all located at the same store, or located at different stores. It is contemplated to determine the success of an offer based on performance data from as few as one POS terminal or from as many as thousands of POS terminals. Data may be applied in its entirety and/or only partially (e.g., using rules or filters) to "adjust" the information prior to applying the information to the receiving store's database.
  • Step 162 represents the central server retrieving, from the propagation rules database 38, criteria for determining success of the offer. It will be appreciated that step 162 may occur either before or after step 160.
  • Decision block 164 represents a determination as to whether the offer was successful. This determination is made on the basis of the performance data received at step 160 and the success determination criteria retrieved at step 162. If it is determined at step 164 that the promotion was unsuccessful, the process of Fig. 8 may simply terminate, as indicated at 166. According to another embodiment, instead of determining whether an offer was successful, the central server 24 may determine to what extent the offer was successful. Alternatively, the central server may be programmed to modify the offer in one or more respects and to instruct the POS terminal or terminals to reevaluate the offer as modified. As another alternative, the central server may be programmed to propagate the offer to POS terminals which are found to be dissimilar in one or more respects from the POS terminal or terminals at which the offer was unsuccessful.
  • the central server 24 may instead propagate information to POS terminals 22 such that certain offers will not be provided (i.e., suppressing certain offers). If at block 164 it was determined that the offer was successful, then at step 168 the central server (or more specifically, processor 28) retrieves from the data storage device 30 the propagation rule listed, for the offer found to be successful, in column 86 (Fig. 6) of the propagation rules database 38. On the basis of the retrieved rule, the central server identifies an additional POS terminal or terminals to which the offer is to be propagated (step 170).
  • Step 170 may be trivial if the propagation rule itself explicitly specifies particular POS terminals, or store locations, to which the offer is to be propagated.
  • the central server accesses a database which stores geographic information as to the location of POS terminals. The central server then processes this data by comparing it with the location of the first POS terminal to select the target POS terminals. In cases where the target POS terminals are to be selected based on demographic characteristics (as in the last two entries in column 86 in Fig. 6), the central server accesses a database of demographic information concerning terminals or store locations in the POS network.
  • Similarity of a potential target POS terminal to a first POS terminal may be determined in a number of ways. For example, where the customer bases of two locations have median incomes that differ by no more than $3,000, the customer bases may be considered to be similar. In addition or alternatively, the customer bases may be required to have an average age that does not differ by more than 5 years. The same or other demographic characteristics of customer populations (including populations which were found to accept the offer at the first POS terminal) may be analyzed to detect which populations have characteristics that fall within a standard deviation of each other. Those of ordinary skill in the art will recognize other ways in which customer bases may be determined to be similar to each other. It will also be recognized from the foregoing how customer bases may be found to be dissimilar from each other.
  • Target POS terminals may also be selected on the basis of being in stores of the same size, having the same or similar facilities and/or an equal degree of proximity to or distance from competitors' stores as the store(s) in which the offer was evaluated. It is also contemplated that step 170 may include selecting one or more target POS terminals on the basis of performance data which indicates circumstances in which the offer was successful. For example, if an offer was found to be successful only during a certam time of day, such as a breakfast period, step 170 may include identifying target locations which do a relatively large proportion of their business during breakfast. It will be appreciated that a suitable propagation rule governing this type of selection process would be stored in column 126 (Fig. 4) for the offer in question.
  • the central server performs step 172, in which it transmits to the additional or target POS terminals the relevant offer, content and rule information, such as that discussed in connection with Fig. 4.
  • the central server may transmit to the target POS terminals a trigger message or pointer which causes the target POS terminals to begin to make offers like the offer determined to be successful at step 164.
  • the central server may instruct another computer or one of the POS terminals to transmit the offer information or a trigger message to the target POS terminals. If and when the offer is found to be successful at the target POS terminals, steps of Fig. 8 may be repeated so that the offer is propagated to still other POS terminals of the POS network 20.
  • the number and/or some other characteristics of target POS terminals may be determined based on how successful other offers proved to be after having been tested at and propagated from the first POS terminal. For example, a number of offers propagated from a first POS terminal may have proved to be very successful at a second POS terminal, while no similarities in customer base, transaction history, etc. between the two POS terminals were identified. In this case, the first POS terminal may continue to propagate offers to the second POS terminal based solely on the past success of the propagated offers.
  • the present invention also contemplates basing selection of target POS terminals on a combination of demographic and geographic factors. It is known to categorize zip codes according to socio-economic characteristics of people who live in the zip codes. This categorization of zip codes can be used to formulate a propagation rule like this: "Spread the offer to POS terminals located in zip codes which are in the same category as the zip code of the POS terminal in which the offer was successful.” Other rule variables may include, for example, traffic patterns and/or demographics of the customers, weather patterns, and competitive analysis (e.g., offers being made by other merchants in a particular area).
  • a propagation rule may prescribe that a successful offer only be propagated to POS terminals staffed by experienced operators.
  • the experience level or another characteristic of an operator at a POS terminal where an offer is evaluated may also be stored and analyzed as performance data, i.e., a circumstance in which the offer was made.
  • operators may be required to log on to POS terminals, in accordance with conventional practices, and a database may be maintained of information concerning the operators.
  • target POS terminals Another factor that may be used in selecting target POS terminals is a historical record of transactions at potential target POS terminals.
  • a propagation rule may hold, for instance, that a successful offer only be propagated to POS terminals which have historically done a relatively large amount of business, or to POS terminals which have historically done a relatively small amount of business.
  • This selection of a target POS terminal may be based on performance characteristics of the potential target such as revenue and/or profitability. Target selection may also be based on a characteristic of a mix of products sold at the potential target POS terminal.
  • a successful offer is not implemented at a potential target POS terminal for some predetermined reason (say the potential target lacks a necessary facility or is already very successful), it may be said that a rejection condition is satisfied at the potential target terminal, and a successful offer is not propagated to a potential target when a rejection condition is determined to be satisfied at the potential target terminal.
  • the determination that a rejection condition is satisfied may be made at the central server, at the potential target POS terminal, or at another POS terminal.
  • Selection of target POS terminals may also take into account physical or programmed characteristics of potential target terminals.
  • an offer which requires a certain type of display screen would only be propagated to POS terminals having such a screen; an offer which requires the implementing POS terminal to be programmed in a certain manner would only be propagated to POS terminals that have been so programmed.
  • an offer is not be propagated to a POS terminal that has already been programmed with another offer or offers that are incompatible with the offer under consideration.
  • the process of selecting a target POS terminal may include determining whether the offer in question is compatible with other offers being made at the potential target. For example, a POS terminal offering dynamically-priced upsell may not be compatible with a successful suggestive sell offer.
  • Selection of a target POS terminal may also include determining the cost of implementing the offer at the potential target, and determining whether the store at which the potential target terminal is located has facilities and/or materials required to make the offer and/or to provide a product or service related to the offer.
  • the present invention contemplates that the server may modify an offer, based on performance data, or for other reasons, before propagating the offer, as modified, pursuant to step 172. For example, if the acceptance rate for the offer was much higher at one time of day than at other times, the rules governing the offer may be modified to provide that the offer is to be made at the target POS locations only at the time of day in which the high acceptance rate was found.
  • Step 160 of Fig. 8 may include receiving performance data with regard to more than one type of offer, whether made at the same POS terminal or group of terminals or at different POS terminals.
  • the performance data may be compared to respective evaluation criteria for the offers, and respective levels of success compared from one offer to another. Accordingly, the determination at 164 may be not simply whether an offer was successful relative to its own criteria, but which of two or more offers are to be deemed more successful or the most successful.
  • the more successful offer or offers may be propagated and the less successful offer or offers suppressed. Alternatively, all offers may be propagated to some extent, but the more successful offers propagated to a larger number of target POS terminals than the less successful offers.
  • least successful offers may be suppressed, moderately successful offers propagated to a relatively small number of target POS terminals, and most successful offers propagated to a larger number of target POS terminals.
  • unsuccessful offers may be propagated to target POS terminals having dissimilar performance characteristics.
  • Fig. 9 is a tabular representation of a database 300 which stores potential upsell offers for a number of products.
  • a table may be stored, for example, at a first POS terminal 22.
  • the information stored in the table may be created and updated, for example, by an operator, the central server 24, and/or other POS terminals 22.
  • the table shown in Fig. 9 includes base products 302 representing an order placed by a customer. For example, a customer may order a "burger" and a "soda” as indicated by the first entry of the table.
  • the table also indicates an offer 304 that should be made to the customer based on the preliminary order. For example, when a customer orders a burger and a soda, the POS terminal 22 will determine that the customer should be offered "fries" in addition to the base products 302.
  • the base products 302 and the offer 304 thus indicate a rule used by the POS terminal 22 to determine an offer.
  • the table also indicates an acceptance rate 306 associated with the rule. For example, 25% of the customers have accepted an offer to purchase fries after they ordered a burger and a soda via the first terminal 22.
  • Fig. 10 illustrates a method of propagating information in a POS network according to an embodiment of the present invention.
  • the method shown in Fig. 10 may be performed, for example, by the first POS terminal 22 and/or the central server 24.
  • transaction information is received.
  • the transaction information may indicate, for example, the base products 302 that a customer wishes to purchase.
  • the transaction information may comprise any information associated with the transaction.
  • the transaction information may include one or more of: demographic characteristics of the customer and/or an employee, a time of day, and phrasing of the offer as it was presented to the customer.
  • transaction information may be received, for example, via a POS terminal (e.g., via the input device 54), an operator of a POS terminal 22, and/or a monitoring device (e.g., a microphone coupled to a processor configured to execute a voice recognition process).
  • an offer is determined. This may comprise, for example, retrieving the offer 304 based on the base products 302.
  • the offer is also randomly determined on occasion.
  • POS terminal 22 may disregard the offer 304 once every ten offers and randomly select a different item to be offered to the customer (or one out often POS terminals 22 in a store may always disregard the offer 304).
  • the POS terminal 22 instead instructs an operator of the POS terminal to select a different item.
  • the operator may indicate which different item he or she selected (e.g., fries or soda) using the input device 54 of the POS terminal 22.
  • performance data is evaluated. This may comprise, for example, comparing an acceptance rate 306 associated with a predetermined offer 304 with an acceptance rate associated with a randomly determined offer.
  • any performance data associated with transactions may be evaluated, including, for example, one or more of: an amount of profit (e.g., associated with a particular transaction or associated with a store), a level of customer satisfaction, a length of time associated with an average transaction, and a quality of service provided during the transaction (e.g., the accuracy of an answer to a customer's question provided by an operator of the POS terminal 22).
  • an amount of profit associated with a transaction may be based at least in part on a payment received from a third party (e.g. , a payment from a manufacturer to a retailer in exchange for selling an item).
  • information is propagated to at least one other POS terminal 22 in the POS network 20. For example, if the acceptance rate associated with a randomly determined offer is greater than an acceptance rate 306 associated with a predetermined offer 304, a POS terminal 22 may instruct one or more other POS terminals to modify the predetermined offer 304. The first transaction terminal 22 may also, of course, decide to modify the predetermined offer 304.
  • any information associated with transaction may be propagated at 314.
  • a modified rule or a new rule may be transmitted to other POS terminals 22 (e.g. , a modified phrasing of an offer to be provided to a customer, or a new rule indicating that a time of day parameter should be added to an offer generation process).
  • performance information may be propagated.
  • other POS terminals 22 may use the performance information, for example, to determine if a predetermined offer should be modified.
  • propagation rules themselves may be propagated.
  • POS terminals may be instructed to only forward information to three additional POS terminals 22 after a 2% increase in an acceptance rate 306.
  • transaction information may be propagated by transmitting some or all of the information to other POS terminals 22.
  • some or all of the information may instead be sent to the central server 24.
  • a first POS terminal may send a new transaction rule to the central server 24, and an indication of the success of the new transaction rule to other POS terminals 22.
  • the other POS terminals 22 may then function to determine whether or not retrieve the new transaction rule from the central server 24.
  • Fig. 11 is a tabular representation of a dynamically-priced upsell database 220, of the type refe ⁇ ed to in connection with Fig. 3, which stores potential upsell scores for a number of products.
  • the table shown in Fig. 11 includes a store identifier field 180 which indicates the store in which the offer is being evaluated.
  • a field 222 indicates the base products which, when included in a transaction, trigger consideration of the potential upsell products listed in database 220.
  • the particular set of base products indicated in field 222 in this example consists of a cheeseburger and a cola. However, the set of base products may be indicated more generally (e.g., "a burger and a drink") or more specifically (e.g., "a cheeseburger and a 32 ounce cola").
  • Columns 226, 228, 230, 232 and 234 of Fig. 11 list the potential upsell products to be considered when the base products listed in field 222 are ordered.
  • Column 223 lists the perishability, popularity and profitability categories of the product. The concept behind tracking the popularity of the product may be that the restaurant chain wishes to promote products that are relatively unpopular, in which case a higher score is accorded to less popular products. Similarly, a restaurant may wish to promote products that are relatively popular (e.g., products associated with an advertising campaign).
  • the propagation of information in the POS network 20 is based on sales mix data (e.g., information associated with individual item popularity). According to another embodiment, the propagation of information in the POS network 20 is based on market basket data (e.g., information associated with particular groups of items and/or the frequency of particular combinations of items).
  • Column 224 lists weighting factors to be applied, respectively, to the scores for the products associated with each of the categories 223.
  • the weighting factors 224 may be used as follows to improve the success of dynamically-priced upsell offers.
  • a product upsell is scored based on a number of categories 223, and each score is multiplied by the weighting factor 224 associated with each category 223 to generate a weighted score.
  • a particular product upsell is selected based on the weighted score associated with the product.
  • the upsell product that is selected may be determined.
  • Figs. 12A and 12B together constitute a flow chart which illustrates a process by which a POS terminal 22 makes a dynamically-priced upsell offer to a customer in accordance with this exemplary embodiment of the invention.
  • the POS terminal 22 receives one or more signals which indicate the customer's selection of products for a transaction. These products form a set of base products which may trigger consideration of a dynamically-priced upsell offer. The POS terminal then calculates a total amount due for the transaction on the basis of the products selected by the customer. This step is represented by block 212 in Fig. 12 A.
  • the POS terminal retrieves from its storage device 52 the potential upsell score database 66 which corresponds to the set of base products indicated at step 210. The POS terminal then also accesses the weighting factor database 68, as indicated by step 216.
  • the weighting factors are applied to the potential upsell scores for the various products to generate a set of weighted scores.
  • Table 220 shown in Fig. 11 illustrates the set of weighted scores which results from step 218.
  • Columns 226, 228, 230, 232 and 234 respectively indicate the weighted scores generated for the various products listed in the dynamically-priced upsell database 220 as well as totals of the weighted scores.
  • step 236 The step of arriving at the totals listed as the last items in columns 226, 228, 230, 232 and 234 is indicated by step 236 in Fig. 12A.
  • the POS terminal determines which of the potential upsell products received the highest score and selects that product to be the subject of an upsell offer.
  • the product receiving the highest score is an apple pie; accordingly, an apple pie is the product selected for the upsell offer.
  • Step 238 may also include a process of determining whether the potential upsell product with the highest score is qualified, taking into account the amount of change due to the customer. That is, the upsell offer may be arranged so that certain products will not be offered unless the amount of change due is sufficient to justify offering them.
  • step 238 may include selecting the product with the highest weighted total score which also is qualified to be offered for the amount of change which is due to the customer. Additionally, the system may randomly (or semi-randomly) select an upsell product from a group of upsell products (e.g., from the three upsell products having the highest weighted total score).
  • the POS terminal causes the upsell offer for the selected product to be made to the customer. This may be done by prompting the operator of the POS terminal with a display on the terminal or by displaying the offer directly to the customer. As will be understood from the previous discussion of Fig. 4, the offer may take the form of saying to the customer "How about a (selected product) for your change?" It is then determined at decision block 242 in Fig.
  • step 244 the customer is given his change (step 244) and an entry is made in a transaction database to the effect that the offer was declined (step 246).
  • the routine of Figs. 12A and 12B then ends, as indicated at 248.
  • the customer is provided with the upsell product (step 250) and an entry in made in the transaction database to indicate that the offer was accepted (step 252).
  • Fig. 12A and 12B may be carried out at the POS terminal 22 each time during the offer evaluation period that the base products are selected and none of the potential upsell products are selected.
  • the potential upsell product which is not included in the order and has the highest score resulting from steps 214, 216, 218 and 236 is offered to the customer as an upsell product for the customer's change.
  • the particular upsell score database accessed at step 214 depends upon which set of base products the customer selects.
  • the weights shown in Fig. 11 are applied to potential upsell scores to generate weighted scores at the time of each transaction (i.e., after the customer has placed an order).
  • the weighted scores of Fig. 11 may be generated ahead of time; for example, the data shown in Fig. 11 may be generated when product scores and weighting factors are first stored in the POS terminal.
  • Fig. 13 illustrates a process by which the central server 24 collects from a number of different POS terminals respective performance data, and determines on the basis of the performance data which of a number of different weighting configurations evaluated in the various POS terminals resulted in the most successful offers. Then the best weighting configurations are propagated to additional locations.
  • Step 260 in Fig. 13 indicates that the server computer receives from a first POS terminal (or all of the POS terminals at a first location) information which indicates the POS terminal or terminals providing the information, the weighting configuration employed in making an upsell offer at the POS terminals, and the extent to which an offer was successful.
  • Step 262 represents the central server receiving the same information from one or more additional POS terminals or POS locations.
  • the central server determines which of the weighting configurations resulted in the highest success rate for an upsell offer.
  • step 266 at which the central server selects one or more target POS terminals to which the most successful weighting configuration is to be propagated (e.g., based on information in the propagation rules database 38).
  • propagation rules call for propagating the highest rated weighting configuration to similar POS locations. These locations may be selected on the basis of geographic proximity to the most successful evaluating POS location or based on demographic similarity, as has been discussed above. According to another embodiment, locations may be selected based upon similarities in rules and/or weighting criteria among one or more stores (or even the order and weighting of the rules themselves).
  • step 268 the best weighting configuration is transmitted to the selected target POS terminals for use in an upsell offer at those terminals.
  • weighting configuration adjustments are transmitted to the selected target POS terminals at step 268 (e.g., "increase the popularity weighting factor by .2"). The procedure then ends as indicated at 270.
  • the propagation rules database 38 and the store database 40 are stored in a central server computer, which also performs the evaluation and propagation functions described in Fig. 8 and 13.
  • a central server computer which also performs the evaluation and propagation functions described in Fig. 8 and 13.
  • the generation of the performance data as well as the evaluation of that data in comparison with success determination criteria and the selection of target POS terminals for propagation of a successful offer may all be performed in a single one of the POS terminals 22.
  • the evaluation and propagation functions may also be performed in a POS terminal different from the POS terminal in which the performance data was generated. It is thus contemplated to provide the POS network 20 without the central server 24 shown in Fig. 1.
  • the various individual POS terminals 22 may all be programmed to generate, evaluate and propagate offers according to various rules, in a manner such that successful offers are spread to larger and larger numbers of terminals in the network, whereas less successful offers are suppressed or maintained in force in a smaller number of terminals or carry less weight.
  • the process of evaluating and propagating offers may proceed without central control and in a manner that is substantially unpredictable, with the successful offers spreading in a manner akin to biological species such that the "fittest" offers survive and multiply.
  • POS terminals could select between two successful offers both propagated to the same POS terminal by exclusively using the more successful of the two offers. Alternatively, both offers can be used part of the time, with the more successful offer used more frequently than the less successful offer.
  • Offers that are less successful may be systematically changed as to one or more of the rules which determine the offer and then may be used again as modified.
  • “sniffer” program may be employed to detect offers that have failed in a predetermined number of modifications and/or a predetermined number of locations and to prevent such offers from being used further.
  • the system may operate to propagate the offer to all or a large number of other locations.
  • all offers may generate a message to be propagated in the POS network 20.
  • the message may comprise, for example, rule information, results information, and/or weighting action instructions.
  • Each POS terminal 22 may then adjust a rule or weighting information based on a received message.
  • all successful offers may generate such a message to be propagated in the POS network 20 (e.g., instructing all POS terminals 22 to increase a particular weight by a small amount). In this way, successful offers may eventually become more heavily weighted.
  • a central server may gather sales and rules data to identify, for example, general trends in sales (e.g., product popularity), acceptance rates. The central server may then propagate information as appropriate (e.g., to create or modify offer rules, offer scripts, and/or propagation rules).
  • MVT multivariable testing
  • teachings of the present invention may also be applied in a network of intelligent vending machines, gaming devices (e.g. , video slot machines) and/or in a network of card authorization terminals such as credit card validation terminals.
  • gaming devices e.g. , video slot machines
  • card authorization terminals such as credit card validation terminals.
  • the teaching may be employed wherein the POS terminal 22 comprises a Web-server or a personal computer coupled to a Web-server (e.g. , to propagate information associated with successful banner advertisements and/or Web-based ordering).
  • the POS network 20 may simply comprise one or more Web-servers.
  • the teaching are not limited to the propagation of information associated with offers (e.g., legally binding offers or other types of offers).
  • any information related to transactions e.g., transactions involving an actual sale or other types of transactions
  • other interactions e.g., customer interactions or other types of interactions
  • Types of information that may be used to determine an offer and/or to propagate information in the POS network 20 include cashier performance information (e.g., information associated with cashier ability, speed, and/or training), cashier compensation information, item pricing (e.g., price points associated with items and/or groups of items), software configuration options, and supply chain processes.
  • the propagation of information may be associated with interactions with customers and/or with other software programs (e.g., a software application executing at a POS terminal 22).

Abstract

A promotional offer is made to customers who engage in transactions at a first point-of-sale (POS) terminal in a network of POS terminals. It is determined whether the offer is successful, and additional POS terminals may be selected to receive data indicative of the offer. The additional POS terminals may be selected before the offer is evaluated at the first POS terminal or may be selected after the evaluation (e.g., based on considerations determined prior to the evaluation). Data setting forth rules for carrying out the offer and one or more messages to be conveyed to customers in making the offer may be transmitted to the selected additional POS terminals. The process of evaluating the offer, selecting additional POS terminals to receive the offer, and transmitting the necessary offer data to the additional POS terminals may be carried out in a central server associated with the POS network, and/or in one or more of the POS terminals.

Description

DYNAMIC PROPAGATION OF PROMOTIONAL INFORMATION IN A NEWORK OF POINT-OF-SALE TERMINALS
CROSS-REFERENCE TO RELATED APPLICATIONS
This application claims the benefit of provisional U.S. Patent Application Serial No. 60/150,630 filed on August 25, 1999. The entire content of this application is incorporated by reference herein. The application is related to: U.S. Patent Application Serial No. 09/052093 entitled "Vending Machine Evaluation Network" and filed March 31, 1998; U.S. Patent Application Serial No. 09/083,483 entitled "Method and Apparatus for Selling an Aging Food Product" and filed May 22, 1998; U.S. Patent Application Serial No. 09/282,747 entitled "Method and Apparatus for Providing Cross-Benefits Based on a Customer Activity" and filed March 31, 1999; U.S. Patent Application Serial No. 08/943,483 entitled "System and Method for Facilitating Acceptance of Conditional Purchase Offers (CPOs)" and filed on October 3, 1997, which is a continuation-in-part of U.S. Patent Application Serial No. 08/923,683 entitled "Conditional Purchase Offer (CPO) Management System For Packages" and filed September 4, 1997, which is a continuation-in-part of U.S. Patent Application Serial No. 08/889,319 entitled
"Conditional Purchase Offer Management System" and filed July 8, 1997, which is a continuation-in-part of U.S. Patent Application Serial No. 08/707,660 entitled "Method and Apparatus for a Cryptographically Assisted Commercial Network System Designed to Facilitate Buyer-Driven Conditional Purchase Offers," filed on September 4, 1996 and issued as U.S. Patent No. 5,794,207 on August 11, 1998; U.S. Patent Application No. 08/920,116 entitled "Method and System for Processing Supplementary Product Sales at a Point-Of-Sale Terminal" and filed August 26, 1997, which is a continuation-in-part of U.S. Patent Application No. 08/822,709 entitled "System and Method for Performing Lottery Ticket Transactions Utilizing Point-Of- Sale Terminals" and filed March 21, 1997; and U.S. Patent Application Serial No. 09/135,179 entitled "Method and Apparatus for Determining Whether a Verbal Message Was Spoken During a Transaction at a Point-Of-Sale Terminal" and filed August 17, 1998. The entire contents of these applications are incorporated herein by reference.
FIELD The present invention relates generally to point-of-sale terminals, and is more specifically concerned with dissemination of promotional information among networked point-of-sale terminals.
BACKGROUND Point-of-sale ("POS") terminals, such as cash registers, are used in a wide variety of businesses for performing such processes as calculating a total price of a purchase of goods and/or services, and calculating an amount of change due to a customer. POS terminals also are frequently interfaced to card authorization terminals, such as credit card validation devices, or themselves incorporate the functions of such devices.
Depending on their level of sophistication, POS terminals may also be used to perform other functions, such as inventory management performed by tracking purchases made and adjusting a database of store inventory accordingly. Some POS terminals are arranged to exchange information with other POS terminals and/or central computer systems located at the same store as the terminals or at a remote location.
It has also been proposed to use POS terminals to make sales offers or otherwise to aid in marketing promotions aimed at customers present at the POS terminal. Modern large-scale retail organizations are exceedingly complex. Some organizations include hundreds or even thousands of stores, located throughout the United States, and in some cases in foreign countries as well. In some retail chains, all stores are owned by a single entity. In other chains, and particularly in the restaurant industry, most or all of the outlets may be owned by franchise owners. The amount of data that may be collected and information that may be generated therefrom in a network of POS terminals in a large retail organization is immense and may encompass hundreds of thousands or millions of transactions per day. In systems that have been disclosed to date only a small amount of the information generated by POS terminals is captured and used; typically, only aggregate sales and product mix results are tabulated and the analysis of such figures is generally carried out by hand. Moreover, information is not automatically communicated between POS terminals, and only modest attempts have been made to harness the computing power that potentially might be tapped in an extensive POS system. Still further, only modest proposals have been made for employing network POS terminals in promotional activities.
SUMMARY To alleviate problems inherent in the prior art, the present invention introduces systems and methods for the propagation of information in a network of POS terminals. According to one embodiment, performance data relating to a transaction at a first POS terminal is identified. Based on the performance data, transaction information is transmitted to at least one additional POS terminal.
In accordance with one embodiment of the present invention, a method of communicating information in a network of POS terminals includes the following: a) receiving, generating, collecting or otherwise identifying performance data relating to an offer at a first POS terminal; b) determining if the performance data meets at least one criterion, such as a predetermined criterion indicating if the offer was successful; and c) automatically transmitting to at least one additional POS terminal, or otherwise making available to the additional POS terminal, data indicative of an offer which may be the same as the offer made at the first POS terminal or otherwise based on that offer.
The step c) referred to above may include transmitting offer rules or message content related to the offer to the additional POS terminal, or may encompass sending a pointer or other indication to direct the additional POS terminal to implement an offer for which data has already been stored in the terminal. The selection of the additional POS terminal may be based on a predetermined list of other terminals to which an offer is to be propagated if success is achieved with the offer made at the first POS terminal. Alternatively, the selection of the additional POS terminal may be based on some relationship between the first POS terminal and the additional POS terminal. For example, propagation of the offer made at the first terminal or a similar offer may be made to other terminals at locations that are near the location of the first POS terminal. As another alternative, a rule for selecting the additional POS terminal may call for selecting terminals having a customer base similar in demographic characteristics to that of the first POS terminal. A rule for selecting the additional POS terminal may also be based on a similarity with a cashier operating the POS terminal or the physical location of the POS terminal (e.g., whether the POS terminal is located in a mall or on a busy street). According to another embodiment, data indicative of an offer may be transmitted to all POS terminals. Note that when a POS terminal receives such data, the POS terminal may evaluate the data before using it to determine an offer (e.g., by comparing a performance criteria associated with the received data to a performance parameter associated with a stored offer).
The steps listed above may be performed, for example, by one or more of the first POS terminals referred to above, one or more other POS terminals, and/or a server computer which is connected to the network of POS terminals.
In a system and method provided in accordance with the invention, successful offer programs may be permitted to propagate throughout a network of POS terminals, while unsuccessful offer programs are suppressed after testing. The propagation of successful programs may be made under the control of a central authority by means of a server computer or master POS terminal. On the other hand, the decision-making required for propagation of offers may be carried out in a decentralized manner, based on rules applied at many individual POS terminals. The aggregate processing capacity of a complex POS network may be utilized to achieve successful outcomes, and a dynamically responsive distribution of offer programs, which would be difficult to achieve through central planning and/or human intervention. One embodiment of the present invention that may be used to communicate information in a network of POS terminals comprises: means for identifying performance data relating to a transaction at a first POS terminal; and means for transmitting transaction information to at least one additional POS terminal based on the performance data. Another embodiment comprises: means for identifying performance data relating to an offer made at a first POS terminal; means for determining if the performance data meets at least one predetermined criterion; means for automatically selecting at least one additional POS terminal in said network based at least in part on a result of the determining step; and means for automatically making available to said selected at least one additional POS terminal an indication of an offer based on the offer made at the first POS terminal.
BRIEF DESCRIPTION OF THE DRAWINGS
Fig.l is a block diagram, which shows a POS network in which the present invention may be applied.
Fig. 2 is a schematic block diagram of a central server shown in Fig. 1.
Fig. 3 is a schematic block diagram of a typical one of the POS terminals shown in Fig. 1.
Fig. 4 is a tabular representation of a promotion rules database which may be stored in accordance with the invention in one or more of the central server and/or the POS terminals.
Fig. 5 is a tabular representation of a database generated in accordance with the invention and indicative of the performance of a number of offer programs. Fig. 6 is a tabular representation of a propagation rules database which may be stored in accordance with the invention in the central server and/or in one or more of the POS terminals of Fig.l.
Fig. 7 is a tabular representation of a store database that may be stored in accordance with the invention in the central server and/or in one or more of the POS terminals.
Fig. 8 is a flow chart, which illustrates a process carried out in accordance with the invention for propagating successful offer programs.
Fig. 9 is a tabular representation of an offer database according to one embodiment of the present invention.
Fig. 10 is a flow chart, which illustrates a method according to one embodiment of the present invention.
Fig. 11 is a tabular representation of calculations made on the basis of product characteristics and weighting factor data associated with a dynamically-priced upsell offer program.
Figs. 12A and 12B together form a flow chart, which illustrates a process for carrying out the dynamically-priced upsell offer program.
Fig. 13 is a flow chart, which illustrates a process for propagating a successful configuration of the dynamically-priced upsell offer program.
DETAILED DESCRIPTION
Definitions
The terms listed below shall be interpreted according to the following definitions in connection with this specification and the appended claims. POS terminal - a cash register or other device (e.g., a personal computer, a portable computer, or a wired or wireless telephone) used in association with a purchase transaction and having some computing capabilities and/or being in communication with a device having computing capabilities; also includes vending machines and card authorization terminals such as credit card validation terminals. A POS terminal may also be, for example, a portable computing device such as a Personal Digital Assistant (PDA), a communication device such as a wireless telephone, or any other device or devices (e.g., a customer's personal computer in communication with a Web-based server) used in association with a purchase transaction. Offer - an offer, promotion, proposal or advertising message communicated to a customer at a POS terminal; includes upsell offers (such as dynamically-priced upsell offers), suggestive sell offers, switch-and-save offers, conditional subsidy offers, coupon offers, rebates, and discounts.
Upsell Offer - a proposal to a customer that he or she add an additional product or service to a transaction.
Dynamically-priced upsell offer - an upsell offer in which the price to be charged for the additional product depends on a round-up amount associated with the transaction. For example, the round-up amount may be the difference between the transaction total (the amount the customer is required to pay without an upsell) and the next highest dollar amount greater than the transaction total. According to this example, if the transaction total without the upsell is $4.25, then the round-up amount is $0.75 ($5.00-$425 = $0.75). In general, the round-up amount may also be based on the difference between a value associated with the transaction total and any other transaction total. For example, if the transaction total without the upsell is $87.50, the round-up amount may be $ 11.50, resulting in a new transaction total of $99.00. Other information, such as an amount of sales tax associated with the transaction, may also be used to determine the round-up amount.
Suggestive sell offer - an upsell offer in which the price to be paid for the additional item is a list or standard price.
Switch-and-save offer - a proposal to a customer that another product be substituted for a product already included in a transaction, typically the substitute product is discounted from its standard price.
Cross-subsidy offer (also referred to as a "conditional subsidy offer") - an offer to provide a benefit (e.g., to subsidize a purchase price) from a third-party merchant in exchange for the performance of a task by the customer (e.g., applying for or subscribing to a service offered by the third-party, receiving information such as an advertisement, or providing information such as answers to survey questions).
Base product(s - a product or group of products which, when included in a transaction, may trigger, for example, an upsell offer, a switch-and-save offer, or a cross-subsidy offer.
Propagation (also referred to as "spreading") - transmitting an offer, or information associated with an offer, to additional POS terminals through a POS network after evaluating performance of an offer at a first POS terminal or group of POS terminals in a network.
Weighting factors (also referred to as "weights" and "weighting configurations") - multipliers used by a POS system to determine which of several offers to make to a customer in a given transaction. Note that weighting factors may be applied to offers and/or to rules used to generate offers. In addition to weighting factors, any genetic algorithm may be used to determine an offer and/or to propagate information in a network.
Performance data - digitally stored information which indicates results or effects of an offer and/or circumstances in which the offer was made. Identifying performance data - includes generating, receiving, collecting, analyzing and categorizing performance data.
Target POS terminal - an additional POS terminal in which an offer may be implemented after the offer or a similar offer has been evaluated in a first POS terminal or group of terminals. Performance characteristic of a target POS terminal - includes any information associated with a target POS terminal. For example, performance characteristics may include one or more of (a) volume of sales in a predetermined period transacted through the target POS terminal or a store in which the target POS terminal is located; (b) profitability of sales in a predetermined period transacted through the target POS terminal or a store in which the target POS terminal is located; (c) number of transactions in a predetermined period; (d) average number of items purchased per transaction in a predetermined period; (e) demographic information associated with customers who make purchases at the target POS terminal; (f) demographic information associated with an employee operating the target POS terminal; and (g) information associated with the store at which the POS terminal is located (e.g., the size of the store, the address of the store, whether the store is located in a mall). Several embodiments of the invention will now be described with reference to the drawings.
System Overview Fig. 1 illustrates, in the form of a block diagram, a simplified view of a POS network in which the present invention may be applied.
In Fig. 1, reference numeral 20 generally refers to the POS network. The network 20 is seen to mclude a plurality of POS terminals 22, of which only three are explicitly shown in Fig. 1. It should be understood that the number of POS terminals in the network may be as few as two, or, in a more realistic application of the invention, may number in the hundreds or thousands. The POS terminals 22 in the POS network 20 may, but need not, all be constituted by identical hardware devices. Any standard type of POS terminal hardware may be employed, provided that it is suitable for programming in accordance with the teachings of this invention. The terminals 22 may, for example, be "intelligent" devices of the types which incorporate a general purpose microprocessor. Alternatively, some or all of the POS terminals 22 may be "dumb" terminals, which are substantially controlled by a separate computer which is either in the same store with the terminal or located remotely therefrom. Although not indicated in Fig.l, two or more of the POS terminals 22 may be co-located in the same store. Indeed, it can be expected that a typical network of the type in which the invention is applied may include numerous store locations each of which has a small or large number of POS terminals 22 installed therein. In one particularly appropriate network for application of the invention, the POS terminals 22 may be of the type utilized at restaurants; in this case, it can be expected that the POS terminals 22 number in the thousands, with a relatively small number of terminals, say three to six, installed in each of hundreds or thousands of different restaurant locations. According to one embodiment, POS terminals 22 in a store communicate with a store controller device (not shown in Fig. 1), which in turn communicates with the central server 24. Note that all elements shown in FIG. 1 may also be located in a single store. Central server computer 24 is connected for data communication with the POS terminals 22 via a communication network 26. The central server 24 may be constituted by conventional computer hardware, programmed in accordance with the invention. The data communication network 26 may also interconnect the POS terminals 22 for communication with each other. The network 26 may be constituted by any combination of conventional data communication channels, including terrestrial lines, radio waves, infrared, satellite data links, microwave links and the Internet.
Fig. 2 is a simplified block diagram showing some details of the central server computer 24. The server 24 may be embodied as an RS 6000 server, manufactured by IBM Corporation, as programmed to execute functions and operations of the present invention. The server 24 includes known hardware components such as a processor 28 which is connected for data communication with each of a data storage device 30, one or more input devices 32 and a communication port 34. The communication port 34 may connect the server 24 to each of the POS terminals 22, thereby permitting the server 24 to communicate with the POS terminals. The communications port 34 may include multiple communications for simultaneous connections.
As seen from Fig. 2, the data storage device 30 of the server 24, which may be a conventional hard disk drive, stores a program 36. This program is, at least in part, provided in accordance with the invention and controls the processor 28 to carry out functions which will be described below. The program 36 may also include other program elements, such as an operating system and "device drivers" for allowing the processor 28 to interface with peripheral devices such as the input devices 32 and the communication port 34. Appropriate device drivers and other necessary program elements are known to those skilled in the art, and need not be described in detail herein. The storage device 30 may also store application programs and data that are not related to the functions described herein. Also stored in the data storage device 30 are a propagation rules database 38 and a store database 40, both of which will also be described hereinafter. Note that not all embodiments of the present invention require a central server 24. That is, methods of the present invention may be performed by the POS terminals 22 themselves in a distributed, de-centralized manner.
Fig. 3 illustrates in the form of a simplified block diagram a typical one of the POS terminals 22. The POS terminal 22 includes a processor 50 which may be a conventional microprocessor. The processor 50 is in communication with a data storage device 52 which may be constituted by one or more of semiconductor memory, a hard disk drive, or other conventional types of computer memory. The processor 50 and the storage device 52 may each be (i) located entirely within a single electronic device such as a cash register/terminal or other computing device; (ii) connected to each other by a remote communication medium such as a serial port, cable, telephone line or radio frequency transceiver or (iii) a combination thereof. For example, the POS terminal 22 may include one or more computers or processors that are connected to a remote server computer for maintaining databases.
Also operatively connected to the processor 50 are one or more input devices 54 which may include, for example, the key pad for transmitting input signals such as signals indicative of a purchase, to the processor 50. The input devices 54 may also include an optical bar code scanner for reading bar codes and transmitting signals indicative of the bar codes to the processor 50. Another type of input device 54 that may be included in the POS terminal 22 is a touch screen.
The POS terminal 22 further includes one or more output devices 56. The output devices 56 may include, for example, a printer for generating sales receipts, coupons and the like under the control of processor 50. The output devices 56 may also include a character or full screen display for providing text and/or other messages to customers and to the operator of the POS terminal. The output devices 56 are in communication with, and are controlled by, the processor 50. Also in communication with the processor 50 is a communication port 58 through which the POS terminal 22 communicates with other components of the POS network 20, including the central server 24 and other POS terminals 22.
As seen from Fig. 3, the storage device 52 stores a program 60. The program 60 is provided at least in part in accordance with the invention and controls the processor 50 to carry out functions in accordance with the teachings of the invention. The program 60 may also include other program elements, such as an operating system and "device drivers" for allowing the processor 50 to interface with peripheral devices such as the input devices 54, the output devices 56 and the communication port 58. Appropriate device drivers and other necessary program elements are known to those skilled in the art, and need not be described in detail herein. The storage device 52 may also store one or more application programs for carrying out conventional functions of POS terminal 22. Other programs and data not related to the functions described herein may also be stored in storage device 52. Also stored in the storage device 52 are a promotion rules database 62, a promotion performance database 64, and a dynamically- priced upsell database 220. The functions and constitutions of these databases will be described below.
Data Structures According to the Invention Fig. 4 is a tabular representation of the promotion rules database 62 referred to in connection with Fig. 3. Note that the rules database 62, as well as the other databases described herein, may include the information shown in the associated Fig. or a pointer indicating the information. The table of Fig. 4 includes columns 120 and 122 which have the same content as columns 80 and 82 shown in Fig. 6. Column 124 in Fig. 4 includes data which is indicative of messages to be conveyed to customers for the purpose of making the offers. Column 126 contains information indicative of rules for determining circumstances in which the offers are to be made.
The promotion offer content 124 contains information related to the offer as it is presented to the customer. For example, this field may contain the text of a prompt a cashier is directed to read to a customer, the prompt including a placeholder that may be filled in based on the product being offered. Instead of including a prompt, the field may comprise text or image information (e.g., video information) to be displayed on a screen, or audio information to be played for the customer. Note that, according to an embodiment of the present invention, an offer may include an offer to purchase more than one additional item (e.g., "would you like to add a soda or desert to your order?") or no item at all (e.g., "would you like to donate your $0.37 change to charity?").
Turning to the promotion rules information listed in column 126, and particularly the promotion rules governing the dynamically-priced upsell offer referred to in the first entry of the table, it will be observed that a somewhat complex set of rules is set forth. In particular, the upsell offer is not to be made unless a customer has purchased a sandwich and the total transaction and amount tendered call for change to be returned to the customer in an amount of at least one cent and no more than 33 cents. Other factors may be taken into account in addition to or instead of those just described, including the total amount of the transaction, the quantity of inventory on hand and/or its age, and/or whether certain items are about to be discarded. Further rules may take into account additional factors relating to the mix of products included in the transaction. The further rules may be employed to determine which product or products should be included in the upsell offer.
For the suggestive sell offer, the entry in column 126 prescribes a simple rule in which the offer is to be made whenever a customer purchases a sandwich and has not purchased fries. Again, other or additional rules may be applied to a suggestive sell, which may be related to factors such as the identity of the customer, the time of day, whether or not the store is busy, and so forth.
In regard to the cross-subsidy offer listed in Fig. 4, the promotion rules require that the customer is not already subscribed to the service provided by the third-party merchant, and that an offer of a cross-subsidy from the merchant not previously have been made to the customer. It will be appreciated that in order to determine whether a customer qualifies under these promotion rules, the customer must be identified, and a database which includes the information needed to determine qualification must be available and must be accessed.
In connection with the switch-and-save offer, the promotion rules prescribe that the product to be substituted for must have been included in the transaction and the potential substitute product must be within 7 minutes of being discarded. Variations upon or substitutions for all of these rules could be contemplated. For example, a minimum purchase total may be required as a qualification in the case of any of these offers, or, alternatively, if the purchase total is greater than a given amount, then the transaction may be considered to be disqualified from applying an offer. The rules governing the upsell offer may include imminent expiration of a potentially upsold product. The rules governing the switch and save offer need not have anything to do with imminent expiration of the potential substitute product.
As will be understood from the discussion of Fig. 6, other types of offers may be included in the promotion rules database 62, including dispensing coupons or providing discounts to the customer or providing promotional messages visually and/or audibly to the customer. In the case of coupon offers, possible promotion rules include requiring that the transaction exceed a certain amount or that one or more particular products be included in the transaction. As used herein, a "coupon" may include any indication (e.g., a voucher or a code). Fig. 5 is a tabular representation of an example of a promotion performance database 64, previously referred to in connection with Fig. 3. The purpose of this database is to store data indicative of the effectiveness of the offer made at the POS terminal 22 in which the performance database 64 is stored. The performance database 64 includes four columns: 140, 142, 144 and 146. Column 140 lists the offers for which the performance data is stored, by identification code number. Column 142 stores data which indicates what percentage of the time each of the offers was accepted. Column 144 stores data which indicates the total amount of the purchase, on average, for the transactions in which the respective offers were made and accepted. As will be explained with respect to Fig. 6 and of criteria for determining whether an offer is acceptable, it will be understood that the data of columns 140 and 142 and 144, taken alone or in combination, may be used to determine whether the respective promotions are considered successful (e.g., whether the promotions increased number of items being sold, increased an average total transaction amount, and/or increased an amount of profit earned by a merchant).
Column 146 lists data indicative of circumstances under which the offers were successful, particularly the time of day when the offers were popular. As will be seen, data of this type, including other data indicative of circumstances in which the offers were accepted or were not accepted, may be used to determine targets for propagating the offers, as well as modifications that may be made in the offer as propagated.
Fig. 6 represents in tabular form the propagation rules database 38 referred to in connection with Fig. 2. The table of Fig. 6 includes columns 80, 82, 84 and 86 which respectively include a code for identifying an offer or promotion, a brief description of the type of the offer, one or more criteria for determining whether the offer was successful, and rules for propagating the offer in the network of POS terminals if the offer was found to be successful.
The first entry in Fig. 6 carries the offer identifying code "01" and is concerned with a dynamically-priced upsell offer. A dynamically-priced upsell offer is a type of promotion in which an operator of a POS terminal offers to sell to a customer an additional product in exchange for a round-up amount that may be, for example, the amount of change which was calculated as being due to the customer at the end of the transaction. Details of an example of a dynamically-priced upsell offer will be described below. For present purposes it is sufficient to note that the product or products to be suggested for an upsell may depend on such factors as which products have already been included in the transaction, and the value of the round-up amount.
In the entry in column 84 with regard to the dynamically-priced upsell offer, the criteria for determining whether the offer was successful are stated as "no dilution" and "increase in demand for upsell products". The first criterion, "no dilution", means that the quantity of sales made of the upsold product at full price are not decreased significantly (e.g., unprofitably) during the period when the upsell offer is in effect, as compared to a comparable period. The second criterion indicates that the overall demand for the upsold products must significantly increase during the period of the offer. Note that the criteria associated with the success of an offer may not be the same for every offer. For example, different upsell offers may have different criteria for success. Moreover, an offer does not need to be categorized as either "successful" or "unsuccessful," but instead may be rated based on a range of effectiveness. For example, information associated with a highly successful offer may be propagated to twenty additional POS terminals 22 while information associated with a moderately successful offer may only be propagated to three additional POS terminals 22.
The entry for the upsell offer in column 86 sets forth a rule for propagating the offer to additional POS terminals if the offer is found to be successful at a first POS terminal. In particular, with regard to this upsell offer, the rule prescribes that the offer is to be propagated to the three nearest POS terminals relative to the first POS terminal. The location of the three nearest terminals is to be determined by reference to zip codes which identify the locations of other POS terminals.
The second entry in the table of Fig. 6 has the identifying code "02" and is concerned with a suggestive sell offer. In this type of offer, the operator of a POS terminal simply suggests to the customer at the end of the transaction or at some other point in the transaction that the customer purchase an additional product. Alternatively, the suggestive sell message may be delivered by a screen display and/or a speaker which is part of or connected to the POS terminal. The entry in column 84 for this offer indicates that the offer is to be considered successful if it is accepted more than 30% of the time. The entry in column 86 specifies, by an Internet Protocol (IP) address, two particular POS terminals to which the suggestive sell offer is to be propagated if it is found to be successful at a first POS terminal. The information in column 86 further specifies by IP address three other POS terminal locations to which the suggested sell offer is to be propagated if found to be successful at the group of POS terminals to which it was propagated after the initial successful test. It should be understood that the POS terminals specified to receive the offer may be specified by data other than an IP address. Such data may be, for example, an identifying code for the target POS terminals. Whether in the form of an identifying code, an IP address, or in some other format, data which specifically identifies a particular target POS terminal may be referred to as a "target identifier".
The third entry in the table of Fig. 6 has an identifying code "03" and is concerned with a cross-subsidy offer. In this type of offer, the customer is advised that some or all of the cost of the transaction will be paid for by a third party merchant if the customer agrees to enter into a transaction or otherwise do business with the third party merchant. One system for providing such a benefit is disclosed in U.S. Patent Application Serial No. 09/282,747 entitled "Method and Apparatus for Providing Cross-Benefits Based on a Customer Activity" and filed March 31, 1999. As an example, a customer at a restaurant may be told that his or her meal is free if he or she agrees to transfer his or her long distance service to a telecommunications company subsidizing the offer.
The entry in column 84 for the cross-subsidy offer indicates that the offer is to be deemed successful if it is accepted more than 15% of the time. The entry in column 86 for this offer indicates that it is to be propagated to POS terminals in other stores which have a customer base which is similar in its demographic characteristics to the store at which the offer was found to be successful. Ways in which other stores may be determined to have similar demographic characteristics relative to a first store will be described below. The last entry shown in the table of Fig. 6 has an offer identification code "04" and is concerned with a "switch-and-save" offer. In an offer of this type, the operator of the POS terminal suggests to the customer that he or she substitute, for a product that has been ordered, another similar product, normally sold at a higher price, but at a reduced price which may be the same as that of the product to be substituted for. An example of a switch and save offer might be, "How about a cheeseburger instead of that hamburger, for the same price?"
In the entry in column 84 for this offer, it is indicated that the offer will be deemed successful if it results in a savings in the store's purchasing budget of more than 5%. According to one embodiment, whether an offer will be deemed successful may be based on whether sales of a promotional item increases by a predetermined amount (e.g., a predetermined amount associated with a local advertising campaign). The rule for propagating the offer, as stated in column 86, is to spread the offer to other stores having a customer base with a demographic characteristic similar to that of customers who were found to accept the offer at stores where the offer was successful. It will be understood that, to implement a propagation rule of this type, it is necessary to collect information indicative of characteristics of customers who engage in transactions at the first POS terminal or group of POS terminals where the offer is being made. Collection of customer characteristics may be accomplished in accordance with conventional practices by identifying customers who shop at the store where the offer is being made, collecting information about the customers, issuing bar coded or magnetic stripe cards, smart cards or the like to customers to identify the customers, and then reading the customer identification cards at the time of transactions with the customers. Note that customers may identify themselves via a frequent shopper card, a payment card (e.g., a credit card), a customer identifier (e.g., entered by the customer at a POS terminal), or any other method.
The simplified example of the propagation rules database 38 shown in Fig. 6 only lists four offer programs; however, a smaller or larger, number of offer programs may be stored in the propagation rules database 38. Moreover, although only one type each of a dynamically-priced upsell offer, a suggestive sell offer, a cross-subsidy offer and a switch-and-save offer are listed in Fig. 6, it is contemplated to include in the database two or more varieties of some or all of these types of offers, instead of a database storing predetermined offers, a POS terminal may store information associated with a process used to determine an offer. This may be accomplished via rules, a genetic algorithm, a neural network, and/or other programming techniques.
It is also contemplated to include entries corresponding to other types of offers, including (a) rebates, (b) simple discounts on selected products, and (c) coupons to be issued in all transactions, or depending on characteristics of the transaction such as types and/or number of products ordered, time of day, characteristics of the customer and so forth, as well as a combination of such factors. Other types of marketing activities may also be assigned propagation rules and stored in the database 38, including programs for selectively delivering various types of promotional messages via displays and/or speakers associated with POS terminals. Offers may be displayed on POS terminals and/or Web sites (e.g. as banner advertisements displayed while customer access a Web site or adjust the contents of a virtual shopping cart).
The propagation rules database may include other types of data in addition to those illustrated in Fig. 6. For example, there may be identified for each offer the POS terminal or terminals at which the offer is currently being evaluated or is to be evaluated in the future. The database may also indicate a time period during which the evaluation is being carried out for each relevant POS terminal or terminals. The time period could be specified in terms of a starting date and time and an ending date and time.
The present invention also contemplates types of criteria for determining success in addition to those indicated in Fig. 6. For example, an offer may be deemed successful if it increases revenue, either on a per transaction basis and/or on an aggregate basis, for either or both of the POS terminal at which the offer is being made or at the store location. The criteria may also be targeted so as to be based on an increase in revenue for a particular portion of the selling day, week or month; e.g., an increase in revenue at lunch or on weekends. Another criterion for determining success may be based on an increase in profit in addition to or instead of an increase in revenue. Other criteria that may be considered to indicate success would be an increase in the number of customer visits and/or the number of transactions and/or the number of items purchased in each transaction. Still another criterion that might be employed would be a reduction in the level of inventory. Other possible criteria for determining success, particularly in the case of an offer which is maintained over a period of time, may be a decrease in labor costs required to produce products sold in connection with the offer or in staffing the POS terminal or terminals at which the offer is made, an increase in the rate at which inventory turns over at the store at which the POS terminal or terminals are located, a reduction in the amount of waste or the average quantity of items of inventory in the store, or an increase in customer retention rates for the store and/or frequency of customer visits at the store. Other criteria for success may include the amount of time required to handle transactions, on average, at the POS terminal or terminals at which the offer is made; the average amount of time that customers wait for service at the POS terminal or terminals; and/or the amount of time required to produce products referred to in the offer. It is also contemplated to use, as a criterion of success, combinations of and/or trends in the factors which have been enumerated above. There may be other useful criteria of success not listed above that fall within the scope of the present invention.
Fig. 7 is a tabular representation of the store database 40, previously referred to in connection with Fig. 2. The table of Fig. 7 includes a column 100 which identifies store locations, columns 102, 104 and 106, which list demographic characteristics of the customer bases for the respective stores, column 108 which indicates the average dollar amount per transaction at the stores, and column 109 which indicates the IP address or address of POS terminals associated with each store. The particular demographic data in columns 102, 104 and 106 respectively is average customer age, average per capita income for the customers, and percentage of customers who are male. The data in columns 102, 104 and 106 may be gathered by surveys or other conventional means, and the data in column 108 can be gathered by conventional techniques for keeping track of store operations. If available, the system may use individual customer history and select those offers that are more likely to be accepted based on the customer's proclivity to accept certain types of offers under certain conditions (e.g., order content, time of day, location, and/or change amount due). Other information that may be stored in the store database 40 may be associated with, for example, a destination of an order (e.g., eat-in, take-out, or drive-through), a total number and/or a frequency of customer visits, an average check-out amount, a contribution margin, and/or c rent product advertising information. In addition to storing information associated with particular stores, information associated with particular customers may be used by the POS network 20 to determine an offer and/or to propagate information.
Although entries for only three stores are shown in Fig. 7, it is to be understood that, in practice, data for a much larger number of stores may be maintained in the store database 40. It is also contemplated to include many additional types of data in addition to that shown in Fig. 7. Other types of information that may be included in the store database include the size of the store, proximity to other stores of the chain and/or competitors' stores, types of facilities at the store, including capabilities for producing and/or selling certain types of product, whether the store has drive-through selling capabilities, and whether the store has been recently remodeled.
Many other aspects of the sales history of the store may be provided in addition to or instead of the average transaction amount. Among the types of data may be total revenue, total profitability, various types of revenue or profitability figures broken down by time of day, month, week and/or year, number of transactions per day, number of items per transaction. Other store performance indicators such as labor and inventory costs, inventory level and inventory turns may also be included.
In addition to or instead of the demographic information presented in Fig. 7, additional characteristics of the customer base may be included, such as distribution of customers among various age categories, which may also be broken down by gender. Additional information could include marital status, number of children, home ownership versus renting, type of car owned, shopping habits and any of the other numerous ways in which customer populations are segmented for marketing analysis. The terminal addresses 109 may be used, for example, by other POS terminals 22 when transmitting transaction information (e.g., a modified offer rule) through the POS network 20. According to one embodiment, transaction information may instead be broadcast to every POS terminal 22 in the POS network 20. In this case, the transaction information may include information associated with an offer's past success (e.g., how successful and in what environments). When transaction information is received at a target POS terminal, the target POS terminal 22 may compare the success information and information associated with the target POS terminal 22 to determine if an order should be modified. According to another embodiment, each target POS terminal 22 may simply use the received information without an evaluation. In another embodiment, the individual stores may receive the information and may apply some, all, or modified portions of the information based on its own history. For example, offers may be received by a store that contains pricing information that does not apply to the particular store. In this case, the system would receive and apply some of the information (e.g., the rules or weights) without applying the conflicting information (e.g., the price). General Description of Evaluation and Propagation of Offers Fig. 8 is a flowchart which illustrates a process by which the central server 24 may determine whether to propagate an offer that has been made at a first POS terminal to other POS terminals in the POS network 20. It will be understood that the process shown in Fig. 8 may be a feature of the program 36, previously refened to in Fig. 2. Referring to Fig. 8, a first step 160 represents the central server receiving offer performance data from a POS terminal at which an offer has been evaluated. The performance data may be transmitted from the POS terminal to the central server in response to a query from the central server. Alternatively, the POS terminal may transmit the performance data at its own instigation, say at the end of a predetermined period during which the evaluation of the offer was to occur. The performance data may include all of the data for the given promotion as listed in the performance database 64 in the POS terminal, or may only be selected data (e.g., the rules, weights, and script text) requested by the central server after consulting the data in column 84 of the propagation rules database 38 (Figs. 2 and 6) to ascertain what information is needed to determine success of the offer.
Step 160 may include receiving performance data from one POS terminal, or from more than one POS terminal, either all located at the same store, or located at different stores. It is contemplated to determine the success of an offer based on performance data from as few as one POS terminal or from as many as thousands of POS terminals. Data may be applied in its entirety and/or only partially (e.g., using rules or filters) to "adjust" the information prior to applying the information to the receiving store's database. Step 162 represents the central server retrieving, from the propagation rules database 38, criteria for determining success of the offer. It will be appreciated that step 162 may occur either before or after step 160.
Decision block 164 represents a determination as to whether the offer was successful. This determination is made on the basis of the performance data received at step 160 and the success determination criteria retrieved at step 162. If it is determined at step 164 that the promotion was unsuccessful, the process of Fig. 8 may simply terminate, as indicated at 166. According to another embodiment, instead of determining whether an offer was successful, the central server 24 may determine to what extent the offer was successful. Alternatively, the central server may be programmed to modify the offer in one or more respects and to instruct the POS terminal or terminals to reevaluate the offer as modified. As another alternative, the central server may be programmed to propagate the offer to POS terminals which are found to be dissimilar in one or more respects from the POS terminal or terminals at which the offer was unsuccessful. Thus, it will be understood that propagation of an offer may occur in some circumstances even though the offer is not successful, or to be more precise, does not satisfy a success criterion. According to one embodiment, the central server 24 may instead propagate information to POS terminals 22 such that certain offers will not be provided (i.e., suppressing certain offers). If at block 164 it was determined that the offer was successful, then at step 168 the central server (or more specifically, processor 28) retrieves from the data storage device 30 the propagation rule listed, for the offer found to be successful, in column 86 (Fig. 6) of the propagation rules database 38. On the basis of the retrieved rule, the central server identifies an additional POS terminal or terminals to which the offer is to be propagated (step 170). Step 170 may be trivial if the propagation rule itself explicitly specifies particular POS terminals, or store locations, to which the offer is to be propagated. In cases where, as in the first entry of column 86 in Fig. 6, the target POS terminals are indicated by a rule of geographic proximity to the first POS terminal, then the central server accesses a database which stores geographic information as to the location of POS terminals. The central server then processes this data by comparing it with the location of the first POS terminal to select the target POS terminals. In cases where the target POS terminals are to be selected based on demographic characteristics (as in the last two entries in column 86 in Fig. 6), the central server accesses a database of demographic information concerning terminals or store locations in the POS network.
Similarity of a potential target POS terminal to a first POS terminal may be determined in a number of ways. For example, where the customer bases of two locations have median incomes that differ by no more than $3,000, the customer bases may be considered to be similar. In addition or alternatively, the customer bases may be required to have an average age that does not differ by more than 5 years. The same or other demographic characteristics of customer populations (including populations which were found to accept the offer at the first POS terminal) may be analyzed to detect which populations have characteristics that fall within a standard deviation of each other. Those of ordinary skill in the art will recognize other ways in which customer bases may be determined to be similar to each other. It will also be recognized from the foregoing how customer bases may be found to be dissimilar from each other. Target POS terminals may also be selected on the basis of being in stores of the same size, having the same or similar facilities and/or an equal degree of proximity to or distance from competitors' stores as the store(s) in which the offer was evaluated. It is also contemplated that step 170 may include selecting one or more target POS terminals on the basis of performance data which indicates circumstances in which the offer was successful. For example, if an offer was found to be successful only during a certam time of day, such as a breakfast period, step 170 may include identifying target locations which do a relatively large proportion of their business during breakfast. It will be appreciated that a suitable propagation rule governing this type of selection process would be stored in column 126 (Fig. 4) for the offer in question.
Once the target POS terminal or terminals have been selected in accordance with the applicable propagation rule, the central server performs step 172, in which it transmits to the additional or target POS terminals the relevant offer, content and rule information, such as that discussed in connection with Fig. 4. Alternatively, and assuming that such information had previously been stored in the target POS terminals, the central server may transmit to the target POS terminals a trigger message or pointer which causes the target POS terminals to begin to make offers like the offer determined to be successful at step 164. It is also contemplated that the central server may instruct another computer or one of the POS terminals to transmit the offer information or a trigger message to the target POS terminals. If and when the offer is found to be successful at the target POS terminals, steps of Fig. 8 may be repeated so that the offer is propagated to still other POS terminals of the POS network 20.
According to another manner in which step 170 may be performed, the number and/or some other characteristics of target POS terminals may be determined based on how successful other offers proved to be after having been tested at and propagated from the first POS terminal. For example, a number of offers propagated from a first POS terminal may have proved to be very successful at a second POS terminal, while no similarities in customer base, transaction history, etc. between the two POS terminals were identified. In this case, the first POS terminal may continue to propagate offers to the second POS terminal based solely on the past success of the propagated offers.
The present invention also contemplates basing selection of target POS terminals on a combination of demographic and geographic factors. It is known to categorize zip codes according to socio-economic characteristics of people who live in the zip codes. This categorization of zip codes can be used to formulate a propagation rule like this: "Spread the offer to POS terminals located in zip codes which are in the same category as the zip code of the POS terminal in which the offer was successful." Other rule variables may include, for example, traffic patterns and/or demographics of the customers, weather patterns, and competitive analysis (e.g., offers being made by other merchants in a particular area).
It is also contemplated by this invention to select target POS terminals based on one or more characteristics of the operators of the POS terminals. For example, a propagation rule may prescribe that a successful offer only be propagated to POS terminals staffed by experienced operators. The experience level or another characteristic of an operator at a POS terminal where an offer is evaluated may also be stored and analyzed as performance data, i.e., a circumstance in which the offer was made. For these purposes, operators may be required to log on to POS terminals, in accordance with conventional practices, and a database may be maintained of information concerning the operators.
Another factor that may be used in selecting target POS terminals is a historical record of transactions at potential target POS terminals. A propagation rule may hold, for instance, that a successful offer only be propagated to POS terminals which have historically done a relatively large amount of business, or to POS terminals which have historically done a relatively small amount of business. This selection of a target POS terminal may be based on performance characteristics of the potential target such as revenue and/or profitability. Target selection may also be based on a characteristic of a mix of products sold at the potential target POS terminal. If a successful offer is not implemented at a potential target POS terminal for some predetermined reason (say the potential target lacks a necessary facility or is already very successful), it may be said that a rejection condition is satisfied at the potential target terminal, and a successful offer is not propagated to a potential target when a rejection condition is determined to be satisfied at the potential target terminal. The determination that a rejection condition is satisfied may be made at the central server, at the potential target POS terminal, or at another POS terminal.
Selection of target POS terminals may also take into account physical or programmed characteristics of potential target terminals. To give examples, an offer which requires a certain type of display screen would only be propagated to POS terminals having such a screen; an offer which requires the implementing POS terminal to be programmed in a certain manner would only be propagated to POS terminals that have been so programmed. According one embodiment, an offer is not be propagated to a POS terminal that has already been programmed with another offer or offers that are incompatible with the offer under consideration. Accordingly, the process of selecting a target POS terminal may include determining whether the offer in question is compatible with other offers being made at the potential target. For example, a POS terminal offering dynamically-priced upsell may not be compatible with a successful suggestive sell offer.
Selection of a target POS terminal may also include determining the cost of implementing the offer at the potential target, and determining whether the store at which the potential target terminal is located has facilities and/or materials required to make the offer and/or to provide a product or service related to the offer. The present invention contemplates that the server may modify an offer, based on performance data, or for other reasons, before propagating the offer, as modified, pursuant to step 172. For example, if the acceptance rate for the offer was much higher at one time of day than at other times, the rules governing the offer may be modified to provide that the offer is to be made at the target POS locations only at the time of day in which the high acceptance rate was found.
Step 160 of Fig. 8 may include receiving performance data with regard to more than one type of offer, whether made at the same POS terminal or group of terminals or at different POS terminals. The performance data may be compared to respective evaluation criteria for the offers, and respective levels of success compared from one offer to another. Accordingly, the determination at 164 may be not simply whether an offer was successful relative to its own criteria, but which of two or more offers are to be deemed more successful or the most successful. The more successful offer or offers may be propagated and the less successful offer or offers suppressed. Alternatively, all offers may be propagated to some extent, but the more successful offers propagated to a larger number of target POS terminals than the less successful offers. As another alternative, least successful offers may be suppressed, moderately successful offers propagated to a relatively small number of target POS terminals, and most successful offers propagated to a larger number of target POS terminals. As still another alternative, unsuccessful offers may be propagated to target POS terminals having dissimilar performance characteristics.
Example - Basic Evaluation And Propagation Of Upsell Offer There will now be described, with reference to Figs. 9-10, a basic example of how an upsell offer may be evaluated and propagated in a network 20 of POS terminals 22 according to an embodiment of the invention.
Fig. 9 is a tabular representation of a database 300 which stores potential upsell offers for a number of products. Such a table may be stored, for example, at a first POS terminal 22. The information stored in the table may be created and updated, for example, by an operator, the central server 24, and/or other POS terminals 22.
The table shown in Fig. 9 includes base products 302 representing an order placed by a customer. For example, a customer may order a "burger" and a "soda" as indicated by the first entry of the table. The table also indicates an offer 304 that should be made to the customer based on the preliminary order. For example, when a customer orders a burger and a soda, the POS terminal 22 will determine that the customer should be offered "fries" in addition to the base products 302. The base products 302 and the offer 304 thus indicate a rule used by the POS terminal 22 to determine an offer. The table also indicates an acceptance rate 306 associated with the rule. For example, 25% of the customers have accepted an offer to purchase fries after they ordered a burger and a soda via the first terminal 22.
Fig. 10 illustrates a method of propagating information in a POS network according to an embodiment of the present invention. The method shown in Fig. 10 may be performed, for example, by the first POS terminal 22 and/or the central server 24.
At 308, transaction information is received. The transaction information may indicate, for example, the base products 302 that a customer wishes to purchase. In general, however, the transaction information may comprise any information associated with the transaction. For example, the transaction information may include one or more of: demographic characteristics of the customer and/or an employee, a time of day, and phrasing of the offer as it was presented to the customer. Note that transaction information may be received, for example, via a POS terminal (e.g., via the input device 54), an operator of a POS terminal 22, and/or a monitoring device (e.g., a microphone coupled to a processor configured to execute a voice recognition process). At 310, an offer is determined. This may comprise, for example, retrieving the offer 304 based on the base products 302. According to one embodiment, the offer is also randomly determined on occasion. For example, POS terminal 22 may disregard the offer 304 once every ten offers and randomly select a different item to be offered to the customer (or one out often POS terminals 22 in a store may always disregard the offer 304). Accordmg to another embodiment, the POS terminal 22 instead instructs an operator of the POS terminal to select a different item. In this case, the operator may indicate which different item he or she selected (e.g., fries or soda) using the input device 54 of the POS terminal 22. At 312 performance data is evaluated. This may comprise, for example, comparing an acceptance rate 306 associated with a predetermined offer 304 with an acceptance rate associated with a randomly determined offer. In general, any performance data associated with transactions may be evaluated, including, for example, one or more of: an amount of profit (e.g., associated with a particular transaction or associated with a store), a level of customer satisfaction, a length of time associated with an average transaction, and a quality of service provided during the transaction (e.g., the accuracy of an answer to a customer's question provided by an operator of the POS terminal 22). Note that an amount of profit associated with a transaction may be based at least in part on a payment received from a third party (e.g. , a payment from a manufacturer to a retailer in exchange for selling an item).
At 314, information is propagated to at least one other POS terminal 22 in the POS network 20. For example, if the acceptance rate associated with a randomly determined offer is greater than an acceptance rate 306 associated with a predetermined offer 304, a POS terminal 22 may instruct one or more other POS terminals to modify the predetermined offer 304. The first transaction terminal 22 may also, of course, decide to modify the predetermined offer 304.
Note that any information associated with transaction may be propagated at 314. For example, a modified rule or a new rule may be transmitted to other POS terminals 22 (e.g. , a modified phrasing of an offer to be provided to a customer, or a new rule indicating that a time of day parameter should be added to an offer generation process). Similarly, performance information may be propagated. In this case, other POS terminals 22 may use the performance information, for example, to determine if a predetermined offer should be modified. Moreover, propagation rules themselves may be propagated. For example, if automatically forwarding information to twenty additional POS terminals 22 after a .5% increase in an acceptance rate 306 has not effectively improved an overall acceptance rate, POS terminals may be instructed to only forward information to three additional POS terminals 22 after a 2% increase in an acceptance rate 306.
Also note that transaction information may be propagated by transmitting some or all of the information to other POS terminals 22. According to another embodiment, some or all of the information may instead be sent to the central server 24. For example, a first POS terminal may send a new transaction rule to the central server 24, and an indication of the success of the new transaction rule to other POS terminals 22. The other POS terminals 22 may then function to determine whether or not retrieve the new transaction rule from the central server 24.
Example - Evaluation And Propagation of Dynamically-Priced Upsell Offer
There will now be described, with reference to Figs. 11-13, a more detailed example of how a dynamically-priced upsell offer may be evaluated and propagated in accordance with the invention.
Fig. 11 is a tabular representation of a dynamically-priced upsell database 220, of the type refeπed to in connection with Fig. 3, which stores potential upsell scores for a number of products. The table shown in Fig. 11 includes a store identifier field 180 which indicates the store in which the offer is being evaluated. A field 222 indicates the base products which, when included in a transaction, trigger consideration of the potential upsell products listed in database 220. The particular set of base products indicated in field 222 in this example consists of a cheeseburger and a cola. However, the set of base products may be indicated more generally (e.g., "a burger and a drink") or more specifically (e.g., "a cheeseburger and a 32 ounce cola").
Columns 226, 228, 230, 232 and 234 of Fig. 11 list the potential upsell products to be considered when the base products listed in field 222 are ordered. Column 223 lists the perishability, popularity and profitability categories of the product. The concept behind tracking the popularity of the product may be that the restaurant chain wishes to promote products that are relatively unpopular, in which case a higher score is accorded to less popular products. Similarly, a restaurant may wish to promote products that are relatively popular (e.g., products associated with an advertising campaign).
According to one embodiment, the propagation of information in the POS network 20 is based on sales mix data (e.g., information associated with individual item popularity). According to another embodiment, the propagation of information in the POS network 20 is based on market basket data (e.g., information associated with particular groups of items and/or the frequency of particular combinations of items).
Column 224 lists weighting factors to be applied, respectively, to the scores for the products associated with each of the categories 223. According to one embodiment of the present invention, the weighting factors 224 may be used as follows to improve the success of dynamically-priced upsell offers. A product upsell is scored based on a number of categories 223, and each score is multiplied by the weighting factor 224 associated with each category 223 to generate a weighted score. A particular product upsell is selected based on the weighted score associated with the product. Thus, by adjusting the scores and/or the weighting factors 224, the upsell product that is selected may be determined. Note that the scores and/or the weighting factors 224 may be determined by an operator and/or be automatically modified based on information received from other POS terminals 22. Figs. 12A and 12B together constitute a flow chart which illustrates a process by which a POS terminal 22 makes a dynamically-priced upsell offer to a customer in accordance with this exemplary embodiment of the invention.
According to a first step 210 in Fig. 12 A, the POS terminal 22 receives one or more signals which indicate the customer's selection of products for a transaction. These products form a set of base products which may trigger consideration of a dynamically-priced upsell offer. The POS terminal then calculates a total amount due for the transaction on the basis of the products selected by the customer. This step is represented by block 212 in Fig. 12 A. Next, as indicated by step 214, the POS terminal retrieves from its storage device 52 the potential upsell score database 66 which corresponds to the set of base products indicated at step 210. The POS terminal then also accesses the weighting factor database 68, as indicated by step 216. Next, in a step represented by block 218, the weighting factors are applied to the potential upsell scores for the various products to generate a set of weighted scores. Table 220 shown in Fig. 11 illustrates the set of weighted scores which results from step 218. Columns 226, 228, 230, 232 and 234 respectively indicate the weighted scores generated for the various products listed in the dynamically-priced upsell database 220 as well as totals of the weighted scores.
The step of arriving at the totals listed as the last items in columns 226, 228, 230, 232 and 234 is indicated by step 236 in Fig. 12A. Next, as indicated at step 238, the POS terminal determines which of the potential upsell products received the highest score and selects that product to be the subject of an upsell offer. In this particular example, the product receiving the highest score is an apple pie; accordingly, an apple pie is the product selected for the upsell offer. Step 238 may also include a process of determining whether the potential upsell product with the highest score is qualified, taking into account the amount of change due to the customer. That is, the upsell offer may be arranged so that certain products will not be offered unless the amount of change due is sufficient to justify offering them. Thus, step 238 may include selecting the product with the highest weighted total score which also is qualified to be offered for the amount of change which is due to the customer. Additionally, the system may randomly (or semi-randomly) select an upsell product from a group of upsell products (e.g., from the three upsell products having the highest weighted total score). At step 240 the POS terminal causes the upsell offer for the selected product to be made to the customer. This may be done by prompting the operator of the POS terminal with a display on the terminal or by displaying the offer directly to the customer. As will be understood from the previous discussion of Fig. 4, the offer may take the form of saying to the customer "How about a (selected product) for your change?" It is then determined at decision block 242 in Fig. 12B, whether the customer has accepted the upsell offer. If not, then the customer is given his change (step 244) and an entry is made in a transaction database to the effect that the offer was declined (step 246). The routine of Figs. 12A and 12B then ends, as indicated at 248. However, if at block 242 it was found that the customer accepted the upsell offer, the customer is provided with the upsell product (step 250) and an entry in made in the transaction database to indicate that the offer was accepted (step 252).
It is to be understood that the procedure of Fig. 12A and 12B may be carried out at the POS terminal 22 each time during the offer evaluation period that the base products are selected and none of the potential upsell products are selected.
Alternatively, if one or more of the potential upsell products are included in the order, the potential upsell product which is not included in the order and has the highest score resulting from steps 214, 216, 218 and 236 is offered to the customer as an upsell product for the customer's change. According to another variation, the particular upsell score database accessed at step 214 depends upon which set of base products the customer selects.
According to one embodiment, the weights shown in Fig. 11 are applied to potential upsell scores to generate weighted scores at the time of each transaction (i.e., after the customer has placed an order). As an alternative, however, the weighted scores of Fig. 11 may be generated ahead of time; for example, the data shown in Fig. 11 may be generated when product scores and weighting factors are first stored in the POS terminal.
Fig. 13 illustrates a process by which the central server 24 collects from a number of different POS terminals respective performance data, and determines on the basis of the performance data which of a number of different weighting configurations evaluated in the various POS terminals resulted in the most successful offers. Then the best weighting configurations are propagated to additional locations.
Step 260 in Fig. 13 indicates that the server computer receives from a first POS terminal (or all of the POS terminals at a first location) information which indicates the POS terminal or terminals providing the information, the weighting configuration employed in making an upsell offer at the POS terminals, and the extent to which an offer was successful. Step 262 represents the central server receiving the same information from one or more additional POS terminals or POS locations. At step 264, the central server determines which of the weighting configurations resulted in the highest success rate for an upsell offer. Following step 264 is step 266, at which the central server selects one or more target POS terminals to which the most successful weighting configuration is to be propagated (e.g., based on information in the propagation rules database 38). For purposes of this example, it is assumed that propagation rules call for propagating the highest rated weighting configuration to similar POS locations. These locations may be selected on the basis of geographic proximity to the most successful evaluating POS location or based on demographic similarity, as has been discussed above. According to another embodiment, locations may be selected based upon similarities in rules and/or weighting criteria among one or more stores (or even the order and weighting of the rules themselves).
In any event, at step 268 the best weighting configuration is transmitted to the selected target POS terminals for use in an upsell offer at those terminals. According to another embodiment, weighting configuration adjustments are transmitted to the selected target POS terminals at step 268 (e.g., "increase the popularity weighting factor by .2"). The procedure then ends as indicated at 270.
According to particular examples disclosed up to this point, the propagation rules database 38 and the store database 40 are stored in a central server computer, which also performs the evaluation and propagation functions described in Fig. 8 and 13. However, it is also contemplated to store those databases and perform those functions in one or more of the POS terminals 22. For example, the generation of the performance data as well as the evaluation of that data in comparison with success determination criteria and the selection of target POS terminals for propagation of a successful offer may all be performed in a single one of the POS terminals 22. The evaluation and propagation functions may also be performed in a POS terminal different from the POS terminal in which the performance data was generated. It is thus contemplated to provide the POS network 20 without the central server 24 shown in Fig. 1. The present invention contemplates that, according to one embodiment, the various individual POS terminals 22 may all be programmed to generate, evaluate and propagate offers according to various rules, in a manner such that successful offers are spread to larger and larger numbers of terminals in the network, whereas less successful offers are suppressed or maintained in force in a smaller number of terminals or carry less weight. The process of evaluating and propagating offers may proceed without central control and in a manner that is substantially unpredictable, with the successful offers spreading in a manner akin to biological species such that the "fittest" offers survive and multiply. POS terminals could select between two successful offers both propagated to the same POS terminal by exclusively using the more successful of the two offers. Alternatively, both offers can be used part of the time, with the more successful offer used more frequently than the less successful offer.
Offers that are less successful may be systematically changed as to one or more of the rules which determine the offer and then may be used again as modified. A
"sniffer" program may be employed to detect offers that have failed in a predetermined number of modifications and/or a predetermined number of locations and to prevent such offers from being used further.
If an offer is determined to be extraordinarily successful, the system may operate to propagate the offer to all or a large number of other locations.
According to one embodiment, all offers may generate a message to be propagated in the POS network 20. The message may comprise, for example, rule information, results information, and/or weighting action instructions. Each POS terminal 22 may then adjust a rule or weighting information based on a received message. According to another embodiment, all successful offers may generate such a message to be propagated in the POS network 20 (e.g., instructing all POS terminals 22 to increase a particular weight by a small amount). In this way, successful offers may eventually become more heavily weighted. According to another embodiment, a central server may gather sales and rules data to identify, for example, general trends in sales (e.g., product popularity), acceptance rates. The central server may then propagate information as appropriate (e.g., to create or modify offer rules, offer scripts, and/or propagation rules).
Whether offer evaluation and propagation are centrally controlled, or are allowed to evolve in a de-centralized fashion, the system of the present invention presents an attractive environment in which to perform multivariable testing (MVT), which has been shown to develop better solutions than single-factor test designs. MVT may be particularly advantageous in a large POS network, with thousands of terminals in which many different combinations of factors may be tested simultaneously at one or a few sites each. Data generated from multivariable testing may be analyzed by using a neural network. Evaluation and propagation of offers may also utilize so-called "genetic algorithms".
The teachings of the present invention may also be applied in a network of intelligent vending machines, gaming devices (e.g. , video slot machines) and/or in a network of card authorization terminals such as credit card validation terminals.
Similarly, the teaching may be employed wherein the POS terminal 22 comprises a Web-server or a personal computer coupled to a Web-server (e.g. , to propagate information associated with successful banner advertisements and/or Web-based ordering). Note that in this case, the POS network 20 may simply comprise one or more Web-servers.
Moreover, the teaching are not limited to the propagation of information associated with offers (e.g., legally binding offers or other types of offers). For example, any information related to transactions (e.g., transactions involving an actual sale or other types of transactions) or other interactions (e.g., customer interactions or other types of interactions) may be propagated. Types of information that may be used to determine an offer and/or to propagate information in the POS network 20 include cashier performance information (e.g., information associated with cashier ability, speed, and/or training), cashier compensation information, item pricing (e.g., price points associated with items and/or groups of items), software configuration options, and supply chain processes. Similarly, the propagation of information may be associated with interactions with customers and/or with other software programs (e.g., a software application executing at a POS terminal 22).
Although the present invention has been described with respect to some possible embodiments, those skilled in the art will note that various modifications may be made to those embodiments without departing from the spirit and scope of the present invention.

Claims

What is claimed is:
1. A method of communicating information in a network of point-of-sale (POS) terminals, the method comprising: identifying performance data relating to an offer made at a first POS terminal; determining if the performance data meets at least one predetermined criterion; automatically selecting at least one additional POS terminal in said network based at least in part on a result of the determining step; and automatically making available to said selected at least one additional POS terminal an indication of an offer based on the offer made at the first POS terminal.
2. A method according to claim 1 , wherein said determining step is performed by a server computer connected to said network of POS terminals on the basis of data sent from said first POS terminal to said server computer.
3. A method according to claim 1, wherein said determining step is performed by said first POS terminal.
4. A method according to claim 1 , wherein said determining step is performed by another one of said POS terminals.
5. A method according to claim 1, wherein said making available step includes sending data to said selected at least one additional POS terminal from a server computer connected to said network of POS terminals.
6. A method according to claim 1, wherein said making available step includes sending data from said first one of said POS terminals to said selected at least one additional POS terminal.
7. A method according to claim 1 , wherein said making available step includes sending data to said selected at least one additional POS terminal from another one of said POS terminals.
8. A method according to claim 1, wherein: said identifying step includes receiving said performance data at a server computer connected to said network of POS terminals; said determining and selecting steps are performed by said server computer; and said making available step includes sending data from said server computer to said at least one additional POS terminal.
9. A method according to claim 1, wherein: said identifying step includes generating said performance data at said first POS terminal; said determining and selecting steps are performed by said first POS terminal; and said making available step includes sending data from said first POS terminal to said at least one additional POS terminal.
10. A method according to claim 1, wherein said determining step is performed by a server computer connected to said network of POS terminals, and at least part of each of said identifying, selecting and making available steps is performed by at least one of said POS terminals.
11. A method according to claim 1, wherein said selecting step is performed by a server computer connected to said network of POS terminals, and at least part of each of said identifying, determining and making available steps is performed by at least one of said POS terminals.
12. A method according to claim 1, wherein said determining and selecting steps are performed by a server computer connected to said network of POS terminals, and at least part of each of said identifying and making available steps is performed by at least one of said POS terminals.
13. A method according to claim 1, wherein: said identifying step includes receiving said performance data at a second one of said POS terminals other than said first POS terminals; said determining and selecting steps are performed by said second POS terminal; and said making available step includes sending data from said second POS terminal to said at least one additional POS terminal.
14. A method according to claim 1, wherein said offer made at said first POS terminal comprises at least one of an upsell offer, a suggestive sell offer, a conditional subsidy offer, a coupon offer and a rebate offer.
15. A method according to claim 7, wherein said upsell offer is a dynamically-priced upsell offer.
16. A method according to claim 1 , wherein said at least one predetermined criterion includes at least one of: a rate at which said offer made at said first POS terminal is accepted at said first POS terminal; a profit margin of a product referred to in said offer; an effect of said offer on sales of a product being promoted; an effect of said offer on gross revenues of a store at which said first POS terminal is located; a ratio of a dollar value of said offer to a dollar value of a transaction; a contribution for a product associated with said offer; a gross margin for a product associated with said offer; a ration of a gross margin for a product associated with said offer to a gross margin of a transaction; an effect of said offer made at said first POS terminal on other sales handled at said first POS terminal; a total dollar volume of sales handled at said first POS terminal; a labor factor required to produce a product refened to in said offer made at said first POS terminal; a rate of inventory turnover at a store at which said first POS terminal is located; a quantity of inventory at a store at which said first POS terminal is located; an amount of time required to perform a transaction at said first POS terminal; an amount of time that customers wait for service at said first POS terminal; an amount of time required to produce a product referred to in said offer made at said first POS terminal; an age of at least some item of inventory at a store at which said first POS terminal is located; a waste factor applicable to inventory at a store at which said first POS terminal is located; a success factor applicable to other offers tested at and propagated from said first POS terminal; a demographic characteristic of a customer base of a store at which said first POS terminal is located; a customer retention rate applicable to a store at which said first POS terminal is located; a frequency at which customers visit a store at which said first POS terminal is located; a measure of customer satisfaction at a store at which said first POS terminal is located; an employee retention rate applicable to a store at which said first POS terminal is located; a measure of employee satisfaction at a store at which said first POS terminal is located; an effect of said offer made at said first POS terminal on transactions at at least one other POS terminal; an average dollar value of transactions at said first POS terminal; an average number of items ordered in transactions at said first POS terminal; and a trend in any one of the criteria recited in this claim.
17. A method according to claim 1, further comprising the step of transmitting, to at least one of a server connected to said network of POS terminals and a POS terminal of said network, performance data including at least one of: a time of day at which said offer made at said first POS terminal is successful; a day of the week at which said offer made at said first POS terminal is successful; whether a day at which said offer was made at said first POS terminal is a holiday; a season of the year at which said offer made at said first POS terminal is successful; an outdoor temperature when said offer made at said first POS is successful; a demographic characteristic of a store at which said first POS terminal is located; a characteristic of a customer associated with said offer; a purchasing history of a customer associated with said offer; a number of persons in a party associated with said offer; a characteristic of an employee associated with said offer; a size of a store at which said first POS terminal is located; a geographic location of a store at which said first POS terminal is located; a physical characteristic of a store at which said first POS terminal is located; a characteristic of a labor market at a location of said first POS terminal; and a location relative to competing businesses of a store at which said first POS terminal is located.
18. A method according to claim 1 , further comprising the step, performed prior to said determining step, of specifying said at least one additional POS terminal.
19. A method according to claim 18, wherein said specifying step includes storing a target identifier in a server computer in association with data indicative of said offer made at said first POS terminal, said target identifier for specifically indicating said at least one additional POS terminal.
20. A method according to claim 18, wherein said specifying step includes storing a target identifier in said first POS terminal, said target identifier for specifically indicating said at least one additional POS terminal.
21. A method according to claim 1, wherein said selecting step includes identifying said at least one additional POS terminal on the basis of its geographical location.
22. A method according to claim 21, wherein said selecting step includes identifying said at least one additional POS terminal on the basis of its geographical location relative to said first POS terminal.
23. A method according to claim 1, wherein said selecting step includes identifying said at least one additional POS terminal on the basis of a demographic characteristic of a customer base of said at least one additional POS terminal.
24. A method according to claim 23, wherein said at least one additional POS terminal is identified as having a customer base similar to a customer base of said first POS terminal.
25. A method according to claim 23, wherein said at least one additional POS terminal is identified as having a customer base that is dissimilar to a customer base of said first POS terminal.
26. A method according to claim 23, further comprising the step of collecting demographic characteristics of customers who accept the offer provided at said first POS terminal; and wherein said at least one additional POS terminal is identified as having a customer base similar to the customers who accept the offer provided at said first POS terminal.
27. A method according to claim 1, wherein said selecting step includes identifying said at least one additional POS terminal on the basis of a characteristic of an operator of said at least one additional POS terminal.
28. A method according to claim 1, further comprising the step of performing a regression analysis to determine factors which lead to success for said offer at said first POS; and wherein said step of selecting said at least one additional POS terminal is based on a result of said regression analysis.
29. A method according to claim 1, wherein said selection of said at least one additional POS terminal is based in part on a history of transactions at said at least one additional POS terminal.
30. A method according to claim 1, wherein said selecting step includes determining whether said at least one additional POS terminal has a characteristic needed to make an offer to be made at said at least one additional POS terminal.
31. A method according to claim 1 , wherein said selecting step includes determining whether an offer to be made at said at least one additional POS terminal is compatible with other offers being made at said at least one additional POS terminal.
32. A method according to claim 1, wherein said selecting step includes determining a cost of implementing an offer to be made at said at least one additional POS terminal.
33. A method according to claim 1, wherein said selecting step includes determining whether a store at which said at least one additional POS terminal is located has a facility needed to make an offer to be made at said at least one additional POS terminal.
34. A method according to claim 1 , wherein said selecting step includes determining whether a store at which said at least one additional POS terminal is located has material needed to make an offer to be made at said at least one additional POS terminal.
35. A method according to claim 1 , wherein said selecting step is based in part on a performance characteristic of said at least one additional POS terminal.
36. A method according to claim 1 , wherein said selecting step is based in part on a characteristic of a mix of products sold at said at least one additional POS terminal.
37. A method according to claim 1, wherein said selecting step includes determining that said at least one additional POS terminal lacks a characteristic of said first POS terminal.
38. A method according to claim 1, wherein said making available step includes making message data available to said at least one additional POS terminal, said message data representing a message to be conveyed to customers at said at least one additional POS terminal in connection with said offer.
39. A method according to claim 1 , wherein said making available step includes making message data available to said at least one additional POS terminal, said message data indicating a manner of conveying a message to customers at said at least one additional POS terminal in connection with said offer.
40. A method according to claim 1 , wherein said making available step includes making rule data available to said at least one additional POS terminal, said rule data for instructing said at least one additional POS terminal to determine circumstances when said offer is made at said at least one additional POS terminal.
41. A method according to claim 1 , wherein said making available step includes making weighting data available to said at least one additional POS terminal, said weighting data for selecting among a plurality of upsell offers to be made at said at least one additional POS terminal.
42. A method according to claim 1, wherein at least some of said POS terminals include, respectively, a card authorization terminal.
43. A method according to claim 1, wherein said POS terminals comprise at least one of: vending machines, personal computers, telephones, and Web-servers.
44. A method of communicating information in a network of POS terminals, the method comprising the steps of: providing a first offer at a first one of the POS terminals; determining that said first offer satisfies a first success criterion; providing a second offer at a second one of the POS terminals; determining that said second offer satisfies a second success criterion; and automatically selecting one of said first offer and said second offer and propagating said selected offer to at least one additional POS terminal of said network of POS terminals.
45. A method of communicating information in a network of POS terminals, the method comprising the steps of: providing an offer at a first one of the POS terminals; evaluating performance of said offer at said first POS terminal; determining whether a rejection condition is satisfied at a second one of the POS terminals; automatically propagating said offer to said second POS terminal if it is determined at said evaluating step that said offer meets at least one predefined evaluation criterion, but only if said rejection condition is not satisfied at said second POS terminal.
46. A method according to claim 45, wherein said determining step is performed by a server computer connected to said network of POS terminals on the basis of data sent from said second POS terminal to said server computer.
47. A method according to claim 46, wherein said evaluating step is performed by said server computer on the basis of data sent from said first POS terminal to said server computer.
48. A method according to claim 45, wherein said determining step is performed by said second POS terminal.
49. A method according to claim 48, wherein said evaluating step is performed by said first POS terminal.
50. A network of point-of-sale (POS) terminals, comprising: a plurality of POS terminals, each of said POS terminals including, respectively, a processor, and a communication port and a memory connected to the processor; network means connected to said POS terminals for transmitting data to and from said POS terminals; means for providing an offer at a first one of the POS terminals; means, responsive to said means for providing, for evaluating performance of said offer at said first POS terminal; means, responsive to said means for evaluating, for automatically selecting at least one additional POS terminal of said plurality of POS terminals; and means, responsive to said means for selecting, for automatically propagating said offer to said selected at least one additional POS terminal.
51. A network of POS terminals according to claim 50, further comprising a server computer connected to said network means.
52. A network of POS terminals according to claim 51, wherein said server computer constitutes at least one of said means for evaluating, said means for selecting and said means for propagating.
53. A network of POS terminals according to claim 50, wherein said processor of said first POS terminal constitutes said means for evaluating.
54. A method according to claim 53, wherein said memory of said first POS terminal stores data indicative of said at least one additional POS terminal.
55. A method of propagating offer information in a network of POS terminals, the method comprising the steps of: storing offer information in a first one of said POS terminals; providing an offer at said first POS terminal in accordance with said stored offer information; evaluating performance of said offer on the basis of performance information gathered at said first POS terminal; automatically selecting at least one additional POS terminal of said network if said offer was determined to be successful at said evaluating step; automatically transmitting said offer information to said selected at least one additional POS terminal; and storing said transmitted offer information in said selected at least one additional POS terminal.
56. A method according to claim 55, wherein said offer information is transmitted to said selected at least one additional POS terminal by a server computer which is connected to said network of POS terminals.
57. A method according to claim 55, wherein said offer information is transmitted to said selected at least one additional POS terminal by a POS terminal of said network of POS terminals.
58. A method according to claim 57, wherein said offer information is transmitted to said selected at least one additional POS terminal by said first POS terminal.
59. A method according to claim 55, wherein said offer information includes at least one rule for determining when to make said offer.
60. A network of POS terminals, comprising: a plurality of POS terminals, each of said POS terminals including, respectively, a processor, and a communication port and a memory connected to the processor; network means connected to said POS terminals for transmitting data to and from said POS terminals; a first one of said POS terminals having offer information stored in the memory thereof, said stored offer information instructing said first POS terminal to provide an offer; said network further comprising: means for evaluating performance of said offer on the basis of performance data gathered at said first POS terminal; means for automatically selecting at least one additional POS terminal of said network if said offer was determined to be successful by said evaluating means; and means for automatically transmitting said offer information for storage in the memory of said selected at least one additional POS terminal of said network.
61. A network of POS terminals installed at a plurality of store locations, each of said store locations having at least one of said POS terminals installed thereat, the network further comprising data communication means interconnecting said POS terminals, and processing means programmed to: provide an offer to customers at a first one of said store locations; evaluate performance of said offer at said first store location; select at least one additional store location if said offer is determined to be successful at said first store location; and automatically transmit to the POS terminals installed at the selected at least one additional store location offer information corresponding to said offer.
62. A digital memory which stores a propagation rules database, said database for controlling propagation of at least one offer in a network of POS terminals and including: at least one offer identifier for indicating an offer; at least one evaluation criterion for determining whether said offer is successful; and at least one propagation rule for indicating one or more of said POS terminals to which said offer is to be propagated if said offer is determined to be successful.
63. A digital memory according to claim 62, wherein said at least one propagation rule includes at least one POS identifier for identifying a specific POS terminal to which said offer is to be propagated if said offer is determined to be successful.
64. A digital memory according to claim 62, wherein said at least one propagation rule defines a process for identifying at least one POS terminal to which said offer is to be propagated if said offer is determined to be successful.
65. A digital memory accordmg to claim 64, wherein said process includes identifying said at least one POS terminal on the basis of a geographical location of said at least one POS terminal.
66. A digital memory accordmg to claim 64, wherein said process includes identifying said at least one POS terminal on the basis of a characteristic of a customer base of a store location at which said at least one POS terminal is installed.
67. A digital memory according to claim 62, wherein said memory is installed in one of said POS terminals.
68. A digital memory according to claim 62, wherein said memory is a part of a server computer connected to said network of POS terminals.
69. A method of propagating an offer in a network of POS terminals, comprising the steps of: storing propagation rule data in a digital memory; after said storing step, determining whether an offer is successful in at least one POS terminal of said network; and automatically propagating said offer to at least one other POS terminal of said network in accordance with said stored propagation rule data, if said offer is determined to be successful at said determining step.
70. A method according to claim 69, wherein said propagation rule data lists at least one POS identifier for specifically identifying said at least one other POS terminal.
71. A method according to claim 69, wherein said propagation rule data defines a process for identifying said at least one other POS terminal.
72. A method of propagating an offer in a network of point-of-sale (POS) terminals, the method comprising the steps of: testing an offer in at least one of said POS terminals; employing processing means to evaluate results of said offer and to automatically propagate said offer to some but not all other POS terminals in said network if said processing means determines that said offer is successful in said at least one POS terminal; and employing processing means to evaluate results of said offer in said some but not all other POS terminals and to automatically propagate said offer to further POS terminals in said network if said processing means determines that said offer is successful in said some but not all other POS terminals.
73. A method according to claim 72, wherein said processing means includes a server computer connected to said network of POS terminals.
74. A method according to claim 72, wherein said processing means includes at least one processor included in the POS terminals of said network.
75. A method of communicating information in a network of point-of-sale (POS) terminals, the method comprising: identifying performance data relating to a transaction at a first POS terminal; and transmitting transaction information to at least one additional POS terminal based on the performance data..
PCT/US2000/019426 1999-08-25 2000-07-17 Dynamic propagation of promotional information in a network of point-of-sale terminals WO2001015033A2 (en)

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