Method and apparatus for controlling offers that are provided at a point-of-sale terminal

A POS terminal or other computing device provides a plurality of offers to customers, and then measures a performance rate of each offer. For example, the acceptance rate or the profit rate of the offers may be measured. Based on the performance rates, a subset of offers is selected. In one embodiment, the highest performing offers are selected. In another embodiment, those offers having performance rates above a predetermined threshold are selected. The selected subset of offers is then provided, while the remaining, less desirable offers are discontinued.

FIELD OF THE INVENTION
 The present invention relates to point-of-sale terminals, and, more
 specifically, to methods and apparatus for controlling offers that are
 provided at point-of-sale terminals.
 BACKGROUND OF THE INVENTION
 Point-of-sale ("POS") terminals, such as cash registers, are used in a wide
 variety of businesses for performing such processes as calculating the
 total price of a purchase (goods or services) and calculating the amount
 of change due to a customer. In addition, POS terminals may also be used
 with an offering system in order to provide offers to customers. Such
 offering systems may be intended to increase sales, and thereby increase
 the average profit gained per transaction.
 One type of offering system is described in the parent application of the
 present application, patent application Ser. No. 08/920,116, entitled
 METHOD AND SYSTEM FOR PROCESSING SUPPLEMENTARY PRODUCT SALES AT A
 POINT-OF-SALE TERMINAL, filed on Aug. 26, 1997. As described therein, a
 customer at a POS terminal is offered an "upsell" in exchange for an
 amount of change he is due. The POS terminal determines an upsell in
 dependence on a purchase of the customer, and also determines an upsell
 price (the amount of change due) based on the purchase. For example, a
 customer purchasing a first product for $1.74 and tendering $2.00 may be
 offered a second product in lieu of the $0.26 change due. The upsell
 price, $0.26, thus depends on the purchase price $1.74. Another type of
 offering system is a computer-determined "suggestive sell". U.S. Pat. No.
 5,353,219 describes a system for suggesting items for a customer to
 purchase at conventional item prices.
 In an offering system, there are many possible offers which may be provided
 to customers. For example, in the above-described upsell offer, many
 different upsells may be offered to a customer in exchange for the
 particular amount of change due. An offer to a customer at a fast-food
 restaurant may include a soda, large French fries, or a dessert. Precisely
 which upsell to offer may be chosen according to a predetermined program
 at random, or manually by a manager or other operator.
 Unfortunately, random or manual selection of an offer does not necessarily
 assure that the "best" (highest performing) offers will be provided to
 customers. What constitutes the "best" offer may be evaluated with respect
 to one or more criteria, yielding corresponding "performance rates" for
 the various offers. For example, the acceptance rate of an offer is a
 performance rate that may be used to evaluate the offer, since some offers
 may be less likely to be accepted by customers than other offers. In
 addition, the profit derived from an accepted offer is another performance
 rate that may be used to evaluate the offer.
 It may be difficult or impossible for a manager or other operator to
 identify the "best" offers (the offers with the highest performance
 rates). A manager is unlikely to have knowledge of the true performance
 rates of a group of offers. A manager is also unlikely to have the time to
 analyze historical trends to identify the best offers. In addition, at
 different times of the day or days of the week, certain offers may be more
 attractive to customers than others. Unanticipated events, such as a high
 state lottery jackpot or a good article in a magazine, may also make
 certain offers more attractive. Such circumstances impede attempts by a
 manager to identify the best offers. Accordingly, a need exists for
 controlling offers that are provided at a point-of-sale terminal.
 SUMMARY OF THE INVENTION
 It is an object of the present invention to control offers that are
 provided at a point-of-sale terminal.
 In accordance with the present invention, a POS terminal or other computing
 device provides a plurality of offers to customers, and then measures a
 performance rate of each offer. For example, the acceptance rate or the
 profit rate of the offers may be measured. Based on the performance rates,
 a subset of offers is selected. In one embodiment, the highest performing
 offers are selected. In another embodiment, those offers having
 performance rates above a predetermined threshold are selected. The
 selected subset of offers is then provided, while the remaining, less
 desirable offers are discontinued.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
 One or more POS terminals control offers that are provided to customers,
 such that those offers which have high performance rates are provided. The
 present invention determines the best offers by providing customers with a
 group of offers, and evaluating the performance rates of the offers. By
 contrast, random or manual (human) selection of offers is unlikely to
 determine the best offers. Furthermore, the present invention
 advantageously relieves managers or other personnel of the task of
 selecting offers.
 By continually evaluating the performance rates of offers, the offers
 provided to customers continue to be the highest performing. If the
 performance rate of a once-attractive offer decreases, it can be replaced
 by other, higher-performing offers.
 The present invention may further make the offer appear to the customer to
 be random, since a POS terminal typically provides different offers at
 different times. This, in turn, can make it difficult for customers to
 manipulate the offer system to their advantage.
 Referring to FIG. 1, a POS terminal 10, which may be the IBM 4683 or IBM
 4693 manufactured by International Business Machines, comprises a
 processor 12, such as one or more conventional microprocessors. The
 processor 12 is in communication with a data storage device 14, such as an
 appropriate combination of magnetic, optical and/or semiconductor memory.
 The processor 12 and the storage device 14 may each be (i) located
 entirely within a single computer 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 10 may comprise one or
 more computers which are connected to a remote server computer for
 maintaining databases.
 An input device 16 preferably comprises a keypad for transmitting input
 signals, such as signals indicative of a purchase, to the processor 12. A
 printer 18 is for registering indicia on paper or other material, thereby
 printing receipts, coupons and vouchers as commanded by the processor 12.
 A display device 20 is preferably a video monitor for displaying at least
 alphanumeric characters to the customer and/or cashier. Many types of
 input devices, printers and display devices are known to those skilled in
 the art, and need not be described in detail herein. The input device 16,
 printer 18 and display device 20 are each in communication with the
 processor 12.
 The storage device 14 stores a program 22 for controlling the processor 12.
 The processor 12 performs instructions of the program 22, and thereby
 operates in accordance with the present invention, and particularly in
 accordance with the methods described in detail herein. The program 22
 furthermore includes program elements that may be necessary, such as an
 operating system and "device drivers" for allowing the processor 12 to
 interface with computer peripheral devices, such as the input device 16,
 the printer 18 and the display device 20.
 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 14 also stores (i) a database of offers 24; (ii) a
 transaction database 26; and (iii) a performance rate database 28. The
 databases 24, 26 and 28 are described in detail below and depicted with
 exemplary entries in the accompanying figures. As will be understood by
 those skilled in the art, the schematic illustrations and accompanying
 descriptions of the databases presented herein are exemplary arrangements
 for stored representations of information. A number of other arrangements
 may be employed besides the tables shown. Similarly, the illustrated
 entries represent exemplary information, but those skilled in the art will
 understand that the number and content of the entries can be different
 from those illustrated herein.
 FIG. 2 illustrates another embodiment of the POS terminal 10, in which a
 control device 28 is in communication via a communication medium 30 with a
 system 32 for providing an offer. The control device 28 comprises a
 processor 34 in communication with the input device 16 and the display
 device 20. The system 32 for providing an offer comprises a processor 36
 in communication with the storage device 14 and the printer 18. In this
 embodiment, the control device 28 may be a cash register, and the system
 32 may be an electronic device for printing coupons in accordance with
 data received from the cash register. Other configurations of the POS
 terminal 10 will be understood by those skilled in the art.
 Referring to FIG. 3, a network 40 includes a server 42 in communication
 with POS terminals 44, 46 and 48. The server 42 directs the operation of,
 stores data from, and transmits data to the POS terminals 44, 46 and 48.
 The server 42 may itself be a POS terminal, as described above, or may be
 another computing device which can communicate with one or more POS
 terminals. Although three POS terminals are shown in FIG. 3, any number of
 POS terminals may be in communication with the server 42 without departing
 from the spirit and scope of the present invention. Each of the POS
 terminals 44, 46 and 48 may be located in the same store, in different
 stores of a chain of stores, or in other locations. The server 42 may
 perform many of the processes described below, especially those processes
 that are performed for more than one POS terminal. The server 42 may
 furthermore store data such as the database of offers 24.
 Referring to FIG. 4, a table 60 illustrates an embodiment of the database
 of offers 24 (FIG. 1). The table 60 includes entries 62, 64, 66 and 68,
 each of which describes an offer to be provided to customers. It will be
 understood by those skilled in the art that the table 60 may include any
 number of entries. Each of the entries 62, 64, 66 and 68 specifies (i) an
 offer identifier 70 for uniquely indicating the offer; (ii) an offer
 description 72 for describing the offer; (iii) a cost of the offer 74 to
 the offeror; and (iv) an offer frequency 76. The offer frequency 76
 indicates the average percentage of times that the corresponding offer is
 to be provided when an offer is provided. For example, each of the entries
 62, 64, 66 and 68 includes an offer frequency of 25%, and thus each of the
 entries 62, 64, 66 and 68 will be provided to customers approximately one
 out of every four times an offer is provided, on average.
 Referring to FIG. 5, a record 90 of the transaction database 26 (FIG. 1)
 defines the transactions performed at a POS terminal identified by a POS
 terminal identifier 92. The transaction database 26 (FIG. 1) typically
 includes a plurality of records such as the record 90, each defining the
 transactions performed at a different POS terminal. The record 90 includes
 entries 94, 96 and 98 which each describe a transaction. It will be
 understood by those skilled in the art that the record 90 may include any
 number of entries. Each of the entries 94, 96 and 98 specifies (i) a
 transaction identifier 100 that uniquely indicates a transaction; (ii) a
 date 102 of the transaction; (iii) a time 104 of the transaction; (iv) a
 purchase description 106 that describes details of the transaction, such
 as the items purchased, the purchase price and/or the identity of the
 customer; (v) an offer identifier 108 that indicates an offer that was
 provided during the transaction; (vi) an indication of whether the offer
 was accepted 110; and (vii) a revenue 112 that is derived due to the
 customer accepting the offer.
 Referring to FIG. 6, a flow chart 120 illustrates a method for controlling
 offers that are provided at one or more POS terminals. Offers are provided
 to customers (step 122) in accordance to the database of offers 24 (FIG.
 1). As described above with reference to the table 60 (FIG. 4), each offer
 includes an offer frequency that indicates the average percentage of times
 that the corresponding offer is to be provided. Thus, the database of
 offers 24 indicates which offers are to be provided to customers, and also
 indicates the frequency with which the offers are to be provided.
 For example, the POS terminal 10 (FIG. 1) (or the server 42 of FIG. 3, in a
 networked embodiment) may generate a random number between 0 and 1 each
 time an offer is to be provided. Then, an offer would be selected in
 accordance with the random number and with the offer frequency illustrated
 in FIG. 4. A random number between 0.00 and 0.25 would correspond to the
 offer "A", while a random number between 0.26 and 0.50 would correspond to
 the offer "B", and so on for offers "C" and "D".
 Alternatively, the POS terminal 10 or server 42 can provide a first offer
 during a first series of transactions, and then provide subsequent offers
 during consecutive series of transactions. The sizes of the series of
 transactions (the number of transactions in the series) would be selected
 in accordance with the offer frequencies 76 of the table 60 (FIG. 4). For
 example, each of the offers specified by the table 60 of FIG. 4 has an
 equal offer frequency (25%). Thus, the first offer "A" defined by the
 entry 62 could be provided to customers during a first series of ten
 transactions, and the remaining three offers defined by the entries 64, 66
 and 68 could be provided during subsequent series of ten transactions
 each. Since there are four offers and each offer is provided to customers
 during ten out of forty transactions, each offer has a frequency of 25%.
 In another embodiment, each of a plurality of POS terminals may provide a
 different offer to customers. For example, a first POS terminal could
 provide a first offer during a series of one hundred transactions, and a
 second POS terminal could provide a second offer during a series of one
 hundred transactions. Accordingly, both the first offer and the second
 offer would have a frequency of 50% (100/(100+100)=0.50=50%).
 Once offers are provided to customers at step 122, the POS terminal 10 or
 server 42 calculates the performance rate of each offer (step 124). The
 performance rate may be any measured and/or calculated quantity, such as
 an Acceptance Rate or a Profit Rate. Many other performance rates will be
 understood by those skilled in the art. The performance rate of each offer
 may be calculated at predetermined periods, such as at the end of each
 day, or after predetermined numbers of offers have been provided to
 customers.
 An Acceptance Rate may be calculated in accordance with the following:
EQU Acceptance Rate=Number of Times Accepted/Number of Times Provided
 The Number of Times Provided is the number of times a particular offer was
 provided to customers. Similarly, the Number of Times Accepted is the
 number of times that the provided offer was accepted by customers. Both
 the Number of Times Provided and the Number of Times Accepted may be
 determined from data stored in the transaction database 26 (FIG. 1). It is
 typically desirable to have a high Acceptance Rate, and ideally an offer
 will have an Acceptance Rate of 100%. However, it is likely that the
 Acceptance Rate of an offer will be less than 100%.
 Referring to FIG. 7, a table 140 illustrates an embodiment of the
 performance rate database 28 (FIG. 1). In this embodiment, the performance
 rate database 28 is configured to store Acceptance Rate data as described
 above. The table 140 includes entries 142, 144, 146 and 148, each of which
 describes an offer that has been provided to customers. It will be
 understood by those skilled in the art that the table 140 may include any
 number of entries. Each of the entries 142, 144, 146 and 148 specifies (i)
 an offer identifier 150 for uniquely indicating the offer; (ii) a number
 of times accepted 152; (iii) a number of times provided 154; and (iv) an
 acceptance rate 156 of the offer. The table 140 may thus be used in
 determining which offers have the highest performance rate.
 A Profit Rate is a performance rate of an offer that may be calculated in
 accordance with the following:
EQU Profit Rate=(Revenue-Cost)/Number of Times Provided
 The Revenue is the amount of all income derived due to customers accepting
 the offer. The Cost is the expense incurred from customers accepting the
 offer. The Number of Times Provided is the number of times a particular
 offer was provided to customers.
 Referring to FIG. 8, a table 170 illustrates another embodiment of the
 performance rate database 28 (FIG. 1). In this embodiment, the performance
 rate database 28 is configured to store average profit per offer. The
 table 170 includes entries 172, 174, 176 and 178, each of which describes
 an offer that has been provided to customers. It will be understood by
 those skilled in the art that the table 170 may include any number of
 entries. Each of the entries 172, 174, 176 and 178 specifies (i) an offer
 identifier 180 for uniquely indicating the offer; (ii) a number of times
 accepted 182; (iii) a number of times provided 184; (iv) an average
 revenue derived per accepted offer 186; (v) an average profit derived per
 accepted offer 188; and (vi) an average profit derived per offer 190.
 Those skilled in the art will understand that the number of times accepted
 182, the number of times provided 184 and the average revenue 186 may be
 determined from data stored in the transaction database 26 (FIG. 1). For
 example, referring again to the record 90 of FIG. 5, at the POS terminal
 #7 the offers "A", "B" and "C" have each been offered once, as seen from
 the offer identifier 108. The offers "B" and "C" have each been accepted
 once, as indicated by the offer accepted 110 field. Similarly, the revenue
 derived for the offers "A", "B" and "C" is $0.00, $0.50 and $0.78
 respectively. An average revenue for each offer would be derived by
 dividing the total revenue from each offer by the number of times it was
 offered.
 The average profit per accepted offer 188 may be determined by subtracting
 the cost per offer (the cost 74 of FIG. 4) from the average revenue 186.
 Finally, the average profit per offer 190, which is the profit rate
 defined above, may be determined by multiplying the average profit per
 accepted offer 188 by the acceptance rate of the offer. As described
 above, the acceptance rate of the offer is determined by dividing the
 number of times accepted 182 by the number of times provided 184.
 Referring again to FIG. 6, after the performance rates of the offers have
 been calculated (step 124), the POS terminal 10 or server 42 determines
 modifications to the database of offers 24 based on the performance rates
 (step 126). Each offer may be provided at a different offer frequency, or
 even discontinued, in accordance with the calculated performance rate of
 that offer. As described below, offers with higher performance rates
 continue to be provided to customers, and are typically provided at higher
 offer frequencies. Similarly, offers with low performance rates are
 typically provided at lower offer frequencies, or may even cease to be
 provided altogether.
 In one embodiment, only offers having performance rates greater than a
 predetermined threshold continue to be provided to customers. If one or
 more offers cease to be provided, each offer frequency must be changed, as
 described below.
 FIG. 9 illustrates the selection of offers to discontinue. A table 200
 depicts data stored in an embodiment of the performance rate database 28
 (FIG. 1). For each offer, there is an offer identifier 202 and an
 acceptance rate 204. A threshold 206 of 10% defines which of the offers in
 the table 200 will continue to be provided. In particular, the offers
 defined by entries 208 and 210 (the offers "A" and "B") have acceptance
 rates greater than 10%, and thus will continue to be provided. By
 contrast, the offers defined by entries 212 and 214 (the offers "C" and
 "D") have acceptance rates less than 10%, and thus will be discontinued.
 A table 216 depicts data stored in an embodiment of the database of offers
 24 (FIG. 1). As described above with respect to FIG. 4, each offer has an
 offer identifier 218 and an offer frequency 220. Since the offers "C" and
 "D" have been discontinued, the corresponding offer frequencies of those
 offers are 0%. The offer frequencies of the offers "A" and "B", which
 continue to be offered, change accordingly. The offer frequencies may be
 changed so that they are equal to each other (50% each). Alternatively,
 the offer frequencies may be changed in accordance with their relation to
 one another, as follows:
EQU F.sub.new =F.sub.old /F.sub.total
 Where:
 F.sub.new is the new offer frequency
 F.sub.old is the offer frequency prior to being changed
 F.sub.total is the sum of the values of F.sub.old for the offers that are
 not discontinued
 In FIG. 9, the offer frequency "58%" of the offer "A" is calculated by from
 the offer frequencies of the offers that are not discontinued:
EQU 58%=20.4%/(20.4%+14.8%)
 The offer frequency "42%" of the offer "B" is similarly calculated:
EQU 42%=14.8%/(20.4%+14.8%)
 Those skilled in the art will understand that there are other methods for
 changing the offer frequencies of offers.
 In another embodiment, a predetermined number of the highest-performing
 offers continue to be provided to customers. The remaining offers, if any,
 are not provided. FIG. 10 illustrates the selection of offers to
 discontinue in this embodiment. A table 240 depicts data stored in another
 embodiment of the performance rate database 28 (FIG. 1). For each offer,
 there is an offer identifier 242 and an average profit per order 244. A
 threshold 246 of "three" defines the number of highest-performing offers
 in the table 240 which will continue to be provided. In particular, the
 offers defined by entries 248, 250 and 252 (the offers "A", "B" and "C")
 are the top three offers with respect to average profit per order, and
 thus will continue to be provided. By contrast, the offer defined by entry
 254 (the offer "D") will be discontinued.
 A table 256 depicts data stored in an embodiment of the database of offers
 24 (FIG. 1). As described above, each offer has an offer identifier 258
 and an offer frequency 260. Since the offer "D" has been discontinued, the
 corresponding offer frequency is 0%. The offer frequencies of the offers
 "A", "B" and "C", which continue to be offered, change accordingly. The
 offer frequencies may be changed so that they are equal to each other
 (331/3% each). Alternatively, the offer frequencies may be changed in
 accordance with their relation to one another, in the manner described
 above.
 Once offers have been discontinued, it may be desirable to make them
 available again at some time in the future. For example, after an offer
 has been discontinued due to a poor performance rate, conditions such as
 consumer tastes may change. Accordingly, discontinued offers may continue
 to be maintained in the database of offers 24 (FIG. 1), and, after an
 offer has been discontinued for more than a predetermined amount of time,
 it may be advantageous to evaluate its performance rate once again. The
 discontinued offer may be granted a randomly-selected or predetermined
 offer frequency, allowing the corresponding performance rate to be
 evaluated.
 In addition, in some situations, after offers are discontinued only one
 offer may continue to be offered. The performance rate of this offer is
 evaluated, and compared with the performance rate of the offer in prior
 time periods. If the performance rate declines below that of prior time
 periods, the offer may be discontinued and replaced. As a replacement,
 another (discontinued) offer may be granted a randomly-selected or
 predetermined offer frequency, allowing the corresponding performance rate
 to be evaluated.
 In some embodiments it may be desirable that the offer frequency of certain
 offers be unchanged, regardless of the performance rate calculated for
 those offers. For example, a high-value offer could have a very low offer
 frequency. The offer could then act as a prize that few customers could
 receive. Accordingly, the cost of giving such a high-value offer in
 exchange for change due would be incurred rarely, yet could serve as
 advertising to prompt customers to frequent a business.
 Referring to FIG. 11, a table 300, similar to the table 60 of FIG. 4,
 illustrates another embodiment of the database of offers 24 (FIG. 1). The
 table 300 includes entries 302, 304, 306 and 308, each of which describes
 an offer to be provided to customers. Each of the entries 302, 304, 306
 and 308 specifies (i) an offer identifier 310 for uniquely indicating the
 offer; (ii) an offer description 312 for describing the offer; (iii) a
 cost of the offer 314 to the offeror; (iv) an offer frequency 316 and (v)
 a fixed frequency indication 318. The fixed frequency indication 318
 indicates whether the corresponding offer frequency may be changed based
 on the performance rate of the offer, as described above. For example, the
 entry 308 includes an offer frequency of 1%. Since this offer has a
 relatively high value ($50 gift certificate), it is likely that it will be
 accepted often, perhaps always. However, the high cost ($50) of the offer
 can make it unprofitable to offer more frequently. Accordingly, the
 frequency of that offer is fixed at 1%.
 Although the present invention has been described with respect to a
 preferred embodiment thereof, those skilled in the art will note that
 various substitutions may be made to those embodiments described herein
 without departing from the spirit and scope of the present invention. For
 example, the evaluation of offers may also account for the time of day at
 which the offers were provided.