SE543238C2 - Method and apparatus for processing a purchase using individualized article information readable from an article to determine an individual price - Google Patents

Abstract

A purchase of an individual article (132) of a certain article type is processed as follows. Data (152) is read (210) from a data carrier (150) provided on the individual article (132). Collective article information (160) is identified (220) in the read data (152), being common to articles of the same type and comprising article number information but no price information. Individualized article information (170) is identified (230) in the read data (152), pertaining to the individual article and potentially being different from individualized article information of other articles of the same type. An individual price (138) for the individual article (132) is determined (240, 250) through one or more computer resource enquiries (180; 182-184) based on data (162, 172) in the identified collective and individualized article information (160, 170). A payment transaction (190) is performed (260), wherein a buyer (102) is charged the determined individual price (138).

Description

_. _ .. II METHOD AND APPARATUS FOR PROCESSING APURCHASE OF--fX-N--ffkš-ëïïl-ï-l-í-i-É-Ell--I-N-A--lšHäf-êšä-íåïifæ-L--Sf-š-'ïíàRíé-USINGINDIVIDUALIZED ARTICLE INFORMATION READABLE FROM ARTICLE TO DETERMINE AN INDIVIDUAL PRICE x . - _. _. . Q ffl..

TECHNICAL FIELD The present invention generally relates to computerized equipment andfunctionality for improved handling of articles in physical stores in terms ofsustainability or traceability. More specifically, the invention relates to a computerizedmethod of processing a purchase of an individual article, selected among a plurality ofarticles of a same article type, in a physical store. The invention also relates to an associated computerized system.

BACKGROUND Since the resources of our planet are limited and because we are facingincreasing challenges to cope with over-usage of these limited resources and otherenvironmental problems, the general society has directed much attention tosustainability and traceability of articles in and for physical stores in recent times.

Laws and regulations require that many kinds of articles be associated with amanufacturing date, best-before date, or both. This is because product quality and safetymay degrade with time. Examples of such kinds of articles are dairy products, bakeryproducts, meat, vegetables and fruit. As is commonly known, products with a limitedlifespan are commonly marked with a best-before date. This will allow customers toestimate the freshness or expected remaining usability of the products before deciding tobuy them. The present inventor has identified quite severe problems and shortcomingsin this regard.

For instance, if articles of the same type (such as l-litre packages of milk of acertain brand) have different best-before dates in the store, then many customers have atendency of always looking for and choosing individual articles of a later best-beforedate over articles of the same type which have an earlier best-before date. As a result,relatively older products in the store get more and more hard to sell, and will ultimatelyhave to be disposed of, or retumed to the manufacturer/distributor.

Moreover, imposing age limits on products is a rather imprecise tool. In manycases, an article is far from useless even if the best-before date is approaching or has even lapsed. Still, since customers generally favor younger articles over older ones judging from the best-before date, the older products Will be perceived as beingrelatively Speaking over-priced compared to the younger products of the same type, andtherefore remain unsold in the store.

A similar problem may arises for certain batches or other subgroups of articlesof a certain type. For instance, a certain production batch may be subject to a certainminor quality impairrnent such as, for instance, slight discoloration, finish artefacts,mounting misalignment, etc. Again, such a mildly impaired batch of articles may stillrepresent a potential usability, but nevertheless be rejected by customers in favor ofarticles from normal batches and are therefore likely to remain unsold.

For every unsold article there Will be an environmental penalty due to the factthat the resources that Were used to produce the article Will not result in actual use of theproduct and therefore represent a Waste of resources. In addition, every unsold articleWill have to be logistically handled, therefore adding on to the environmental penalty interms of transport and storage resources.

In line With the observations above, the present inventor has identified both theneed for and the benefits of a computerized manner of processing a purchase of anindividual article, selected among a plurality of articles of a same article type, in aphysical store. This serves to offer improvements in sustainability and/or traceability of articles and to mitigate the draWbacks of remaining unsold articles.

SUMMARY It is accordingly an object of the invention to solve, eliminate, alleviate,mitigate or reduce at least some of the problems and shortcomings referred to above.

A first aspect of the present invention is a computerized method of processinga purchase of an individual article, selected among a plurality of articles of a samearticle type, in a physical store, Wherein the method comprises: reading data from a data carrier provided on the article to be purchased; identifying collective article information in the data read from the data carrier,Wherein the collective article information is common to articles of said same article typeand coinprises article niimber information luv: no price iiifbrrnatioii; identifying individualized article information in the data read from the datacarrier, Wherein the individualized article information pertains to the individual articleto be purchased and is potentially different from individualized article information of other individual articles of said same article type; making one or more computer resource enquiries to determine an individualprice for the article to be purchased based on data in the identified collective articleinformation as Well as data in the identified individualized article information; and causing performance of a payment transaction for Which a buyer of the articleto be purchased is charged the deterrnined individual price.

The provision of such a computerized method Will solve or at least mitigateone or more of the problems or drawbacks identified in the background section of thisdocument, as Will be clear from the following detailed description section and thedrawings.

Advantageously, the computerized method more specifically involves makinga first computer resource enquiry to retrieve a nominal price for the article to bepurchased based on the data in the identified collective article information, Which maycomprise an article number for the article type. The computerized method furtherinvolves making a second computer resource enquiry to determine a possible deviationfrom the nominal price based on the data in the identified individualized articleinformation, Which for instance may comprise one or more of a manufacturing date, amanufacturing time, a best-before date, a best-before time, a batch number for articlesmanufactured in the same batch, and a subgroup identifier Which is common to asubgroup of all articles of said type.

The computerized method then deterrnines the individual price for the article tobe purchased based on the retrieved nominal price, as modified, When applicable, by thedeterrnined deviation. This represents a highly flexible approach, Which is stillbackWards compatible With existing solutions Where the price of an article of a certainarticle type is based solely on collective article information, such as article number. Theflexibility is provided by the second computer resource enquiry; since it operates onindividualized article information in contrast to collective article information, thedeviation from the nominal (collective) price can be defined in a virtually unlimitednumber of different Ways to take into account factors such as article age or articlesubgroup (e. g. production batch) to obtain an improved effect in sustainability and/ortraceability. The benefits of this approach Will appear more clearly from the various usecases that are described in the detailed description section of this document.

In advantageous embodiments, the data carrier is a machine-readable opticalcode, such as for instance a QR (Quick Response) code.

Advantageously, as already briefly touched upon, the individual price for the article to be purchased may be deterrnined as a nominal price subject to a discount, the discount being based on the data in the identified individualized article information. Usecases that are believed to be particularly beneficial for improved sustainability byreducing the fraction of articles that remain unsold include applying the computerizedmethod such that a discount is made available for older articles, possibly such that thediscount grows bigger as the articles grow older, or such that a discount is madeavailable for articles that are close to their best-before date, possibly such that thediscount grows bigger the closer to the best-before date.

Other use cases that are believed to be particularly beneficial for improvedsustainability in this regard involve applying the computerized method such that adiscount is made available for articles for which the best-before date has expired,possibly such that the discount grows bigger as time goes past the best-before date.

Still other use cases that are believed to be particularly beneficial for improvedsustainability in this regard involve applying the computerized method such that acertain discount is made available close to the best-before date, whereas a biggerdiscount is made available after the best-before date.

Use cases that are believed to be particularly beneficial for improvedtraceability by reducing the fraction of articles that remain unsold include applying thecomputerized method such that it comprises analyzing the individualized articleinformation to determine whether it identifies the article to be purchased as belonging toa certain subgroup of articles of the same article type. It is recalled that the analyzedindividualized article information may comprise at least one of a batch number forarticles manufactured in the same batch, and a subgroup identifier which is common toa subgroup of all articles of the article type in question. If the article to be purchased isidentified as belonging to the certain subgroup, the computerized method deterrnines adiscount associated with the certain subgroup, and applies the deterrnined discountwhen deterrnining the individual price for the article to be purchased.

Advantageously, the computerized method according to any of theembodiments referred to above further causes performance of a compensationtransaction for which a manufacturer or distributor of the article to be purchasedfinancially compensates a merchant of the physical store for at least a part of thedeterrnined discount. This makes the approach even more attractive in terms ofsustainability and/or traceability, since it introduces motivation not only for the endcustomer (the buyer of the article in question) but also for the store merchant.

The computerized method according to any of the embodiments referred to above may further involve presenting the deterrnined individual price for the article to be purchased to the buyer prior to causing performance of the payment transaction. Thisis beneficial for several reasons. It will make store customers aware of the existence ofthe approach according to the computerized method, which in tum will boost theapproach in terms of sustainability and/or traceability. Moreover, it gives the potentialbuyer of an article the option to accept or decline the purchase based on the deterrninedindividual price. In situations where the individual price includes a discount, seeing thediscount in advance will likely increase the potential buyer°s motivation to actuallyproceed with the purchase of the article, even when it is about to expire (or has in factalready expired), or belongs to an impaired production batch or article subgroup.

In some embodiments, without limitation, the computerized method isperformed in or by a computerized point-of-sale system in the physical store. In otherembodiments, without limitation, the computerized method is performed in or by amobile communication device.

A second inventive aspect is a computerized apparatus for processing apurchase of an individual article, selected among a plurality of articles of a same articletype, in a physical store. The apparatus comprises a reader device and a processingdevice. The processing device is configured for performing the method according to thefirst aspect as referred to above, including any or all of its embodiments.

The provision of such a computerized apparatus will solve or at least mitigateone or more of the problems or drawbacks identified in the background section of thisdocument, as will be clear from the following detailed description section and thedrawings.

Other aspects, objectives, features and advantages of the disclosed embodi-ments will appear from the following detailed disclosure, from the attached dependentclaims as well as from the drawings. Generally, all terms used in the claims are to beinterpreted according to their ordinary meaning in the technical field, unless explicitlydefined otherwise herein.

All references to "a/an/the [element, device, component, means, step, etc]" areto be interpreted openly as referring to at least one instance of the element, device,component, means, step, etc., unless explicitly stated otherwise. The steps of anymethod disclosed herein do not have to be performed in the exact order disclosed,unless explicitly stated.

A reference to an entity being "designed for" doing something, or "capable of " doing something in this document is intended to mean the same as the entity being 77 CC "arranged for , configured for" or "adapted for" doing this very something, and vice VCTSEJ..

BRIEF DESCRIPTION OF THE DRAWINGS Fig 1 illustrates an embodiment of a computerized apparatus for processing apurchase of an individual article, selected among a plurality of articles of a same articletype, in a physical store.

Fig 2 illustrates an altemative embodiment of the computerized apparatus.

Fig 3 illustrates another embodiment of the computerized apparatus.

Fig 4 illustrates yet another embodiment of the computerized apparatus.

Fig 5 illustrates still another embodiment of the computerized apparatus.

Fig 6 illustrates an embodiment of a computerized method of processing apurchase of an individual article, selected among a plurality of articles of a same articletype, in a physical store.

Fig 7 illustrates another embodiment of the computerized method.

Fig 8 illustrates yet another embodiment of the computerized method.

DETAILED DESCRIPTION The disclosed embodiments will now be described more fully hereinafter withreference to the accompanying drawings, in which certain embodiments of the inventionare shown. This invention may, however, be embodied in many different forms andshould not be construed as limited to the embodiments set forth herein; rather, theseembodiments are provided by way of example so that this disclosure will be thoroughand complete, and will fully convey the scope of the invention to those skilled in the art.Like numbers refer to like elements throughout.

Fig 1 illustrates a computerized apparatus 100 for processing a purchase of anindividual article 132 in a physical store 140. The individual article 132 is selected orselectable by a potential buyer 102 among a plurality of articles 130 of a same articletype. The articles may, for instance, be dairy products, bakery products, meat,vegetables, fruit, snacks, drinks, deli products, etc, as well as products that are notrelated to food or drinks.

More samples of the articles 130 of the same article type may be storedextemal to the store 140, such as in a remote warehouse 142 operated by the store merchant, or by a distributor or a manufacturer of the article type in question.

The Computerized apparatus 100 has a reader device 110 and a processingdevice 120. The processing device 120 is conf1gured for receiving, from the readerdevice 110, data 152 that has been read 151 from a data carrier 150 provided on thearticle 132 to be purchased, and for identifying collective article information 160 in thedata 152 read from the data carrier. Even though not shown in Fig 1, respective datacarriers like data carrier 150 for the individual article 132 will be provided not only onthe individual article 132 but rather on all articles 130,. The collective articleinformation 160 is common to articles of the same article type, i.e. to all articles 130 inthe situation shown in Fig 1. Accordingly, the data carriers of all the articles 130 will allcontain the same collective article information 160, which may typically comprise data162 in the form of an article number for the article type in question.

In the disclosed embodiment, the data carrier 150 is a machine-readable opticalcode, such as for instance a QR (Quick Response) code. Other types of machine-readable optical codes are however also conceivable.

The processing device 120 of the computerized apparatus 100 is furtherconf1gured for identifying individualized article information 170 in the data 152 readfrom the data carrier at 151, wherein the individualized article information pertains tothe individual article 132 to be purchased and is potentially different fromindividualized article information of other individual articles 130 of said same articletype. Data 172 in the identified individualized article information 170 may typicallycomprise one or more of a manufacturing date, a manufacturing time, a best-before date(or expiry date), a best-before time (or expiry time), a batch number for articlesmanufactured in the same batch, and a subgroup identifier which is common to asubgroup of all articles 130 of said type (i.e. less than all articles 130).

In the embodiment in Fig 1, the processing device 120 makes a computerresource enquiry 180 to determine an individual price 138 for the article 132 to bepurchased based on the data 162 in the identified collective article information 160, aswell as data 172 in the identified individualized article information 170. The computerresource enquiry 180 is referred to as GetPríce in Fig 1, has the data 162 in theidentified collective article information 160 as well as the data 172 in the identifiedindividualized article information 170 as arguments, and is directed at a computerresource 181. The GetPríce retrieval 180 retums the individual price 138 for the article132 to be purchased.

In the embodiment in Fig 1, the computer resource 181 is local to the store 140; it may however altematively be an extemal computer resource 181", as is indicated by hatched lines for computer resource enquiry 180" in Fig 1 (taking the same argumentsas the aforementioned computer resource enquiry 180).

The processing device 120 then causes perforrnance of a payment transaction190 for which the buyer 102 of the article 132 to be purchased is charged thedeterrnined individual price 138. This may involve invoking a ChargeBuyer transaction190 at a payment service 192, wherein the ChargeBuyer transaction 190 takes thedeterrnined individual price 138 as argument. As is seen in Fig 1, the payment service192 is typically an extemal service in Fig 1, accessible via a broadband communicationnetwork 110. Other altematives are however conceivable.Fig 2 illustrates an altemativeembodiment of the computerized apparatus 100. Here, the processing device 120 isconfigured for making a first computer resource enquiry 182 to a first computerresource 183 so as to retrieve a nominal price 134 for the article 132 to be purchasedbased on the data 162 in the identified collective article information 160 (e. g. articlenumber). In Fig 2, the first computer resource enquiry 182 is made as a GetNomPríceretrieval 182, taking the data 162 in the identified collective article information 160 asargument and retuming the nominal (collective) price 134 of the article 132 to bepurchased.

The processing device 120 is furtherrnore configured for making a secondcomputer resource enquiry 184 to a second computer resource 185 so as to determine apossible deviation 136 from the nominal price 134 based on the data 172 in theidentified individualized article information 170 (e.g., manufacturing date/time, best-before date/time (or expiry date/time), batch number/subgroup identifier, etc). In Fig 2,the second computer resource enquiry 184 is made as a GetDevíatíon retrieval 184,taking the data 172 in the identified individualized article information 170 and possiblyalso the data 162 in the identified collective article information 160 as arguments, andretuming the deviation 136 to be applied to the nominal price 134 of the article 132 tobe purchased.

Then, the processing device 120 is configured for deterrnining the individualprice 138 for the article 132 to be purchased based on the retrieved nominal price 134,as modified, when applicable, by the deterrnined deviation 136.

In the embodiment shown in Fig 2, the processing device 120 is configured formaking the second computer resource enquiry 184 by sending a request to the remoteserver resource 185 via a communication interface 122 of the computerized apparatus100 (see Fig 3) and the broadband communication network 110. The request is a firstpart of the GetDevíatíon retrieval 184 and includes the data 172 in the identified individualized article information 170 and possibly also the data 162 in the identifiedcollective article information 160. The processing device 120 is further configured forreceiving a response to the request from the remote server resource 185 via thecommunication interface 122. The response is a second part of the GetDevíatíonretrieval 184 and includes the deviation 136 from the nominal price 134, Whenapplicable.

As further seen for the embodiment of Fig 2, the processing device 120 may beconfigured for enquiring a local store database 183 using the data 162 in the identifiedcollective article information 160. The enquiry is a first part of the GetNomPríceretrieval 182. The processing device 120 is further configured, in response, for receivingthe nominal price 134 for the article to be purchased from the local store database 183.The receiving is a second part of the GetNomPríce retrieval 182 and includes thenominal price 134.

Advantages of the embodiment in Fig 2 have been referred to in the summarysection of this document.

As can be seen in Fig 4, the computerized apparatus 100 may advantageouslybe comprised in a computerized point-of-sale system 310 in the physical store 140. Asseen at 312, the buyer 102 Will bring the selected individual article 132 to be purchasedfrom the spot Where it is marketed (together With the other articles 130 of the samearticle type) in the store 140, to the computerized point-of-sale system 310 typicallybeing located at a cash register or checkout area of the store 140.

The reader device 110 may, When appropriate, be implemented by an existingscanner device capable of scanning, for instance, QR codes from printed coupons or thedisplay screens of mobile devices. The processing device 120 may be implemented byan existing processing unit in the computerized point-of-sale system 310, beingappropriately (re-)programmed to perform its technical functionality as described in thisdocument. Such a processing unit may, for instance, be a microcontroller, CPU, DSP,FPGA, ASIC, etc.

As can be seen in Fig 5, the computerized apparatus 100 may altematively becomprised in or as a mobile communication device 320. The mobile computing device320 may, for instance, be a mobile phone, tablet computer, personal digital assistant,smart glasses, smart Watch or smart bracelet. The mobile communication device 320may implement the reader device 110 as Well as the processing device 120, similar tothe description above for Fig 4. For instance, a camera and an appropriately programmed image scanner application program in the mobile communication device 320 may implement the reader device 110, Whereas a processing unit in the forrn of, forinstance, a microcontroller, CPU, DSP, FPGA or ASIC together With an appropriatelyprogrammed application program may implement the processing device 120.

Further altematives than those described for Fig 4 and Fig 5 are conceivable.

Fig 6 illustrates an embodiment of a computerized method 200 of processing apurchase of an individual article 132, selected among a plurality of articles 130 of asame article type, in a physical store 140. In a first step 210, the computerized method200 comprises reading data 152 from a data carrier 150 provided on the article 132 to bepurchased.

Then, in a second step 220, the computerized method 200 comprisesidentifying collective article information 160 in the data 152 read from the data carrier150, as seen at 151 in Figs 1, 2, 4 and 5. It is recalled that the collective articleinformation 160 is common to articles 130 of the same article type.

In a third step 230, the computerized method 200 comprises identifyingindividualized article information 170 in the data 152 read from the data carrier 150.The individualized article information 170 pertains to the individual article 132 to bepurchased and is potentially different from individualized article information of otherindividual articles 130 of the same article type.

The computerized method 200 then comprises making 240 one or morecomputer resource enquiries (cf 180 in Fig 1 and 182-184 in Fig 2) to determine 250 anindividual price 138 for the article 132 to be purchased based on data 162 in theidentified collective article information 160 as Well as data 172 in the identifiedindividualized article information 170.

The computerized method 200 finally comprises causing 260 performance of apayment transaction (cf 190 in Fig 1 and Fig 2), for Which a buyer 102 of the article 132to be purchased is charged the deterrnined individual price 138.

Fig 7 illustrates a ref1ned embodiment of the computerized method 200. Inaddition to the steps described for Fig 6, the computerized method 200 in Fig 7 alsocomprises a step 255 of presenting at least either the deterrnined individual price 138 orthe deviation/ discount 136 for the article 132 to be purchased to the buyer 102, prior tocausing performance 260 of the payment transaction 190. Advantages of this ref1nedembodiment have been referred to in the summary section of this document.

Accordingly, a corresponding ref1ned embodiment 100" of the computerizedapparatus further comprises a display device 128 (see Fig 3), Wherein the processing device 120 is further configured for causing the display device 128 to present at least ll either the deterrnined individual price 138 or the deviation 136 for the article 132 to bepurchased to the buyer 102, prior to causing perforrnance of the payment transaction1 90.

Fig 8 illustrates another refined embodiment of the Computerized method 200.In addition to the steps described for Fig 6, the computerized method 200 in Fig 8 alsocomprises a step 270 of causing performance of a compensation transaction 192 (seeFig 2) for which a manufacturer or distributor of the article 132 to be purchasedfinancially compensates a merchant of the physical store 140 for at least a part of thedeterrnined discount 136. Advantages of this refined embodiment have been referred toin the summary section of this document.

In a corresponding refined embodiment of the computerized apparatus 100, theprocessing device 120 is further configured for performing the functionality of step 270by making a CompMerch transaction request 191 at the payment service 192 (or anotherpayment service, refund service or crediting service), taking the deviation/discount 136as argument. This is seen in Fig 2.

A number of use cases for the computerized apparatus 100 and method 200 intheir intended operational environment will now be described. These use cases areconsidered as being particularly advantageous but shall nevertheless be understood asbeing exemplifying and non-limiting to the general scope of the present invention.

In these use cases, the processing device 120 is configured for deterrnining 250the individual price 138 for the article 132 to be purchased as a nominal price 134subject to a discount 136, wherein the discount 136 is based on the data 172 in theidentified individualized article information 170. Hence, the discount 136 is a specialform of the aforementioned deviation 136.

A first use case that is believed to be particularly beneficial for improvedsustainability by reducing the fraction of articles that remain unsold involves applyingthe computerized apparatus 100 and method 200 such that a discount is made availablefor older articles, possibly such that the discount grows bigger as the articles growolder, or such that a discount is made available for articles that are close to their best-before date, possibly such that the discount grows bigger the closer to the best-beforedate.

Accordingly, in the first use case, the discount 136 increases as the differenceincreases between a current date or time and a manufacturing date or time for the article132 to be purchased, wherein the manufacturing date or time is indicated by the data 172 in the identified individualized article information 170. 12 A second use case that is believed to be particularly beneficial for improvedsustainability involves applying the computerized apparatus l00 and method 200 suchthat a discount is made available for articles for which the best-before date has expired,possibly such that the discount grows bigger as time goes past the best-before date.

Accordingly, in the second use case, the discount l36 increases as thedifference decreases between a best-before date or time for the article l32 to bepurchased and a current date or time, wherein the best-before date or time is indicatedby the data l72 in the identified individualized article information l70, and wherein thecurrent date or time precedes the best-before date or time.

Moreover, the discount l36 may increase as the difference increases between acurrent date or time and a best-before date or time for the article l32 to be purchased,wherein the best-before date or time is indicated by the data l72 in the identifiedindividualized article information l70, and wherein the best-before date or timeprecedes the current date or time.

A third use case that is believed to be particularly beneficial for improvedsustainability involves applying the computerized apparatus l00 and method 200 suchthat a certain discount is made available close to the best-before date, whereas a biggerdiscount is made available after the best-before date.

Accordingly, in the third use case, the discount l36 is deterrnined as a functionof the difference between a current date or time and a best-before date or time for thearticle l32 to be purchased, wherein the best-before date or time is indicated by the datal72 in the identified individualized article information l70. The discount functiondefines a first discount or discount increase when the current date or time precedes thebest-before date or time, and a second discount or discount increase when the best-before date or time precedes the current date or time. The second discount or discountincrease is greater than the first discount or discount increase.

A fourth use case that is believed to be particularly beneficial for improvedtraceability by reducing the fraction of articles that remain unsold involves applying thecomputerized apparatus l00 and method 200 such that they comprise analyzing theindividualized article information l70 to determine whether or not it identifies thearticle l32 to be purchased as belonging to a certain subgroup of articles of the samearticle type. It is recalled that the analyzed individualized article information l70 maycomprise at least one of a batch number for articles manufactured in the sameproduction batch, and a subgroup identifier which is common to a subgroup of all articles of the article type in question. If the article l32 to be purchased is identified as 13 belonging to the certain subgroup, the computerized apparatus 100 and method 200determine a discount associated With the certain subgroup, and apply the deterrnineddiscount When deterrnining the individual price 138 for the article 132 to be purchased.

The broadband communication network 110 as referred to in this documentmay, for instance, be compliant With WCDMA, HSPA, GSM, UTRAN, UMTS, LTE orLTE Advanced, or altematively Wired data communication based, for instance, onTCP/IP.

The computer resources described in this document, particularly the ones thatare extemal to the physical store 140, may be implemented by server computers,clusters of such computer devices, or cloud computing resources or services, havingprocessing units in the form of, for instance, CPUs and/or DSPs, and being programmedto perform the respective functionalities as described in this document by the processingunit executing program instructions of computer programs.

The invention has mainly been described above With reference to a fewembodiments. HoWever, as is readily appreciated by a person skilled in the art, otherembodiments than the ones disclosed above are equally possible Within the scope of the invention, as defined by the appended patent claims.

Claims (36)

1. A Computerized method (200) of processing a purchase of an individualarticle (132), selected among a plurality of articles (130) of a same article type, in aphysical store (140), the method comprising: reading (210) data (152) from a data carrier (150) provided on the article (132)to be purchased; identifying (220) collective article information (160) in the data (152) readfrom the data carrier (150), Wherein the collective article information is common toarticles of said same article type and comprises article number information but no priceinformation; identifying (230) individualized article information (170) in the data (152) readfrom the data carrier, Wherein the individualized article information pertains to theindividual article to be purchased and is potentially different from individualized articleinformation of other individual articles of said same article type; making (240) one or more computer resource enquiries (180; 182-184) todetermine (250) an individual price (138) for the article (132) to be purchased based ondata (162) in the identified collective article information (160) as Well as data (172) inthe identified individualized article information (170); and causing (260) performance of a payment transaction (190) for Which a buyer(102) of the article (132) to be purchased is charged the deterrnined individual price(1 3 8).

2. The computerized method (200) of processing a purchase of an individualarticle as defined in claim 1, Wherein making said one or more computer resourceenquiries (180; 182-184)) to determine the individual price (138) for the article (132) tobe purchased involves: making a first computer resource enquiry (182) to retrieve a nominal price(134) for the article (132) to be purchased based on the data (162) in the identifiedcollective article information (160); making a second computer resource enquiry (184) to determine a possibledeviation (136) from the nominal price (134) based on the data (172) in the identified individualized article information (170); and deterrnining (250) the individual price (138) for the article to be purchasedbased on the retrieved nominal price (134), as modified, When applicable, by the deterrnined deviation (136).

3. The computerized method (200) of processing a purchase of an individualarticle as defined in any preceding claim, Wherein the data carrier (150) is a machine- readable optical code.

4. The computerized method of processing a purchase of an individual articleas defined in any preceding claim, Wherein the data (162) in the identified collective article inforrnation (160) comprises an article number for said article type.

5. The computerized method of processing a purchase of an individual articleas defined in any preceding claim, Wherein the data (172) in the identifiedindividualized article inforrnation (170) comprises one or more of: a manufacturing date; a manufacturing time; a best-before date; a best-before time; a batch number for articles manufactured in the same batch; and a subgroup identifier Which is common to a subgroup of all articles of said type.

6. The computerized method of processing a purchase of an individual articleas defined in any preceding claim, Wherein the individual price (138) for the article tobe purchased is deterrnined (250) as a nominal price (134) subject to a discount (136),the discount (136) being based on the data (172) in the identified individualized article inforrnation (170).

7. The computerized method of processing a purchase of an individual articleas defined in claim 6, Wherein the discount (136) increases as the difference increasesbetween a current date or time and a manufacturing date or time for the article to bepurchased, the manufacturing date or time being indicated by said data (172) in the identified individualized article inforrnation (170). 16

8. The Computerized method of processing a purchase of an individual articleas defined in claim 6, wherein the discount (136) increases as the difference decreasesbetween a best-before date or time for the article to be purchased and a current date ortime, the best-before date or time being indicated by said data (172) in the identifiedindividualized article inforrnation (170), the current date or time preceding the best- before date or time.

9. The computerized method of processing a purchase of an individual articleas defined in claim as defined in claim 6, wherein the discount (136) increases as thedifference increases between a current date or time and a best-before date or time for thearticle to be purchased, the best-before date or time being indicated by said data (172) inthe identified individualized article inforrnation (170), the best-before date or time preceding the current date or time.

10. The computerized method of processing a purchase of an individual articleas defined in claim 6, wherein the discount (136) is deterrnined as a function of thedifference between a current date or time and a best-before date or time for the article tobe purchased, the best-before date or time being indicated by said data (172) in theidentified individualized article inforrnation (170), wherein the discount function defines a first discount or discount increasewhen the current date or time precedes the best-before date or time, and a seconddiscount or discount increase when the best-before date or time precedes the currentdate or time, and wherein the second discount or discount increase is greater than the first discount or discount increase.

11. The computerized method of processing a purchase of an individual articleas defined in any of claims 1-5, further comprising: analyzing the individualized article inforrnation (170) to determine whether ornot it identifies the article (132) to be purchased as belonging to a certain subgroup ofarticles of said same article type; and if the article (132) to be purchased is identified as belonging to the certainsubgroup: deterrnining a discount associated with the certain subgroup; and 17 applying the deterrnined discount When deterrnining (250) the individual price(138) for the article (132) to be purchased.

12. The Computerized method of processing a purchase of an individual articleas defined in claim 11, Wherein the analyzed individualized article inforrnation (170)comprises at least one of a batch number for articles manufactured in the same batch, and a subgroup identifier Which is common to a subgroup of all articles of said article type.

13. The computerized method of processing a purchase of an individual articleas defined in any preceding claim, Wherein the individual price (138) for the article tobe purchased is deterrnined (250) as a nominal price (134) subject to a discount (136),the discount (136) being based on the data (172) in the identified individualized articleinforrnation (170), the method further comprising: causing (270) performance of a compensation transaction (192) for Which amanufacturer or distributor of the article to be purchased financially compensates amerchant of the physical store (140) for at least a part of the deterrnined discount (136).

14. The computerized method of processing a purchase of an individual articleas defined in any preceding claim, further comprising: presenting (255) at least either the deterrnined individual price (138) or thedeviation (136) for the article (132) to be purchased to the buyer (102) prior to causingperformance (260) of the payment transaction (190).

15. The computerized method of processing a purchase of an individual articleas defined in claim 2, Wherein making the second computer resource enquiry (184)comprises: sending a request to a remote server resource (185) via a communicationinterface (122), the request including the data (172) in the identified individualizedarticle inforrnation (170); and receiving a response to the request from the remote server resource (185) viathe communication interface (122), Wherein the response includes the possible deviation(136) from the nominal price (134). 18

16. The Computerized method of processing a purchase of an individual articleas defined in claim 15, Wherein making the first computer resource enquiry (182)comprises: enquiring a local store database (183) using the data (162) in the identifiedcollective article inforrnation (160); and in response receiving the nominal price (134) for the article to be purchasedfrom the local store database (183).

17. The computerized method of processing a purchase of an individual articleas defined in any preceding claim, performed by a computerized point-of-sale system(3 10).

18. The computerized method of processing a purchase of an individual article as defined in any of claims 1-16, performed by a mobile communication device (320).

19. A computerized apparatus (100) for processing a purchase of an individualarticle (132), selected among a plurality of articles (130) of a same article type, in aphysical store (140), the apparatus comprising: a reader device (110); and a processing device (120), Wherein the processing device (120) is configuredfor: receiving, from the reader device (110), data (152) that has been read from adata carrier (150) provided on the article (132) to be purchased; identifying collective article information (160) in the data (152) read from thedata carrier, Wherein the collective article information is common to articles of saidsame article type and comprises article number information but no price information; identifying individualized article information (170) in the data (152) read fromthe data carrier, Wherein the individualized article information pertains to the individualarticle to be purchased and is potentially different from individualized articleinformation of other individual articles of said same article type; making one or more computer resource enquiries (180; 182-184) to determinean individual price (138) for the article (132) to be purchased based on data (162) in theidentified collective article information (160) as Well as data (172) in the identified individualized article information (170); and 19 causing performance of a payment transaction (190) for Which a buyer (102) ofthe article (132) to be purchased is charged the deterrnined individual price (138).

20. The computerized apparatus (100) as defined in claim 19, Wherein theprocessing device (120) is configured for making said one or more computer resourceenquiries (180; 182-184) to determine the individual price (138) for the article (132) tobe purchased by: making a first computer resource enquiry (182) to retrieve a nominal price(134) for the article (132) to be purchased based on the data (162) in the identifiedcollective article information (160); making a second computer resource enquiry (184) to determine a possibledeviation (136) from the nominal price (134) based on the data (172) in the identifiedindividualized article information (170); and deterrnining the individual price (138) for the article to be purchased based onthe retrieved nominal price (134), as modified, When applicable, by the deterrnineddeviation (136).

21. The computerized apparatus (100) as defined in claim 19 or 20, Wherein the data carrier (150) is a machine-readable optical code.

22. The computerized apparatus (100) as defined in any of claims 19-21,Wherein the data (162) in the identified collective article information (160) comprises anarticle number for said article type.

23. The computerized apparatus (100) as defined in any of claims 19-21,Wherein the data (172) in the identified individualized article information (170)comprises one or more of: a manufacturing date; a manufacturing time; a best-before date; a best-before time; a batch number for articles manufactured in the same batch; and a subgroup identifier Which is common to a subgroup of all articles of said type.

24. The computerized apparatus (100) as defined in any of claims 19-23,wherein the individual price (138) for the article (132) to be purchased is deterrnined(250) as a nominal price (134) subject to a discount (136), the discount (136) beingbased on the data (172) in the identified individualized article inforrnation (170).

25. The computerized apparatus (100) as defined in claim 24, wherein thediscount (136) increases as the difference increases between a current date or time and amanufacturing date or time for the article (132) to be purchased, the manufacturing dateor time being indicated by said data (172) in the identified indiVidualized article information (170).

26. The computerized apparatus (100) as defined in claim 24, wherein thediscount (136) increases as the difference decreases between a best-before date or timefor the article (132) to be purchased and a current date or time, the best-before date ortime being indicated by said data (172) in the identified indiVidualized article information (170), the current date or time preceding the best-before date or time.

27. The computerized apparatus (100) as defined in claim 24, wherein thediscount (136) increases as the difference increases between a current date or time and abest-before date or time for the article (132) to be purchased, the best-before date ortime being indicated by said data (172) in the identified indiVidualized article information (170), the best-before date or time preceding the current date or time.

28. The computerized apparatus (100) as defined in claim 24, wherein thediscount (136) is deterrnined as a function of the difference between a current date ortime and a best-before date or time for the article (132) to be purchased, the best-beforedate or time being indicated by said data (172) in the identified indiVidualized articleinformation (170), wherein the discount function defines a first discount or discount increasewhen the current date or time precedes the best-before date or time, and a seconddiscount or discount increase when the best-before date or time precedes the currentdate or time, and wherein the second discount or discount increase is greater than the first discount or discount increase. 21

29. The computerized apparatus (100) as defined in claim 24, Wherein theprocessing device (120) is further configured for: analyzing the individualized article inforrnation (170) to deterrnine Whether ornot it identifies the article (132) to be purchased as belonging to a certain subgroup ofarticles of said same article type; and if the article (132) to be purchased is identified as belonging to the certainsubgroup: deterrnining a discount associated With the certain subgroup; and applying the deterrnined discount When deterrnining (250) the individual price(138) for the article (132) to be purchased.

30. The computerized apparatus (100) as defined in claim 29, Wherein theanalyzed individualized article information (170) comprises at least one of a batchnumber for articles manufactured in the same batch, and a subgroup identifier Which is common to a subgroup of all articles of said type.

31. The computerized apparatus (100) as defined in any of claims 19-30,Wherein the individual price (138) for the article to be purchased is deterrnined (25 0) asa nominal price (134) subject to a discount (136), the discount (136) being based on thedata (172) in the identified individualized article information (170), and Wherein theprocessing device (120) is further configured for: causing performance of a compensation transaction (192) for Which amanufacturer or distributor of the article to be purchased financially compensates amerchant of the physical store (140) for at least a part of the deterrnined discount (136).

32. The computerized apparatus (100) as defined in any of claims 19-31,further comprising a display device (128), Wherein the processing device (120) isfurther configured for: causing the display device (128) to present at least either the deterrninedindividual price (138) or the deviation (136) for the article (132) to be purchased to thebuyer (102), prior to causing performance (260) of the payment transaction (190).

33. The computerized apparatus (100) as defined in claim 20, furthercomprising a communication interface (122), Wherein the processing device (120) is configured for making the second computer resource enquiry (184) by: 22 sending a request to a remote server resource (185) via a communicationinterface (122), the request including the data (172) in the identified individualizedarticle inforrnation (170); and receiving a response to the request from the remote server resource (185) viathe communication interface (122), Wherein the response includes the possible deviation(136) from the nominal price (134).

34. The computerized apparatus (100) as defined in claim 33, Wherein theprocessing device (120) is configured for making the first computer resource enquiry(182) by: enquiring a local store database (183) using the data (162) in the identifiedcollective article information (160); and in response receiving the nominal price (134) for the article to be purchasedfrom the local store database (183).

35. The computerized apparatus (100) as defined in any of claims 19-34, comprised in a computerized point-of-sale system (310).

36. The computerized apparatus (100) as defined in any of claims 19-34, comprised in a mobile communication device (320).