APPARATUS, SYSTEM AND METHOD FOR SECURE TRANSACTIONS AND MONITORING IN A RETAIL ENVIRONMENT

Abstract

An apparatus, system method of providing mobile checkout. The apparatus, system and method may include obtaining, via an opt-in to an in-store wireless network, of consumer device data regarding a plurality of consumer mobile devices, the consumer data comprising device use data, prior purchase data, and GPS data, receiving video surveillance data related to at least one consumer having consumer device data, interrelating, from at least one non-transitory computer-readable medium storing at least the consumer device data and the video surveillance data, of at least the consumer device data and the video surveillance data by at least one computing processor, and applying, by the computing processor, of a plurality of business rules to the interrelated datas to enable at least the mobile checkout, wherein the mobile checkout includes a purchase of at least one in-store item via the consumer device associated with the purchasing one of the at least one consumer.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Ser. No. 61/762,106, filed Feb. 7, 2013 entitled “Apparatus, System and Method for Secure Transactions and Monitoring in a Retail Environment”; U.S. Provisional Application Ser. No. 61/762,122, filed Feb. 7, 2013 entitled, “Apparatus, System and Method for Stimulating and Securing Retail Transactions”; and U.S. Provisional Ser. No. 61/762,113, filed Feb. 7, 2013 entitled “Apparatus, System and Method for Facilitating and Securing Access to Transactions in a Retail Environment”, the entire disclosure of which are incorporated herein as if set forth in its entirety.

BACKGROUND

1. Field of the Disclosure

The instant disclosure relates to retail transactions, and, in particular, to apparatuses, systems and methods for secure transactions and transaction monitoring in a retail environment.

2. Background of the Disclosure

In the present retail market, it is generally the case that tethered point of service (POS) devices are used in-store to provide a variety of functionality. These tethered POS devices include, by way of non-limiting example: cash registers that scan items either at the direction of a cashier or the direction of a consumer (at “self checkout”) in order to allow for a transaction, i.e., to allow the user to be charged for goods desired for purchase; and tracking devices, such as cameras and scanners, for tracking consumer patterns and for POS tracking of purchased or unpurchased items. These tethered POS devices thus provide for transactions, and help minimize loss in the form of mistake or theft.

However, the retail environment is changing rapidly, particularly with the advent of smart phones. “Mobile checkout” using smartphones and like devices is increasingly desired by consumers, but mobile checkout leads to a plurality of issues, particularly with respect to a loss by mistake and theft. Further, mobile checkout may give rise to issues with regard to, for example, loyalty programs and the like, as well as consumer and consumer purchase tracking.

Therefore, the needs exists for an apparatus, system, and method to allow for mobile checkout and in-store shopping in a secure manner, but also in a manner that decreases the probability of theft and mistake while improving consumer tracking.

SUMMARY OF THE DISCLOSURE

The apparatus, system and method of the disclosure may include obtaining, via an opt-in to an in-store wireless network, of consumer device data regarding a plurality of consumer mobile devices, the consumer data comprising device use data, prior purchase data, and GPS data, receiving video surveillance data related to at least one consumer having consumer device data, interrelating, from at least one non-transitory computer-readable medium storing at least the consumer device data and the video surveillance data, of at least the consumer device data and the video surveillance data by at least one computing processor, and applying, by the computing processor, of a plurality of business rules to the interrelated datas to enable at least the mobile checkout, wherein the mobile checkout includes a purchase of at least one in-store item via the consumer device associated with the purchasing one of the at least one consumer.

Thus, the present invention provides an apparatus, system, and method to allow for mobile checkout and in-store shopping in a secure manner, but also in a manner that decreases the probability of theft and mistake while improving consumer tracking.

BRIEF DESCRIPTION OF THE FIGURES

Understanding of the present invention will be facilitated by consideration of the following detailed description of the preferred embodiments of the present invention taken in conjunction with the accompanying drawings, in which like numerals refer to like parts:

FIG. 1 illustrates aspects of the disclosed embodiments; and

FIG. 2 illustrates aspects of the disclosed embodiments.

DETAILED DESCRIPTION OF THE EMBODIMENTS

It is to be understood that the figures and descriptions of the present invention have been simplified to illustrate elements that are relevant for a clear understanding of the present invention, while eliminating, for the purpose of clarity, many other elements found in typical retail environment, electronic purchase, telecommunications network, and security, apparatuses, systems, and methods. Those of ordinary skill in the art may recognize that other elements and/or steps are desirable and/or required in implementing the present invention. However, because such elements and steps are well known in the art, and because they do not facilitate a better understanding of the present invention, a discussion of such elements and steps is not provided herein. The disclosure herein is directed to all such variations and modifications to the disclosed elements and methods known to those skilled in the art.

The present invention is and includes apparatuses, systems, and methods that may be provided, for example, by a smartphone, such as in an “app” associated with the smartphone, wherein consumers may engage in mobile self or assisted checkout using the app and/or the smartphone without accessing tethered points of service in making retail purchases. Those skilled in the art will appreciate, in light of the discussion herein, that a phone, smart phone, or like term, may include any type of mobile computing device, including a PDA, a tablet computer, a laptop, or the like. The present invention also provides, through the use of such embodiments, the maintaining of security of goods, security of the purchase transaction for the buyer and seller, decrease in loss and theft, and improvement in consumer, employee and purchase tracking, in real time and over predetermined time periods. The technologies provided herein may thus include and/or be partially dependent upon location-based technologies, such as GPS or triangulation. Thus, with respect to GPS, the as used herein may include any location based technologies. For example, a user may have GPS location services turned off on the user's phone but, should the user opt into the in-store network, the user's phone may still be located via, for example, triangulation with knowledge of the user's MAC address or the like. The systems and method provided herein may further include features dependent upon near field communications (NFC), radio frequency identification (RFID), Bluetooth, or like wireless reading technologies, as well as including aspects dependent upon UPC, JAN, barcodes, QR codes, EAN codes, or the like.

In previous retail embodiments, most retail establishments provide point of service (POS) purchase systems. In such systems, a barcode or like identifying code, such as those referenced above, is read, typically by a scanner, or is entered by a cashier. When the code is scanned, thereby indicating that a consumer desires to make a purchase, that code is sent to a database which associates the item for purchase with the barcode or like code, and which associates that item for purchase with a purchase price. Thereafter, the consumer is asked to pay that purchase price via cash, credit card, debit card, or the like.

However, it is becoming increasingly prevalent that retailers offer, or wish to offer, opt-in programs for in-store Wi-Fi, thereby allowing in-store processes to be untethered from POS. Further, to the extent such opt-in programs are offered for Wi-Fi, opt-out programs may similarly be offered, although a retailer may place limitations on an opt-out program. However, for a variety of reasons, it is still atypical that the available untethering of many in-store transactions has occurred prior to the instant invention. These reasons include lack of acceptable transaction security and increased likelihood of theft, among other reasons.

In an example of a non-purchase in-store transaction, it is also typical that in-store tracking of consumers occurs, particularly using security video. For example, several large retail chains employ digital (such as Internet protocol, or “IP”) or analog -based camera systems through which security personnel can see all, many, or some portions of the store simultaneously. In such embodiments, it is typical that in-store staff watches security cameras across the store as well as purchase transactions at the POS of purchase, such as in order to enforce loss prevention mechanisms in real time. Such security video may additionally be maintained or recorded, and, as discussed further herein, the present invention may provide the ability to use and manage such security video locally, remotely, via mobile application, or the like.

It is further the case that, in prior retail embodiments, retailers employ exception based reporting (EBR). In the course of an EBR transaction, the transaction is viewed in light of a plurality of business rules that indicate the relative value of the transaction. In an EBR system, particularly high value transactions are focused on, particularly from a security, loss, mistake and/or theft standpoint. In present day systems, EBR tracking gives insight into relevant retail factors for high value transactions, although present systems are exclusively tethered, and include solely batched data.

In view of the foregoing, it is evident that previously available systems provide a plurality of mechanisms that might improve the convenience, speed and security of mobile checkout, but it is also clear that these mechanisms give rise to a plurality of difficulties for mobile checkout that have gone previously unaddressed. For example, with respect to the foregoing EBR discussion, were a transaction to occur anywhere in the store other than a tethered POS subject to security cameras and through which a purchaser would be “funneled” to exit the store, the ability to isolate that high value transaction appreciably decreases. By way of non-limiting example, in a EBR context that employed mobile checkout, a consumer might much more readily swap price tags in a remote aisle and engage in a mobile checkout in which the consumer pays $9.99 for a shirt that originally had a tag on it for $99.99. This happens, in part because it is difficult to use EBR to isolate this transaction in a remote aisle of the store in a mobile checkout context.

Thus, the present invention may provide, as illustrated in FIG. 1, an opt-in Wi-Fi system 10, wherein a smart phone 12 may opt-in to an in-store Wi-Fi network 14. The opt-in system 10 and network 14 may similarly comprise, for example, a cellular system, Bluetooth system, or the likie, as will be appreciated by those of skill in the pertinent arts. The phone may further include on or more apps 16 that allow for mobile checkout 18, such as secure apps that allow an item to be scanned by the phone, have the price of the item received by the phone, and access given to a payment capability on the phone for the scanned item, such as access to credit card data, Google Wallet, or the like of the phone's owner. As used herein, mobile checkout 18 may also include mobile return (such as wherein a user uses an e-receipt, or scans a paper receipt, and drops a returned item, and wherein the returned item can be scanned, such as by bar code or RFID scan, or wherein image recognition is performed, or wherein physical characteristic recognition, such as weight recognition, is performed, to confirm the item returned). Additionally, a system in accordance with the invention may include one or more video cameras 20 that may focus on consumers throughout the store, and/or that may be directed to consumers when an item is scanned for mobile checkout, such as to check for or insure proper payment, such as from an on-board device wallet as referenced above, for the correct item(s).

Of course, those skilled in the art will appreciate that the aforementioned on-board device wallet may include a “personality wallet.” In such an embodiment, a smart phone or like device, such as automatically or by consumer interaction, may store her preferences over time. This personality information may form the basis for improved interaction with digital devices. In other words, a smart phone in such an embodiment may provide to digital devices the historical information of that consumer, such as to help with the shopping process, such as by improving the quality of recommendations/advice provided to the consumer as discussed throughout. Correspondingly, a retailer may be provided with a detailed, analytical history of in-store consumer preferences.

Likewise, a personality wallet may comprise a “loyalty program wallet.” For example, many consumers in prior art embodiments maintain individual “apps” that are specific to individual stores or retailers, certain of which apps track buying patterns and reward points, among many other things. This information may be used by retailers, such as for retailer-based loyalty programs.

Accordingly, the present invention increases consumer convenience, at least in that a consumer need not keep track of all individual loyalty programs. For a retailer point of view, access to a loyalty program wallet provides an enhanced profile of customers across multiple product categories. Such a multi-category profile improves buying recommendations, increases revenue for the retailer, and allows for expanded marketing programs to engage with the consumer.

For example, a consumer that has opted-in to a Wi-Fi network may, knowingly or unknowingly, accordingly provide information regarding the user's smart phone 12, such as the user's SIM information, MAC address, or the like, during the Wi-Fi opt-in process. Thereby, the user's phone may be tracked by any method known to those skilled in the art, including but not limited to GPS, triangulation via cellular towers or wireless nodes, or the like. Thus, when a user makes a purchase, the user's specific physical location may be known, and thereby in-store security cameras may look to the consumer as an item is being scanned. Thus, the present invention provides a system wherein video may be targeted to a consumer or an employee scanning an item based on the GPS signature, or like location signature, of a device making the scan. Further, the actions of the scanning consumer or the scanning employee may thus be immediately known, either locally or remotely, via the video. For example, IP video may be made available locally and remotely, such as at a central security hub, and may further be available to store manager or security personnel apps, such as may be carried around the store with a security guard.

The aforementioned real-time camera scan of a consumer scanning an item may be useful not only for theft prevention, but additionally in the treatment of “showrooming.” As used herein, showrooming is a process wherein a consumer may scan a particular item in a retail context, but only to check the pricing in the retail context against the on-line price of the item being scanned in-store. The method discussed herein, wherein a scan by a consumer indicates, via the opted-in Wi-Fi network, that the consumer is scanning the item, and wherein in-store cameras provide insight into the consumer's actions, allows for in-store personnel to take particular action with regard to showrooming. For example, in-store personnel may provide the consumer with a coupon, a discount, loyalty points, or the like, while the consumer is still or near in the aisle in which the showrooming scan occurred. This may incentivize the consumer to purchase the item in-store, or may, over time, incentivize the user to be loyal to the store and stop showrooming.

Those skilled in the art will further appreciate, in light of the discussion herein, that, due to the consumer's opt-in to the Wi-Fi network and the consequent availability of the identifying characteristics of the consumer's phone, store personnel and/or an in-store computing server and/or a remote monitoring system may know what the user is viewing on a phone. This provides store personnel with an indication that showrooming is occurring, or that a third party app on the user's phone is in use, or the like. Due to this ability, store personnel or the computing system may send a coupon or discount mechanism directly to the user's phone, such as to the aforementioned store-app on the user's phone. This coupon or discount may occur automatically from the store's computing system based on one or more business rules in the store computing system. Similarly, this provides an opportunity for remote or local customer service assistance. For example, if an item is scan, but no additional action is undertaken and the customer does not move for 90 seconds, an interrupt may be sent to the user's mobile device in which a remote customer service pop-up window may activate and ask the user, “May I help you learn more about ITEM?” Based on the user response, if any, a customer service transaction may occur.

For example, the computing system/server 20 illustrated in FIG. 1 may monitor the network, the phone activity of user's that have opted-in to the network, and/or in-store cameras. Thus, if a scan on a particular phone is sensed in conjunction with, for example, use of a third party app, the business rules may indicate that the computing system provide to the phone of the user engaging in the scan a discount or coupon, with or without intervention of store personnel.

Not only does the foregoing system, and the described method(s) performed therein, lower the likelihood of theft, but additionally the system and method(s) allow for in-store data tracking, purchase pattern tracking, enhanced EBR tracking, employee action tracking, customer tracking, loyalty tracking, and the like. More particularly, multiple ones of the foregoing records may be tied together over a pre-determined timeframe, such as wherein consumer purchase patterns may be gauged weekly, monthly, annually, and the like, such as for all consumers based on phone identifiers, or for consumers that are, for example, members of an in-store loyalty program.

Further, the computing system of a retail store or a retail chain may thus have a record of what phone each consumer uses, whereby providing unique information to each consumer's phone may be made easier. For example, a consumer in possession of an iPhone may be offered, while in-store, a mobile app, a coupon app, or the like, such as for that retail chain in which the user is then shopping. Further, it is known to the computing system that the particular consumer should be offered an iPhone application while in-store, rather than an Android application, by virtue of the fact that it is known that the consumer is using an iPhone. This information may be used, for example, in pattern analysis, as discussed hereinthroughout.

The computing system 20, or an associated remote computing system communicatively connected to the computing system 20, may engage in pattern/trend analysis. This pattern analysis may provide not only the aforementioned patterns and trending for one, multiple, loyal, frequent, or the like consumers, but may additionally provide the ability to do pattern analysis for particular employees, groups of employees, particular stores as among other stores in a retail chain, and the like. Accordingly, theft may be more readily prevented, and additionally information profiles, both for consumers and employees, may be created.

By way of non-limiting example, a particular store employee may give a $50 cash refund to a consumer who makes a return without a receipt. When this behavior is engaged in, a record is maintained of that employee's mobile scanning device identifiers, the transaction is associated therewith, and a video signature of the transaction may also be maintained by the computing system. If the same employee engages in the behavior a certain number of times, such as eight times over a six month span, the pattern analysis rules of the rules engine associated with the computing system 20 may indicate a pattern on behalf of that employee of participating in likely theft. Further, for each or all such instances, the computing system of the present invention can verify whether the consumer did, in fact, make the purchase in-store, such as by assessing the user's phone signature and a geo-synched in-store video signature. If it is indicated that for multiple ones of the aforementioned eight transactions the user did not actually make the purchase in the store based on transaction/video/phone records, this again increases the likelihood that the employee is actively participating in theft.

Further, the present invention may employ the aforementioned aspects to prevent “roundabouting.” As used herein, roundabouting indicates that an item has been taken off of a shelf, walked to the front of the store without purchase, and a consumer has endeavored to return the item to the store unpurchased and without a receipt. The system of the present invention, and as illustrated in FIG. 1, will recognize, based on the MAC address, SIM information, or the like of the consumer's smart phone, as well as the GPS signature of the phone, the in-store video signature of near-in-time transactions, etc., and the consumer's in-store actions, that the user did not, in fact, purchase the item prior to attempting a return.

Those skilled in the art will appreciate in light of the discussion herein that the performance of the system and method discussed herein may be improved by forcing consumers and employees to opt-in to the in-store Wi-Fi network. In order to stimulate this behavior, in-store opt-in may be required to enable mobile-check out or other in-store services or discounts, or the opt-in may be enticed, such as by being required on each trip into the store if the user intends to use a loyalty program while in-store.

In short, the present invention may thus allow for mobile checkout, and may link this mobile checkout to GPS (location) and video records in-store. Further, data from the consumer's device may be obtained and stored, and may be stored as or in conjunction with the user's activity data, GPS data, video data, and the like. Finally, this data may be tracked, and may be manipulated to obtain business intelligence that indicates trends for the pattern/trend analysis as directed by the business rules associated with the computing system 20 and as discussed above. Those skilled in the art will further appreciate that data, as that term is used herein, includes entry of the data, which may include user activity on a phone as read by the opted-in Wi-Fi network, the reading of a barcode, an NFC read, a Bluetooth read, a movement between departments within a store, and the like. As used herein, the term data also includes data schema, including data formatting, that may be employed with respect to accumulated, read or interrelated data. Further, data, as the term is used herein, may include created data rather than tracked or accumulated data. Such created data may include, for example, the integrity score discussed below. Data may further include atypical data in a retail context, such as biometrics data as may be tracked by a video, phone usage (such as a fingerprint read engaged in by a telephone app) and the like.

As discussed herein, video tracking and management services are currently provided for many large retail stores. Such providers of video management, as well as providers of other in-store applications typically employed in a retail context, may provide an open API library that allows third parties to “hook” applications into the open API system provided. Accordingly, the aspects of the present invention discussed herein may be hooked as “applications” into existing systems, such as to provide branded or white label mobile checkout apps, or the like. Further, in such a context, the aspects of the present invention may be associated with other applications that may additionally enhance the security of the transactions engaged in a mobile checkout context. For example, exterior video may be used in conjunction with the in-store video to provide an ability to track license plates, whereby a user may be tracked in-store, as discussed herein, and then may be tracked leaving the store and getting into a vehicle that is associated with a license plate which may provide for subsequent tracking and locating of the user.

FIG. 2 is a hierarchical diagram illustrating, at Step A, the generation of data regarding phone use, GPS, video surveillance, and the like, in-store. At Step B, this information is accumulated and may be interrelated. For example, at Step A, only phone and GPS data may be indicated, but such data may be linked together, or, GPS, phone, video, and use data may be generated by a particular mobile device and may be accumulated and related to that particular mobile device, at step B.

At Step C, data analysis that may indicate that a particular action is performed, such as based on business rules as applied to the interrelated data of step B. For example, at Step C, a shopper integrity score may be issued. The shopper integrity score may be an indication of the risk level of a particular consumer that is then in-store. The shopper integrity score may be numerical score, and/or may be shared with in-store personnel. As such, shoppers having a particular shopper integrity score, such as a particularly high shopper integrity score, may be invited to participate in particular programs, such as by receiving targeted advertisements, coupons, red carpet services, such as the unlocking of secure cabinets, or the like, either manually by in-store personnel or automatically by the computing system discussed in FIG. 1. Accordingly, systems and methods discussed herein may not only be used to increase the security of goods sold, the security of in-store transactions, and to target particular consumers, but may additionally be used to obtain and retain the most desired shoppers. For example, the presence of those desired shoppers may be assessed, and the store may endeavor to increase the level/amount of shopping and/or participation in loyalty programs by these most desired shoppers, such as based on the aforementioned shopper integrity score.

Of course, the shopper integrity score (SIS) may thus comprise a plurality of available information in combination. For example, a consumer's SIS may be calculated by combining publicly available data from credit history, criminal history, buying history, and/or social media endorsements, to thereby calculate a risk model that retailers can access to enable or prohibit certain mobile transactions, either in-store or on-line. The SIS may thus create a personalized profile that consumers maintain based on behaviors and history. The SIS may be dynamic, such as based on real-time or periodic data feeds. For example, the higher an SIS, the greater the access for the subject consumer to locked merchandise, targeted coupons, or unassisted mobile check-outs, by way of non-limiting example.

For example, a particularly high integrity scored user may walk past a locked cabinet that has therein high value items, such as electric shavers. As the user passes the locked cabinet, the user may be provided with a coupon, advertisement, alert, or the like, because of the user's high integrity score or loyalty score, or the user may be provided with such coupons, ads, or alerts simply because the user has been monitored as purchasing a great many disposable razors, or as having a preference for frequently purchasing electric shavers. Similarly, the cabinet may be unlocked, such as by an electronic key or token sent to the user's phone, wherein the user's phone engages with an NFC or Bluetooth transaction with the cabinet.

Further, certain users may receive not only high integrity scores, but additionally may receive valuable consumer scores. For example, such a user may not only have high integrity, but may additionally have high integrity in the frequent purchase of expensive items. All of that information may be accumulated in accordance with the present invention, and may indicate not only to a particular retailer but across different retailers that that consumer is one who should be targeted by those retailers as a valuable customer.

Of course, the present invention may make a variety of other scoring systems, security applications, and/or recommendation systems available to retailers and consumers. For example, the present invention may allow for a buyer's compliance app, which may allow consumers to provide real-time feedback to in-store security, such as for the purposes of reporting shoplifting events based on activities witnessed while shopping. This would allow shrinkage to be maintained at low rates, thereby enabling lower overall costs to retailers and consumers (e.g., in the event costs of shoplifting are typically at least partially passed on to consumers).

Similarly, the present invention may allow for a mobile fitting room compliance app. Such an app may allow consumers to scan their merchandise as they enter fitting rooms to “self-report” the number of pieces being tried-on. Consumers may receive coupons for on-going compliance, and retailers may thereby reduce the cost of labor while gaining insight into merchandise that enters fitting rooms versus conversion rates, such as purchases at point of service. Such an app, in combination with real-time access to in-store inventories (style, color, size availability, etc.), may enable significantly enhanced self-service buying. Furthermore, this may allow so-called “out of stocks” to be mitigated, at least in part because consumers can order merchandise they want to purchase but which is not available at the store, based on this insight into and access to the supply chain and ability to ship direct, all via mobile device.

By way of more particular example, using the disclosed systems and methods, a user may try on a particular brand of sneaker in a size 10.5. The user may, based on this try-on, assess that the user needs the shoe in a size 11—however, there may be no size 11 on the shelf from which the user took the shoes. As such, the user may scan the size 10 sneaker box, and may receive, upon the scan and from the app discussed herein, a pop-up or like inquiring and interactive user window that asks, “You have scanned a size 10 men's ‘MegaSneaker.’ What is your inquiry regarding this item: Size? Color?” Of course, other inquiries relevant to particular items may also be provided. The user may select “Size,” and may select, such as via a drop down menu, a size 11. The user may then be informed, “Yes, your selected item is in stock at this store. Please see a sales associate for assistance.” Or, for example, the user may be informed, “We're sorry, your selected item is not in stock at this store. However, 3 local stores do have your item in stock. Would you like information regarding those locations? If not, would you like to order your selected item online?” Similarly, the pricing of the item from the online store of the retailer may be, at the direction of the user or automatically, compared against the price at other online or brick & mortar locations, and the use may be provided with this information and/or the ability to order from other retailers as well.

The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of providing mobile checkout, comprising:

obtaining, via an opt-in to an in-store wireless network, of consumer device data regarding a plurality of consumer mobile devices, the consumer data comprising device use data, prior purchase data, and location data;

receiving video surveillance data related to at least one consumer having the consumer device data;

interrelating, from at least one non-transitory computer-readable medium storing at least the consumer device data and the video surveillance data, of at least the consumer device data and the video surveillance data by at least one computing processor; and

applying, by the computing processor, of a plurality of business rules to the interrelated datas to enable at least the mobile checkout, wherein the mobile checkout includes a purchase of at least one in-store item via the consumer device associated with the purchasing one of the at least one consumer.

2. The method of claim 1, wherein said applying further comprises applying the business rules to the interrelated datas to enable issuance of a shopper integrity score.

3. The method of claim 1, wherein the receiving video surveillance data is triggered by an indication received from the consumer device.

4. The method of claim 1, wherein the consumer data comprise exception based reporting.