Abstract:
A system and method are provided for a display space allocation and costing system, allowing direct access by companies or individuals seeking a place to sell goods.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application claims the benefit of U.S. Provisional Patent Application No. 61/987,191 filed May 1, 2014, the disclosure of which is incorporated herein by reference in its entirety. 
     
    
     BACKGROUND OF THE INVENTION 
     Field of the Invention 
       [0002]    This invention relates to a system for the allocating and costing of retail display space. Despite the popularity of catalog and Internet shopping, brick-and-mortar stores remain very important, with hundreds of millions of square feet of display space installed. Product placement has become an important science for manufacturers, distributors, and retailers. For example, smaller brands, regional brands, and gourmet brands might occupy a top shelf, with the second and third shelves having best-sellers, national brands, and high-margin products, and the bottom shelf having bulky and oversized products. While a store manager would recognize that he must carry certain items, for example, a grocer would need to carry staples such as milk and bread, as well as certain brands of laundry detergents, the retailer still has great latitude in determining which brands and products will receive shelf space in his store. This invention describes a system allowing retailers to rent a percentage of the shelf space in their stores to interested parties, which could be wholesalers, manufacturers, or speculators. The shelf space made available for rental is described by location within the store, width, depth and height of retail space available, vertical position of shelf within a stack of shelves, etc. 
         [0003]    It is therefore an object of the present invention to provide a hardware and software platform, including analytical model and data sets, for allocating and costing display space. 
       BRIEF SUMMARY OF THE INVENTION 
       [0004]    The above objects and further advantages are provided by the methods and systems for allocating and costing retail display space. 
         [0005]    According to one aspect of the present invention a system and method are provided for the allocation and costing of retail display space. 
         [0006]    It is a further object of the present invention to disclose one embodiment of a hardware interface for a display space allocation and costing system, in which the hardware interface provides a shelf product monitor system. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0007]    The invention will be described in further detail below and with reference to the attached drawings in which the same or similar elements are referred to by the same or similar reference numerals, in which: 
           [0008]      FIG. 1  is a block diagram of a display space allocation and costing system for the trading of retail shelf space; and 
           [0009]      FIG. 2  is a block diagram of one embodiment of a hardware interface for the display space allocation and costing system. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0010]    The present invention broadly comprehends a display space allocation and costing system allowing retailers to list a percentage of their store&#39;s shelf space on the system, while manufacturers, wholesalers, or speculators can bid on leasing the display space. 
         [0011]    Reference will now be made in detail to implementations of the invention, examples of which are illustrated in the accompanying drawings. 
         [0012]      FIG. 1  illustrates an embodiment of a display space allocation and costing system  100 , in which proprietary hardware and software uses statistical and behavioral metrics to make recommendations to users. In this embodiment, users of the system, which will include both retailers  101  who have ownership or control of retail display space, as well as product owners  102 , middle-men, speculators, or others who are interested in leasing display space from retailers  101 . The users, retailers  101  and product owners  102  use the display space allocation and costing system  100  by utilizing user interface  110 . 
         [0013]    User interface  110  communicates with and controls a number of hardware and software components including an analytics engine (analytics front end  210  and analytics engine back end  220 ), risk analysis engine  300 , placements engine  400 , bidding/auction engine  500 , hardware interface  170 , real-time data store  140 , and data warehouse  160 . User interface  110  also communicates with data look-up  121  and user hash key module  125 . user interface  110  includes the visual interface that is displayed to the user, and also includes user data capture  145 , which is a client-side ‘beacon’ script that monitors as the user moves through the system, with user hash key attached, and is acquired securely by each aspect of the system flow. This process enables us to track everything that the user does in the system, furthering the system&#39;s ability to make better recommendations for the users, and to provide better security. 
         [0014]    A virtual private network (VPN) accessible API adapter layer  120  facilitates the communications between user interface  110  and analytics engine front end  210 , risk analysis engine  300 , placements engine  400 , bidding/auction engine  500 , and hardware interface  170 . As understood to one of ordinary skill in the art, API adapter layer  120  is an interface that allows binary data from a foreign system to run on a host system. System calls for the foreign system are translated by API adapter layer  120  into native system calls for the host system. In conjunction with libraries for the foreign system, this will allow the host system to run binaries of the foreign systems. 
         [0015]    Additional application programming interfaces (APIs)  180  are provided, including APIs that handle miscellaneous third party data and validation services; profiling; decision-making for the allocation and costing system; risk management; incident management; credit worthiness. The APIs also handle dynamic creation and stacking of new layers, for example, extending the capabilities of display space allocation and costing system  100  by allowing it to work with a third-party&#39;s system, so that the two systems together create a new function that is defined as an additional layer in the system that is enabled by additional application programming interfaces (APIs)  180 . Additional APIs  180  communicate with user interface  110  via other APIs data path  117 . 
         [0016]    A data abstraction layer  130 , as is understood to one of ordinary skill in the art, is an application programming interface that unifies communication between user interface  110  and the databases, real-time data store  140  and data warehouse  160 . As is understood by one of ordinary skill in the art, the massive amounts of data available to complex systems favor the use of a real-time data store in conjunction with offline data warehousing, with different storage practices for the data stored in the different areas, correlating to the amount of times per day that data needs to be accessed, as well as by the number of people requiring access to particular data. For example, the price of a unit of a product, or the fee for slotting a specific space, would be an example of data requiring real-time storage. The data contained in a user profile, which is not factored and used in the system&#39;s dynamic decision-making, is an example of data that can be stored in a data warehouse. 
         [0017]    Real-time data store  140  receives data originating from multiple sources that pertain to the allocation and costing of retail display space. The data is integrated which can include known techniques of data scrubbing, resolving redundancy and checking against business rules for integrity. One source of data is data look-up  121 , which communicates with real-time data store  140  via real-time data store to data look-up module data path  132 . Another source of data is from data abstraction layer  130  and API adapter layer  120  via API adapter layer to data abstraction layer data path  122 . 
         [0018]    After processing in real-time data store  140 , data is passed to an extract-transform-load (ETL) engine  150  via real-time data store to ETL engine data path  127 . 
         [0019]    ETL engine  150  extracts data from the various data sources input into real-time data store  140 , transforms the data for storing it in proper format or structure for querying and analysis, and loads it into data warehouse  160  via ETL engine to data warehouse data path  128 . The function of an ETL engine is well-known to one of ordinary skill in the art. 
         [0020]    Data warehouse  160  is a backend database storage layer/system that contains much greater amounts of data than the real-time data store, with the data arranged into hierarchical groups (“dimensions”), facts and aggregate facts. Data warehouse  160  is a central repository of integrated data that stores current and historical data relevant to the allocation and costing of display space. It is used to create trending reports that will serve both the retailers  101  and product owners  102 . Data warehouse  160  communicates to data look-up  121  via data abstraction layer  130  and data warehouse to data look-up module data path  131 . Data warehouse  160  also communicates to analytics engine back end  220  via data warehouse to analytics engine data path  129 . 
         [0021]    User interface  110  includes a number of components, including user data capture module  145 , display space router  155 , space evaluation flow module  165 , data driven page rendering module  168 , space offer builder admin module  169 , and display space evaluation engine  175 . 
         [0022]    Space evaluation flow module  165  includes premium space selection module  166 , alternate space selection module  167 , and data driven page rendering module  168 . The user is presented with choices, with premium space selection module  166  providing a preferred choice, and alternate space selection module  167  providing an alternate choice. In one embodiment, display space allocation and costing system  100  will charge transaction fees relating to the leasing of display space, and if it can increase the arbitrage for the users, it can charge larger transaction fees. 
         [0023]    Hardware interface  170  includes a software development kit (SDK) interface. In a preferred embodiment, an open SDK is employed, allowing various developers to build hardware and software applications on top of the proprietary display space allocation and costing system  100 . External physical devices&#39; access to display space allocation and costing system  100  is supported via a secured internet protocol security (IPSec), with a virtual private network (VPN) accessible API adapter layer  120 . Hardware interface  170  communicates bidirectionally with display space evaluation engine  175  of user interface  110 , via API adapter layer  120  and hardware interface data path  114 . 
         [0024]    The analytics engine, as noted above, includes both an analytics engine front end  210  and an analytics engine back end  220 , which communicate with each other via analytics engine internal bus  116 . The analytics engine provides a system to organize, process and prepare all internally- and externally-available data for use in the display space allocation and costing system  100 . The analytics engine is used to perform a variety of tasks for the user, such as identifying sell-through timing (the length of time a product sits on the shelf), which products sell best in a particular neighborhood, the price paid on average for a product in a particular neighborhood, and the number of free cases needed to be given to a retailer to lower the retailer&#39;s overall cost. Analytics engine front end  210  communicates bidirectionally with user data capture module  145  of user interface  110 , via API adapter layer  120  and analytics engine data path  115 . 
         [0025]    Placements engine  400  is a deterministic system incorporating all known data points to provide a best-placement solution for a product onto a given shelf space. Data points for a given shelf space include location of the store, location of the shelf space within the store, dimensions and height of the shelf space, height above the floor, and the length of time a lease is available. Placements engine  400  is used to find a space for a product, or conversely, to find a product to fit a particular space based upon specific products that consumers are purchasing from similar stores in similar areas. Placements engine  400  communicates bidirectionally with space evaluation flow module  165  of user interface  110 , via API adapter layer  120  and placements engine data path  112 . A data append function allows for additional data retrieved by placements engine  400  to be added to space evaluation flow module  165 . For example, if a product owner  102  wants to place an item in a store located in New York, the data is sent to placements engine  400 . Placements engine is not limited to acting on this data, however, but can instead suggest a different location or course of action, for example based on data that the item might sell better in a different location. 
         [0026]    Risk analysis engine  300 , described in greater detail below, is a deterministic peer-influenced system incorporating internal and external data sources to perform validation, fraud check, and risk analysis for users of display space allocation and costing system  100 . This stratified application accounts for both risk of network peers and risk of transaction. Network peer ranking are based on offline information such as past bankruptcies, if any, whereas risk of transaction is based with in-store concerns such as lack of sell-through or lack of consumer traffic. Risk analysis engine  300  communicates bidirectionally with display space router  155  of user interface  110 , via API adapter layer  120  and risk analysis engine data path  111 . In this manner, risk analysis engine  300  accesses user data that has been generated and stored from other API engines. 
         [0027]    Bidding/auction engine  500  provides a real-time bidding system for commoditizing the shelf space. It helps determine the price and relative overall value, including sell-through proportions, enabling the user to intelligently bid and lease space. Bidding/auction engine  500  communicates bidirectionally with space evaluation flow module  165  of user interface  110  via API adapter layer  120  and risk analysis engine data path  113 . A retargeting integration function, similar to the data append function described for placements engine  400 , allows bidding/auction engine  500  to recommend a course of action that might dynamically modify the flow of the user&#39;s choices through the system. For example, display space allocation and costing system  100  has the ability to suggest stores in a different geographic location than the one product owner  102  inputs into the system. 
         [0028]    User data capture module  145  receives communication from the users of the display space allocation and costing system  100 . For example, user data capture module  145  can collect details of display spaces, and can query retailer  101  about annual sales. Retailer  101  communicates with user data capture module  145  via retail user to user data capture module data path  118 . Product owner  102  communicates with user data capture module  145  via products owner to user data capture module data path  119 . As is understood by one of ordinary skill in the art, retail user to user data capture module data path  118  and products owner to user data capture module data path  119  can be a connection via the Internet, via a smartphone application, via a hardwired line, etc. 
         [0029]    User data capture module  145  receives communications from data look-up  121  via data look-up module to user data capture module data path  133 . Data about the user&#39;s previous purchases is made available via this path. User data capture module  145  also communicates with display space router  155 , via user data capture module to display space router data path  136 . 
         [0030]    Data look-up  121  is an object space provided in memory that serves as a security buffer preventing users from ever having direct access to data warehouse  160 . Data warehouse  160  pushes data into data look-up  121  via unidirectional data warehouse to data look-up module data path  131 . Data look-up  121  creates global identifiers that are used throughout display space allocation and costing system  100 . 
         [0031]    As part of a security protocol, retailer  101  And product owner  102  are provided with a user hash key via user hash key module  125 , which generates the hash key and verifies it as unique via data warehouse  160 . The hash key is a security token provided to a user via their first interaction with display space allocation and costing system  100 . User hash key module  125  communicates with data look-up  121  via data look-up module to user hash key module data path  124 . User hash key module  125  communicates the hash keys to the users via user hash key module to user data path  126 . 
         [0032]    Display space router  155  receives requests for a display space from product owner  102 , communicating with placements engine  400  and display space evaluation engine  175 . Display space router  155  returns display space requests to the retailer  101 . Display space router  155  communicates with space evaluation flow module  165 . Specifically, display space router  155  communicates with premium space selection module  166  via display space router to premium space selection module data path  137 , and it also communicates with alternate space selection module  167  via display space router to alternate space selection module data path  138 . 
         [0033]    Data driven page rendering module  168  dynamically provides elements of a user-experience based on the known data in the system and at the run-time of the user experience. It overlaps with space evaluation flow module  165 . All pages on the system are assembled from database calls, rather than being static files of information. Data driven page rendering module  168  receives communications from data abstraction layer  130  via data abstraction layer to data driven page rendering module data path  134 . 
         [0034]    Space offer builder admin module  169  is utilized by retailer  101  to add available retail space to display space allocation and costing system  100  and to administrate the listing of that entry. Space offer builder admin module  169  receives communications from data abstraction layer  130  via data abstraction layer to space offer builder admin module  123 . Space offer builder admin module  169  communicates with space evaluation flow module  165  via space offer builder admin module to space evaluation flow module data path  139 . 
         [0035]    Display space evaluation engine  175  provides a final evaluation for the best choices presented to the user. Display space evaluation engine  175  communicates bidirectionally with premium space selection module  166 , via space evaluation flow module to premium space selection module data path  141 . 
         [0036]    In addition to the direct connections shown in  FIG. 1 , indirect communications are also common. For example, it has been described above that a user&#39;s bidding history collected by bidding/auction engine  500  is passed to display space router  155  via API adapter layer  120  and risk analysis engine data path  111 . However, the data can also be accessed by risk analysis engine  300  via a circuitous path through real-time data store  140 , data warehouse  160 , data abstraction layer  130 , data look-up module  121 , user interface  110 , and API adapter layer  120 . 
         [0037]      FIG. 2  shows an example of a shelf product monitor system  600  that is installed in a retail establishment. This is one embodiment of hardware interface  170  as shown on  FIG. 1 . 
         [0038]    Small retailers who maintain product stores have no method to track inventory or customer acquisition information via a web-based or mobile-based product. UPC and Nielsen data compilations are available post-monthly for stores that have a modern point-of-sale system that supports such a feature. However, independent store owners have no way to determine how many people browsed by a specific shelf, in a given month, or on a particular day. A store owner could benefit from such data, if available, and additionally would benefit by learning if customers picked up a product from the shelf, examined it and returned it to the shelf without purchase. This type of data would aid a retailer in making various determinations, such as deciding which products to reorder, or deciding to physically reposition an item within the store for added exposure. Historically, such data has only been available to very large enterprise stores that hire a consultant who may provide a human to monitor this information. No service exists to allow small and medium retailers to have this same ability, and certainly not in real-time via a web-based or mobile-based application. 
         [0039]    Shelf product monitor system  600  includes both a real-time on-the-shelf unit  605  and a central in-store server  650 . 
         [0040]    Real-time on-the-shelf unit  605  incorporates a microprocessor and memory, as well as interfacing with either a self-contained or weight sensor  610 , UPC scanner/detector  615 , privacy-safe video camera  620 , inventory tracker  625 , and wireless interface  630 . The unit can sit unnoticed below a store shelf, out of the view of the customer. 
         [0041]    Weight sensor  610  provides an indication of how much product is on a shelf, as well as whether a customer has lifted a product from the shelf, e.g., for inspection. 
         [0042]    UPC scanner/detector  615  provides for monitoring the presence of inventory. 
         [0043]    Privacy-safe video camera  620  can provide the shelf product monitor system  600 , and in turn the display space allocation and costing system  100 , with data such as the amount of time that a customer spends at a shelf inspecting the product being displayed, and can employ fuzzy logic techniques to determine demographics data, such as age-range, gender, race, etc. of the customers showing an interest in the product on display. 
         [0044]    Inventory tracker  625  is a software component that is stored in the memory of, and that is executed by the microprocessor of, real-time on-shelf unit  605 . Inventory tracker  625  accepts data from components such as weight sensor  610 , UPC scanner/detector  615 , and privacy-safe video camera  620 , determining product totals, which assists a user in tracking overall product sales as well as shrinkage. 
         [0045]    Wireless interface  630  allows the real-time on-the-shelf unit  605  to communicate with the central in-store server  650 . 
         [0046]    The memory includes a program that runs on the microprocessor, monitoring and processing data received from weight sensor  610 , UPC scanner/detector  615 , privacy-safe video camera  620 , and that transmits the data via wireless interface  630  to central in-store server  650 . 
         [0047]    Central in-store server  650  communicates with the real-time on-the-shelf unit  605  via its own wireless interface  655 . Central in-store server  650  also incorporates data collection software  660 . 
         [0048]    The shelf product monitor system  600  communicates with the display space allocation and costing system (not shown, appears as element  100  on  FIG. 1 ) via inventory API via a virtual private network  675  and inventory API interface  670  (which appears as Other APIs  180  on  FIG. 1 ). Thus, data gathered by the real-time on-the-shelf unit  605  can be tracked by its self-contained microprocessor, can be transmitted wirelessly to central in-store server  650 , and then sent via secured VPN tunnel  675  to the inventory API service  670  of display space allocation and costing system  100 . Via the API service  670 , data gathered by the real-time on-the-shelf unit  605  can be provided to the retailer or to a third party, via mobile application, email, or web notification, as selected by the user. 
         [0049]    The system of the present invention has been described above and with reference to the attached drawings; however, modifications will be apparent to those of ordinary skill in the art and the scope of protection for the invention is to be defined by the claims that follow.