Source: http://www.google.com/patents/US20060010027?dq=7222078
Timestamp: 2017-05-26 10:22:22
Document Index: 685862113

Matched Legal Cases: ['art 23', 'art 23', 'arts 23', 'arts 23', 'art 23', 'art 43']

Patent US20060010027 - Method, system and program product for measuring customer preferences and ... - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsA method, system and program product for determining movement data of a customer or customers in a store to analyze customer decisions and optimize product presentation and customer service in response to the analysis. The movement of customers through a store may be correlated with various environmental...http://www.google.com/patents/US20060010027?utm_source=gb-gplus-sharePatent US20060010027 - Method, system and program product for measuring customer preferences and needs with traffic pattern analysisAdvanced Patent SearchTry the new Google Patents, with machine-classified Google Scholar results, and Japanese and South Korean patents.Publication numberUS20060010027 A1Publication typeApplicationApplication numberUS 10/887,748Publication dateJan 12, 2006Filing dateJul 9, 2004Priority dateJul 9, 2004Also published asWO2006017132A2, WO2006017132A3Publication number10887748, 887748, US 2006/0010027 A1, US 2006/010027 A1, US 20060010027 A1, US 20060010027A1, US 2006010027 A1, US 2006010027A1, US-A1-20060010027, US-A1-2006010027, US2006/0010027A1, US2006/010027A1, US20060010027 A1, US20060010027A1, US2006010027 A1, US2006010027A1InventorsPaul RedmanOriginal AssigneeRedman Paul JExport CitationBiBTeX, EndNote, RefManPatent Citations (4), Referenced by (50), Classifications (21) External Links: USPTO, USPTO Assignment, EspacenetMethod, system and program product for measuring customer preferences and needs with traffic pattern analysis
DESCRIPTION OF THE INVENTION [0052] The following description, and the figures to which it refers, are provided for the purpose of describing examples and specific embodiments of the invention only and are not intended to exhaustively describe all possible examples and embodiments of the invention. [0053] Referring now to FIG. 1, the path 11 of a customer in a store 15 having products 17 arranged on shelves 19 in aisles 21 is shown. In a typical scenario the customer path is from the store entry 10 where a cart 23 is obtained by the customer, to the checkout 12. The customer pushes a cart 23 through the store 15 to evaluate products 17 placed on the shelves 19 (shown in FIG. 5) of aisles 21. The products 17 are illustrated on an aisle for emphasis, but they are distributed along all the aisles 19 in this example, perhaps on shelves (shown in FIG. 5). Observing this path 11 may yield at least three types of path data, the location of the route taken by the customer; the time of the route and the time spent at various locations throughout the route. The shopper may linger at locations in the aisles 21 where products 17 of interest to the customer are located. [0054] In the prior art stores would attempt to simply attract customers to higher profit margin items so that the store can make a reasonable overall business margin. This was done using common sense, an example of this might be the fact that higher priced cereal may be placed at eye level, and the low priced, low margin cereal may be on the bottom shelf. These strategies have traditionally helped stores increase their revenue and margins. A careful analysis of path data and traffic data however, can reveal a better profile of customer psychology in response to environmental conditions or sales terms and reveal appropriate product inducements that may be placed at different locations in the store to induce increased traffic for increased product sales. [0055] In one embodiment of the present invention the paths taken by customers may be observed manually by an observer 29 situated at a vantage point that allows him to observe customer traffic and record and correlate it manually as well. Alternatively a group of cameras 31 could be placed at different locations in the store and the customers tracked by a display (not shown) or by connecting the cameras to a central data processor 100, a computer, and tracked with the use of facial recognition software. In this embodiment a new customer face could be recorded on the data processing unit 100 upon entry to the store by a first camera and, much like the preferred embodiment, the path of a customer could be implied from the order of the sequence of when a customer is recognized by subsequent cameras. The time spent lingering in an area could be calculated by subtracting the time at which a customer face was recognized at a first camera, from the time at which the face is recognized at a second camera. [0056] Referring now to FIG. 2, the paths of a plurality of customers 11A, 11B and 11C may be correlated to determine traffic patterns of customers. For example, locations where customers disproportionately linger in proximity to products may be determined and are termed herein hot spots shown at 33, the size of the circle being proportionate to the average amount of time spent by customers lingering there. A hot spot, combined with data reflecting few actual purchases at that location, may indicate that an item is not being purchased, it may indicate a problem because a customer is lingering over the product deciding whether to purchase it. Conversely, locations in proximity to products that customers disproportionately avoid are termed cold spots, shown at 35 by way of example. A cold spot, combined with data reflecting many actual purchases at that location, may indicate a quick decision to buy, meaning that the price might be increased on that product. This data may be calculated for all products in the store. In this way the user can determine whether it would be advisable to modify item placements, offer discounts to increase sales, and other strategies such as offering a loss leader to attract traffic and increase sales of other products that are nearby. The path data may also reveal locations where a disproportionate number of customers reverse direction in an aisle, termed turn spot, shown at 37. As indicated above, such traffic data can be used for several purposes. With respect to product sales, traffic data may be correlated to actual product sales to identify the success or failure of different product inducement strategies. Individual path and traffic data may indicate problems with particular areas of a store or to correlate traffic behavior with proposed sales variables, factors thought to influence buying decisions, such as product placement in the store, weather and economic data. [0057] In the preferred embodiment the path data is inputted into a data processing system, referred to generally as a computer and an optimization report correlating path data and product sales is generated by the computer with appropriate programming. Ideally the data will be recorded directly from the electronic tracking device to obviate the need for any human data collection or calculation. [0058] In the preferred embodiment RFID tag readers 41 (also indicated by the letter R) are disposed throughout the store, at the ends and middle of aisles. Preferably the tag readers are placed within about six feet of each other, preferably at the ends of each aisle. An RFID tag 43 is affixed to shopping carts 23 provided for customer use, but may be affixed to any other shopping implement provided by the store for customer use, such as a personal digital assistant 43A, an implement to grasp products 43B or a small vehicle to transport the customer 43C. Newer RFID tag readers have become an affordable tracking solution. RFID technology is known to those skilled in the art. Tracking shopping carts 23 with RFID technology allows a similar utility to tracking vehicles on a toll road. In this case the tracking vehicles are deployed within the internal environment of a store, however. This technology allows real-time tracking of customers within a store which facilitates resource allocation and also allows trend and optimization analysis to be performed on aggregate data. [0059] Placing RFID readers at or near the point of sale, using a cash register at the checkout location for recording the sale, or a similar point of sale device, and integrating the system into an RFID point of sale device allows a customer path to be related to the exact products purchased by the customer traveling that path. [0060] FIG. 3 shows an exemplary RFID system of the prior art. A typical RFID system has three components, RFID tags 43, also referred to as transponders, that are electronically programmed with information concerning the product to which they are attached; readers or sensors 41 to interrogate the tags, also referred to as antennas; and 100 a computer or server on which software records the tags as they are read. The information contained on microchips in the tags affixed to products is read using radio frequency technology. RFID tags are already fairly ubiquitous: they are used on products, on ID badges and by commuters on toll roads that pass readers that pick up a unique signal from an RFID tag placed on each car. [0061] The tags used in RFID technology are preferably un-powered, the power to read the tags comes from the reader. The tags are the backbone of the technology and come in all shapes, sizes and read ranges including thin and flexible labels which can be laminated between paper or plastic. An RFID system creates an automatic way to collect information about product and path data, the location and time. [0062] FIG. 4 shows use of an RFID tag reader as used in the preferred embodiment of the present invention, in conjunction with the RFID tag system of FIG. 3. A tag 43 is placed on a container, here a shopping cart 23. [0063] As shown in FIG. 5 the shopping cart 43 can be read by typical tag readers 41 (also shown by the letter R) when the tag and tag readers are in close proximity, about six feet, generally disposed at the ends and in the middle of aisles 21 of the store 15. In one method when a customer moves a cart past a tag reader 41A and path data is recorded, the path 11 shown in direction of arrows, which includes the location of the tag reader and may include other path data such as the time of day and the date. The duration of how long a tag is read by a tag reader can be used to indicate how long a customer lingered just next to that tag reader. When the user passes a second tag reader 41B it may be implied that the customer moved in a path from the location of the first tag reader to the location of the second tag reader. The time of the first read may be subtracted from the time of the second read to calculate the time spent in the area between to two tag readers. [0064] The preferred embodiment of the present invention also includes the data collection process that tracks customer paths using RFID technology, correlates that data to the products purchased, and an optimization report generated by computer system can be used to optimize the stores product sales, increase margins and remove impediments to a customer buying a product. [0065] For example, by knowing exactly where the highest volume of customers travel at a particular time on a particular day, or by knowing based on the weather and historical data, such customer activity as when the customers will be going to the ice-cream or winter coat aisle can be predicted. The store can put higher margin products at that location and increase its revenues. It is a sales axiom that the more customers you reach the more product you will generally sell. This may be of great advantage over previous methods for collecting sales data. Without this information it is more difficult to optimize sales. [0066] FIG. 6 is a flow chart of an embodiment of the method of the present invention, which may be executed by program product executed on a data processing apparatus. A store customer is tracked to obtain path data about that customer. The path may identify an impediment to product sales, such as lingering in an area near a product that requires assistance. An appropriate remedial action is then implemented, such as sending an employee to assist the customer. Tracking a plurality of customers to obtain their path data and correlating the path data of the plurality of customers results in a traffic pattern for customers. A sales impediment, such as low sales of some products due to environmental conditions may be identified by the traffic pattern in an optimization report. The user may then implement remedial action or offer an inducement to product sales based on the traffic pattern. Further tracking and observation of any change in the traffic pattern may be used to test the success of the remediating action or the sales inducement. [0067] The Path data or a traffic pattern may be correlated to increase sales, to remediate sales impediments or to facilitate sales by using product inducements. Path data may be used in real time to remediate impediments purchasing products. For example the path data of a customer of time and location may be used to send an employee to the location where a cart has been sitting for too long a time to determine if the customer needs assistance. The path data of location may be used to send a store asset, such as an employee or a forklift to locations where a customer will ultimately need assistance, such as purchasing lumber or goods that need to be moved, prepared or packaged, such as lumber, paint or loose items such as nails. [0068] Real time traffic data is the correlation and averaging of a plurality of paths taken by customers. Traffic pattern information can be used to predict path behavior and anticipate the need to allocate store assets, such as employees, to a particular location in the store. [0069] Traffic pattern information can be obtained and used for any store having a plurality of customers, with products located at different locations in the store. It includes the steps of recording the path data of a plurality of customers, path data includes all attributes solely related to a customer's path, such as location of a portion of the path taken by a customer in the store; the amount of time spent by a customer at a location in the store; the time of day a customer spends at a location in the store; or the date a customer spends at a location in the store. The path data for a plurality of customers is then statistically correlated to determine a customer traffic pattern of the store. This statistical correlation may be as straightforward as averaging the paths to indicate a predominant path. [0070] The observation and recording can be implemented by electronically tracking the path taken by a customer in a number of ways. There are several tracking technologies available, as detailed above, but it is preferred to use an RFID tracking device of FIG. 4, where the RFID tag is placed on a shopping implement, generally a shopping cart, that is moved by one or more of the plurality of customers. [0071] Tags and tag readers may be provided, in the preferred embodiment the tags and tag readers are RFID tags and RFID tag readers. [0072] In the preferred embodiment path data is entered into a data processing device, a computer and calculated by the computer to generate an optimization report. The optimization report is a report that correlates the traffic pattern with any proposed variable relating to the sale of a product, such as an environmental variable or the price of a product. [0073] Optimization reports may be used to suggest appropriate remedial measures to be taken to remove impediments to sales, or to suggest affirmative inducements to product sales. The optimization report may further be used to test for sales impediments that are thought to have been corrected, or to see whether sales inducement strategies are successful. [0074] For example, correlated information can be used to correlate disproportionate lingering next to a particular product with sales of that product. This might indicate something as trivial as poor lighting in an aisle. This might also indicate that although the product is attractive to customers it might be too expensive. Remedial measures might include a sale, a discount coupon, or only offering it during times of the year when customers will likely be willing to spend the full amount. Other products themselves may be used to alter traffic patterns, such as the loss leader described above as one example. [0075] Path data or a traffic pattern may be correlated to increase sales, to remediating sales impediments or to facilitate sales by using sales inducements. Path data may be used in real time to remediate impediments purchasing products. For example the path data of a buyer of time and location may be used to send an employee to the location where a cart has been sitting for too long a time to determine if the buyer needs assistance. The path data of location may be used to send a store asset, such as an employee or a forklift to locations where a buyer will ultimately need assistance, such as purchasing lumber or goods that need to be moved, prepared or packaged, such as lumber, paint or loose items such as nails. [0076] A more sophisticated optimization report might compare an aisle of products based on calculating the profit margin of products in that aisle, the quantity of products actually sold in that aisle and the net revenue made from that aisle. A product inducement strategy might be implemented by placing an inexpensive impulse item in the aisle to cause the customer to linger longer near higher profit margin items. Am alternative exemplary product inducement strategy might be to provide information through a communications device, such as a video display 51 or dispense a related discount coupon 53. [0077] The present invention relates to methods, systems and a program product for use with a computer, also referred to as a data or digital processing system herein. [0078] In a preferred implementation, the computer is embodied in a data processing system such as that depicted as 100 in FIG. 7. FIG. 7 is a block diagram of an exemplary computer system for implementing the methods of the present invention. A general purpose computer 100 implements the method of the present invention, wherein the computer housing 102 houses a motherboard 104 which contains a CPU 106, memory 108 (e.g., random access memory (RAM), dynamic ram (DRAM), static RAM (SRAM), synchronous DRAM (SDRAM), flash RAM, read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), or any other desired memory), and other optional special purpose logic devices (e.g., application specific integrated circuits (ASICs)) or configurable logic devices (e.g., generic array of logic (GAL) or reprogrammable field programmable gate array (FPGA)). The computer 100 also includes one or more input devices (e.g., a keyboard 122 and a mouse 124) and a display card 110 for controlling a monitor 120. In addition, the computer system 100 further includes a floppy disk drive 114; other removable media devices (e.g., a compact disc 119, a tape, and a hard disk 112, or other fixed, high density media drives, connected using an appropriate device bus (e.g., a small computer system interface (SCSI) bus, an enhanced integrated device electronics (IDE) bus, or an ultra direct memory access (DMA) bus). Also connected to the same device bus or another device bus, the computer 100 may additionally include a compact disc reader 118, a compact disc reader/writer unit (not shown), or a compact disc jukebox (not shown). Although compact disc 119 is shown in a CD caddy, the compact disc 119 can be inserted directly into CD-ROM drives which do not require caddies. In addition, a printer (not shown) also provides printed listings of any of the inputs, intermediate values, and outputs associated with the models of the methods of the present invention. Other peripheral devices may include additional computer systems via local or wide area networks and the Internet, and which may further include such peripheral devices as printers, facsimile machines, scanners, network connection devices, tape drive units, etc. [0079] The system includes at least one computer readable medium used for storing computer instructions, program product. Examples of computer readable media are compact discs 119, hard disks 112, floppy disks, tape, magneto-optical disks, PROMs (EPROM, EEPROM, Flash EPROM, etc.), DRAM, SRAM, SDRAM, etc. Stored on any one or on a combination of computer readable media, the present invention includes software for controlling both the hardware of the computer 100 and for enabling the computer 100 to interact with a human user. Such software may include, but is not limited to, device drivers, operating systems and user applications, such as development tools. Such computer readable media further includes the computer program product of the present invention, in accordance with the description above or any of the examples below. [0080] The computer code devices of the present invention can be any interpreted or executable code mechanism, including but not limited to scripts, interpreters, dynamic link libraries, Java classes, and complete executable program which when executed, perform the methods of the invention. The method can be implemented as a software program using a variety of programming languages, such as Simula, C++, Visual Basic or Java, by programming techniques known to those of skill in the art. Thus, the present invention may be implemented on a machine, such as the general purpose computer 100, that transforms data (representing path or traffic data and relating them to proposed marketing variables) to achieve a practical application. [0081] In conjunction with the data processing system 100, the undertaking as described here is implemented by successively adding increasingly detailed customer path information to a database which may be retained on computer-readable media of the system. The data is processed by one or more programs executed by the CPU 106 which are designed to analyze the proffered data against various models and previously stored data related to customer path or traffic as will be subsequently described herein. Accordingly, the process interrelates these programs and data to present customized solutions. [0082] It will be appreciated that the invention has been described hereabove with reference to certain examples or preferred embodiments as shown in the drawings. Various additions, deletions, changes and alterations may be made to the above-described embodiments and examples without departing from the intended spirit and scope of this invention. Accordingly, it is intended that all such additions, deletions, changes and alterations be included within the scope of the claims. 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