Patent Application
20130317916
The disclosed technology relates generally to smart shopping services and, more particularly, to smart shopping services that incorporate a user's location to better enhance the user's shopping experience.
Many buying decisions tend to be made inside a store as users search for or casually browse various types of products on the shelves. One powerful tool for influencing a shopper's buying decisions is to target certain content, such as an advertisement or informational alert, pertaining to specific items that are in the shopper's immediate proximity and, thus, also close to the shopper's mobile device. Another technique is to develop an understanding of a shopper's behavior based on the amount of time he or she spends near particular products as well as content choices he or she makes on the mobile device. Location awareness and shopper context awareness may be combined to create highly targeted content that results in superior shopper engagement and influencing of buying decisions.
However, the key to providing such smart shopping experiences is to gather accurate shopper location, e.g., find out which product(s) the shopper is near at an given time. Existing wireless technologies that estimate location are either unavailable indoors, e.g., GPS or cellular to some extent, or have poor accuracy, e.g., WiFi and cellular, to enable such an experience. For example, while WiFi is a commonly-used indoor location tracking technology, WiFi location accuracy is limited to a few meters, e.g., no more than approximately 2.5 meters. Such accuracy may be adequate for room-level tracking but is not adequate for providing optimized and complete smart shopping services to users.
Another technology that can be used indoors is near field communication (NEC), e.g., radio communication. However, NFC technologies tend to have a very short range, usually on the order of 10 centimeters or less, which essentially means that the user must almost be in physical contact with the source in order to recover any meaningful information with regard to the source. Such a limitation would effectively render NFC incapable of being successfully implemented in a smart shopping service as described above.
Thus, there remains a need for improved smart shopping services provided to users that are based at least in part on the user's location within an establishment.
Embodiments of the disclosed technology are illustrated by way of example, and not by way of limitation, in the drawings and in which like reference numerals refer to similar elements.
Embodiments of the disclosed technology may be implemented in virtually any type of indoor location or establishment, e.g., a large retail store, that has a number of lighting sources, e.g., lamps or overhead lighting. In certain embodiments, each user, e.g., shopper, within the establishment, e.g., store, has his or her own mobile device that can be either their own personal smartphone, tablet device, or other handheld electronic device, or an establishment-owned portable device, e.g., a tablet computing device, that may be attached to the shopping cart. For example, shoppers may each carry their own mobile device with them as they travel around a store shopping.
Certain embodiments of the disclosed technology include highly accurate indoor location tracking technology using visible light communication (VLC) location beacon messages. In terms of physical properties such as range and directivity, VLC characteristics are favorable in terms of delivering indoor location based content with very high accuracy. Such location information can be used for or in connection with discovering a number of useful parameters such as user dwell-times and trajectory. Communication with a mobile device over a wireless technology other than VLC may be achieved by tagging VLC location-related information to messages.
By combining accurate location information with a shopper interaction profile and/or a shopper personal profile, for example, smart shopping services using any or all the VLC location-related information may be realized. Certain embodiments include the delivering of content to a user that is immediately relevant to the user, e.g., content that translates typically to items that are within the user's and, thus, his or her mobile device's immediate proximity. Such content may be delivered to the user's mobile device as the user walks by specific items in a store, for example. VLC location precision can be controlled by deploying an appropriate number of sources and being highly directional in order to deliver high accuracy location information to be used by smart shopping services.
Certain implementations may include methods for accurately estimating the location, movement trajectory, dwell time(s), etc. of a user by way of monitoring the user's mobile device in an indoor setting, such as a retail store or shopping mall. A number of smart shopping services can be provided once such accurate location information is known, e.g., discovered or determined. For example, the combination of information pertaining to where a user is inside of a store, e.g., near certain products in a retail store, with information pertaining to a user's response to and/or interest in certain products, advertisements, etc. can be used to influence the user's in-store buying decisions in real-time. Customer response, interest, and interaction may thus be tied with context and location to offer a number of smart shopping services combining such information.
The lighting industry has been undergoing a major technological shift toward Light Emitting Diode (LED)-based lighting, due primarily to their superior lifetimes and energy efficiency compared to current lighting technology. LEDs have a modulation bandwidth that can be used to transmit information without any noticeable effects to the lighting function. Such information will be referred to herein as Visible Light Communication (VLC). Thus, LEDs can serve dual purposes of lighting and communication. Furthermore, VLC is ideally suited for providing location information due to its highly directional nature, which comes from having highly directional antennas, e.g., via optics, due to the extremely short wavelength of VLC.
In certain embodiments, each VLC source may transmit a unique ID announcing its fixed location, referred to herein as a location beacon. A shopper's mobile device can be equipped with a VLC receiver such as a photo-diode or photo-sensor array. VLC-enabled light sources may be placed throughout, the store and, as the shopper moves about the store, the VLC-enabled mobile device may receive one or more location beacons that may serve to identify where the user's mobile device is.
The granularity of user location estimation can be controlled by having a sufficient number of VLC-enabled light sources, particularly as compared to WiFi. If the user's mobile device receives multiple location beacon messages, it can use one of a number of techniques to resolve the location. For example, the mobile device can take a simple average of the different locations or a weighted average based on signal strength indicators, or use the angle of location beacon arrival information to determine the location.
In certain embodiments, it is possible to know the location of users' mobile devices and also to communicate with them using an appropriate wireless technology, e.g., WiFi. To enable this, a special packet can be constructed that combines location-related information gathered via VLC with the unique address/identifier of the mobile device. For example, location based content may be enabled from the infrastructure or other mobile devices to be delivered over WiFi, in which case the mobile device can tag its WiFi MAC address or local IP address along with the location information gathered via VLC. This may enable other devices/infrastructure to know the mobile device location and communicate with the mobile device using an appropriate wireless technology, thus complementing the VLC location tracking capability with the communications capability of virtually any other wireless technology.
Once a user's location information becomes known, other attributes such as the user's dwell time(s), e.g., how long he or she stayed at a certain location within the store, and trajectory, e.g., how the user was moving and to where, may be inferred therefrom. A large number of smart shopping services may use and/or rely on such location-based information. For example, information about one or more products in the immediate vicinity of the user or user's device may be delivered onto the screen of the mobile device.
The user may choose to interact with the smart shopping service(s) to find out more information about a particular product, for example. Certain embodiments include a user interaction profile, which may include information pertaining to which product(s) he or she chose to find out more about, how much time he or she spent in a specific location, etc. A user interaction profile can have information that is very valuable information in inferring the shopper's personal interests. Combining the precise user location with the user's specific interaction profile can be a very rich source of information that can be used to deliver targeted content directly to the user's mobile device.
In certain implementations of the disclosed technology, the user's location and context information may be fed back to the smart shopping infrastructure wirelessly, e.g., via WiFi or VLC. The smart shopping infrastructure may use this information to deliver real-time content to the mobile device or to display appropriate shopper-specific content on fixed digital signage screens within the store as he or she walks up to each one.
In certain implementations, a user can either manually or automatically, e.g. via VLC, NFC, or WiFi, share his or her shopping profile information and/or personal information from their personal device, e.g., smartphone. As used herein, a user's shopping profile includes information generally pertaining to the user's general shopping interests, shopping list, etc., and personal information refers to name, sex, age, and other objective descriptors. Such information may be used in connection with the accurate location information, the user's interaction profile, and any previous shopping history to deliver powerful targeted content.
A number of smart shopping services in accordance with the disclosed technology may be based on accurate location information provided by VLC technology, for example, as well as context provided by way of shopper interaction information. In some embodiments, such smart shopping services may also rely on sensors deployed by the user's mobile device itself. Described below are some of the many smart shopping services that may be implemented in a number of embodiments.
In certain embodiments, precise location information, shopper interaction information, personal profiles, or any combination thereof may be used to deliver targeted content to the user's mobile device and/or fixed digital signage. Such targeted content may include an advertisement, shopping or product-specific information, or special promotions relevant to one or more specific items or products situated in the vicinity of the shopper.
Certain implementations may include guiding the shopper inside the store to particular item or service. For example, the user's mobile device can act as an indoor global positioning system (GPS) to help guide the user to the frozen meals section in a grocery store. In certain embodiments, the framework may be used to locate and/or track people by way of locating/tracking their mobile devices. For example, members of a certain group inside a large indoor theme park may have their mobile devices located/tracked so as to keep the leader(s) informed as to the members' whereabouts within the theme park.
Certain implementations of the disclosed technology may include an inventory supply service. In such embodiments, the user may be a store or warehouse employee. As the employee places or re-stocks certain inventory, for example, the user's VLC-enabled mobile device can automatically mark the location of the item for the user. This can be used for automatically re-stocking inventory in future. For example, an automatic device, e.g., robot, may be programmed to put items in a specific location when it determined that a re-stocking is required or when it instructed to do so.
In certain embodiments, offline shopper data analytics concerning shopper dwell times, trajectory, interaction context, or any combination thereof may be used for any of a number of services. For example, a store may use it to determine the placement of certain products and also to provide an appropriate service based on where customers are situated within the store.
Step 304 involves communication between the mobile device and a smart shopping backend infrastructure, which may include a smart shopping server or other device. Such communication may take place using WiFi technology, for example. The mobile device can provide user-specific information such as the current location of the user/device, which the infrastructure may use to further define or develop the user's shopper profile. Further, such infrastructure can deliver location-based content to the device.
Step 306 illustrates an optional extension in which the smart shopping infrastructure is tied to other smart shopping entities within the store such as a digital sign. For example, as the user walks by the digital sign, the smart shopping infrastructure may cause the sign to display content that it determines to be at least potentially relevant to the user.
At 308, the user's personal profile is updated by the user's mobile device, the smart shopping infrastructure, or both. For example, the user's personal profile may be updated at the end of each visit to the establishment, after a certain period of time has passed, after a dwell time has exceeded some predefined threshold, etc. The user's profile may be stored on his or mobile device, remotely, e.g., on a smart shopping server or database, or some combination thereof.
Embodiments of the disclosed technology may be incorporated in various types of architectures. For example, certain embodiments may be implemented as any of or a combination of the following: one or more microchips of integrated circuits interconnected using a motherboard, a graphics and/or video processor, a multicore processor, hardwired logic, software stored by a memory device and executed by a microprocessor, firmware, an application specific integrated circuit (ASIC), and/or a field programmable gate array (FPGA). The term “logic” as used herein may include, by way of example, software, hardware, or any combination thereof.
Although specific embodiments have been illustrated and described herein, it will be appreciated by those of ordinary skill in the art that a wide variety of alternate and/or equivalent implementations may be substituted for the specific embodiments shown and described without departing from the scope of the embodiments of the disclosed technology. This application is intended to cover any adaptations or variations of the embodiments illustrated and described herein. Therefore, it is manifestly intended that embodiments of the disclosed technology be limited only by the following claims and equivalents thereof.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US2011/067749 | 12/29/2011 | WO | 00 | 6/25/2013 |
