Patent Application
20220129919
This application relates generally to a system and method to provide automated shopping assistance to shoppers based on their historic shopping choices.
While mail order purchases are on the rise, many products are still purchased by consumers at a retail premises. This is especially the case for perishable items, such as groceries, as well as clothing, which customers still like to try on for fitting and viewing prior to purchasing.
Consumers often shop at the same store, or different branches for the same store. In the case of consumables, such as groceries, shoppers generally know the location goods from their usual store location which they buy frequently. However, if they go to a different location, they can spend considerable time trying to locate items on their list, and they may have to retrace their steps multiple times to track down missing items. One solution is to try to track down a store employee to ask for a product location. When many items cannot be found, an employee may have to found multiple times during a single shopping trip. This problem can be further exacerbated understanding that many store workers are not employed by the establishment, but provide direct stocking of products they deliver to the store. They are likely unknowledgeable about locations of any goods but their own. Even when a consumer shops at their customary location, stores often rearrange their inventory, and the same problems can occur.
Various embodiments will become better understood with regard to the following description, appended claims and accompanying drawings wherein:
The systems and methods disclosed herein are described in detail by way of examples and with reference to the figures. It will be appreciated that modifications to disclosed and described examples, arrangements, configurations, components, elements, apparatuses, devices methods, systems, etc. can suitably be made and may be desired for a specific application. In this disclosure, any identification of specific techniques, arrangements, etc. are either related to a specific example presented or are merely a general description of such a technique, arrangement, etc. Identifications of specific details or examples are not intended to be, and should not be, construed as mandatory or limiting unless specifically designated as such.
In example embodiments herein provide an automatic assistant system which helps consumer with shopping based on their own prior shopping patterns. Most consumers have their developed their own shopping patterns over time. For example, a consumer may shop for their family on a weekly basis for the essential items such as milk, eggs, fruits, and meats. They may have alternative shopping patterns at the same time. For example, the consumer may shop for laundry detergent every couple of months.
In an example embodiment, a retail store system keeps a record of consumers' faces and a list of their shopping items and purchasing intervals and identifies one or more shopping patterns for each consumer. This information can be shared among affiliated stores. When the same consumer enters a store, the system identifies the consumer and sends a store map including an indication of a current location of their frequently purchased items or items that are due for repurchase based on their shopping pattern. Information is sent to the consumer's smart device, such as smartphone or tablet, by identification accomplished by facial recognition. If the consumer enters a different store branch the consumer can easily locate products that are often purchased as their locations at the new store have been identified and indicated on their map.
When the consumer shops at the same store frequently, and knows the typical location of the products, the retailer store often times will update the shelf space for products. With the subject system, the consumer does not need to worry about locating their frequent purchased products when they have been relocated.
In further example embodiments, the system includes a reminder subsystem that reminds the consumer to buy certain products based on the shopping pattern. In the example above, it may have been two months since their last laundry detergent purchase, and they may not have recalled that it's time to replenish their supply.
Example embodiments identify and utilize individual consumer shopping pattern, and through the use of a recommendation engine, the retailer store is able to push on-sale information and/or coupons to consumer's smart phone for potential products of interest.
Retailer store is able to keep a record of the consumer's face and shopping item list, and compile a shopping pattern for the consumer.
In accordance with the subject application,
During a shopping visit, consumers acquire their selection of goods from the premises and pay for their selections when they leave, such as via clerk 128 at checkout point-of-sale (POS) terminal 132. Their selections are stored associatively a purchase date with their shopping pattern information. In the illustrated example, consumer 120 purchases canned vegetables from location 136, toothpaste from location 140, bread from location 144, frozen pizza from location 148, tissue from location 152 and milk from location 156. This information is aggregated with information from prior shopping visits for consumer 120 if this is not their initial visit using the assistant. The system 100 includes pre-stored information or data indicating a location at the premises for each item selected for purchase. If consumer 120 has an established shopping pattern when they are identified as they enter the premises 116, a store map showing locations for frequently purchased items, or items that are likely due for repurchase, is generated and sent to the user's device 122 before they start shopping. A suitable map may appear similar to the layout and indications illustrated in
Turning now to
Processor 304 is also in data communication with a storage interface 306 for reading or writing to a data storage system 308, suitably comprised of a hard disk, optical disk, solid-state disk, or any other suitable data storage as will be appreciated by one of ordinary skill in the art.
Processor 304 is also in data communication with a network interface controller (NIC) 330, which provides a data path to any suitable network or device connection, such as a suitable wireless data connection via wireless network interface 338 or a wired data connection via wired network interface 339. A suitable data connection to an MFP or server is via a data network, such as a local area network (LAN), a wide area network (WAN), which may comprise the Internet, or any suitable combination thereof. A digital data connection is also suitably directly with an MFP or server, such as via BLUETOOTH, optical data transfer, Wi-Fi direct, or the like.
Processor 304 is also in data communication with a user input/output (I/O) interface 340 which provides data communication with user peripherals, such as touch screen display 344 via display generator 346, as well as keyboards, mice, track balls, touch screens, or the like. It will be understood that functional units are suitably comprised of intelligent units, including any suitable hardware or software platform. Processor 304 is also in data communication with a digital camera 350, which may be from an external device, such as camera 124 of
If a determination is made at block 816 that an identified customer exists in the database, the process proceeds to block 848 wherein a generated shopping patterns for the customer are compiled based on their shopping patterns and prior purchases. A customized listing of coupons or on-sale items is generated from a database of coupon or on-sale items at block 852. Next, at block 856 map information, suitably including locations and listings of frequently purchased items for a current store location, is pushed to the shopper's device, along with relevant coupon or on-sale information, for display on the shopper's device. The process then proceeds to block 844.
In block 844, a customer's shopping pattern is tracked. If the customer never checks out, such as when they leave the store without any purchases, as determined by block 860, the process ends at block 864, suitably after a set timeout duration. When a customer checks out, their new purchase information and shopping pattern information is sent to the cloud service at block 868 and the process ends at block 864.
While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the spirit and scope of the inventions.
