Restaurant Specific Personalization

Patent metadata

Field	Value
Publication number	US-2018096440-A1
Application number	US-201514755308-A
Country	US
Kind code	A1
Filing date	Jun 30, 2015
Priority date	Jun 30, 2015
Publication date	Apr 5, 2018
Grant date	—

Abstract

Personalizing recommendations for users based at least in part on learning user patterns that are specific to individual entities is described. A service provider may determine data associated with interactions between users and an entity and may determine, based on the data, patterns associated with a user of the users and the entity. The patterns may represent affinities between the user and at least one of goods or services offered by the entity. The service provider may determine entity data associated with the entity and, based at least in part on an availability of at least one of the goods or the services, may generate recommendations associated with the patterns and the entity data.

First claim

1 . A system comprising:
one or more processors; memory; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising:
determining restaurant data associated with a restaurant, the restaurant data including a plurality of menu items offered by the restaurant;
determining user data that is representative of a behavior of a user with respect to the restaurant, the user data including data associated with menu items of the plurality of menu items ordered by the user from the restaurant;
determining, based on the user data, a user pattern associated with the user and a menu item of the menu items ordered by the user from the restaurant, the user pattern being determined based on applying a machine learning algorithm to the user data to generate the user pattern and at least one of a frequency in which the user ordered the menu item or a number of times the user ordered the menu item;
receiving updated restaurant data indicating that at least one of an availability of the menu item changed or that the menu item is being offered at a discounted price; and
based at least in part on the updated restaurant data and the user pattern, generating a recommendation to be provided to a user device associated with the user, the recommendation being associated with a reservation for the restaurant.

2 . The system of claim 1 , the operations further comprising:
comparing the user data to the updated restaurant data; based on comparing the user data to the updated restaurant data, determining an alternative menu item offered by the restaurant to recommend to the user; and generating a deal that is redeemable by the user for the alternative menu item.

3 . The system of claim 1 , the operations further comprising determining, based on the user data, an additional user pattern associated with the user and at least one of a table at the restaurant, a server at the restaurant, or a date, wherein the reservation is associated with at least one of the table, the server, or the date.

4 . The system of claim 1 , the operations further comprising:
generating a user interface that provides functionality to the user to request the reservation; and providing the user interface to the user device.

5 . The system of claim 4 , the operations further comprising:
generating a notification indicating at least one of that the availability of the menu item changed or that the menu item is being offered at the discounted price; and providing the notification and the user interface to the user device.

6 . A method comprising:
determining data associated with interactions between a user and a restaurant; determining, based at least in part on the data, a pattern associated with the user and menu items offered by the restaurant, the pattern being determined based at least in part on at least one of a frequency in which the menu items were requested or a number of times the menu items were requested; based at least in part on the pattern, generating a recommendation that is associated with at least one of a reservation for the restaurant, an action associated with the menu items to be provided by the restaurant, or a deal associated with the menu items that is redeemable at the restaurant; and sending the recommendation to a device associated with the user.

7 . The method of claim 6 , further comprising determining that the pattern corresponds to at least one of an ingredient included in a menu item of the menu items or a preparation of the menu item.

8 . The method of claim 6 , further comprising determining that the pattern corresponds to the user and one or more other users who are associated with a same social graph as the user.

9 . The method of claim 6 , further comprising:
determining that the pattern corresponds to a time; generating the recommendation for the action associated with the menu items to be provided by the restaurant at or before the time; and sending the recommendation for the action to the device a predetermined period of time before the time.

10 . The method of claim 9 , further comprising:
receiving input associated with the recommendation; and based at least in part on the input, at least one of:
based at least in part on a first determination that the input confirmed performance of the action, sending a first instruction to the restaurant to perform the action; or
based at least in part on a second determination that the input canceled performance of the action, sending a second instruction to the restaurant to refrain from performing the action.

11 . The method of claim 6 , further comprising:
determining that a menu item of the menu items that was previously unavailable is available; generating a notification indicating that the menu item is available; and sending the notification and the recommendation to the device.

12 . The method of claim 6 , further comprising:
determining that a menu item of the menu items that was previously available is unavailable; comparing the data to restaurant data associated with the menu items; based at least in part on comparing the data to the restaurant data associated with the menu items, determining an alternative menu item offered by the restaurant to recommend to the user; and determining that the recommendation for the restaurant includes the deal that is redeemable by the user, the deal being associated with the alternative menu item.

13 . The method of claim 6 , further comprising:
determining that the user has interacted with the restaurant at least one of a second frequency above a predetermined threshold or a predetermined number of times; determining that the user qualifies for premium benefits that are different from benefits associated with users that have interacted with the restaurant at a third frequency below the predetermined threshold or fewer than the predetermined number of times; determining that the device is within a predetermined distance from a physical location associated with the restaurant; and based at least in part on determining that the device is within the predetermined distance from the physical location associated with the restaurant, determining that the recommendation is associated with one or more premium benefits of the premium benefits.

14 . A system comprising:
one or more processors; memory; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising:
determining data associated with interactions between users and an entity;
determining, based at least in part on the data, one or more patterns associated with a user of the users and the entity, the one or more patterns representing one or more affinities between the user and at least one of goods or services offered by the entity and being determined based at least in part on at least one of:
a frequency in which at least one of the goods or the services were requested by the user or on behalf of the user; or
a number of times at least one of the goods or the services were requested by the user or on behalf of the user;

determining entity data associated with the entity, the entity data including data associated with at least one of the goods or the services offered by the entity; and
based at least in part on an availability of at least one of the goods or the services, generating one or more recommendations associated with the one or more patterns and the entity data.

15 . The system of claim 14 , the operations further comprising sending the on

Assignees

• Amazon Tech Inc

Inventors

• Lopez Gustavo Eduardo
• Gureja Neha
• Uppuluri Pawan Lata

Classifications

• G06Q30/0259

  based on store location · CPC title

• G06Q50/12 Primary

  Hotels or restaurants · CPC title

• G06Q10/02

  Reservations, e.g. for tickets, services or events · CPC title

• G06Q30/0255

  based on user history · CPC title

• G06Q30/0226

  Incentive systems for frequent usage, e.g. frequent flyer miles programs or point systems · CPC title