Trigger repeat order notifications
First Claim
1. A computer-implemented method comprising:
- receiving a particular set of user data, the particular set of user data including user data obtained from a user device and data indicating one or more of (i) an inclination of the user to cook, (ii) an inclination of the user to dine out, (iii) a likelihood that the user has already placed an order with an ordering service for delivery of food within a recent time interval, and (iv) a likelihood that the user has performed an activity other than eating or visiting a restaurant that is associated with ordering food;
obtaining a predictive model that estimates a likelihood of the user to order a food item, wherein the predictive model is generated using observation data that includes historic user data and user data from other user devices;
providing the particular set of user data to the predictive model;
obtaining, from the predictive model, an indication of the likelihood of the user to order the food item;
based on the indication of the likelihood of the user to order the food item obtained from the predictive model, determining whether to output a notification on the user device inviting the user to order the food item; and
in response to determining whether to output the notification on the user device inviting the user to order the food item, selectively outputting the notification on the user device inviting the user to order the food item.
1 Assignment
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Accused Products
Abstract
Methods, systems, and apparatus for receiving a particular set of user data; obtaining a predictive model that estimates a likelihood of a user to order a food item, wherein the predictive model is generated using observation data that includes historic user data and user data from other user devices; providing the particular set of user data to the predictive model; obtaining an indication of a likelihood of the user to order a food item; based on the indication of a likelihood of the user to order a food item, determining whether to output a notification on the user device inviting the user to order a food item; and in response to determining to output a notification on the user device inviting the user to order a food item, selectively outputting a notification on the user device inviting the user to order a food item.
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Citations
20 Claims
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1. A computer-implemented method comprising:
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receiving a particular set of user data, the particular set of user data including user data obtained from a user device and data indicating one or more of (i) an inclination of the user to cook, (ii) an inclination of the user to dine out, (iii) a likelihood that the user has already placed an order with an ordering service for delivery of food within a recent time interval, and (iv) a likelihood that the user has performed an activity other than eating or visiting a restaurant that is associated with ordering food; obtaining a predictive model that estimates a likelihood of the user to order a food item, wherein the predictive model is generated using observation data that includes historic user data and user data from other user devices; providing the particular set of user data to the predictive model; obtaining, from the predictive model, an indication of the likelihood of the user to order the food item; based on the indication of the likelihood of the user to order the food item obtained from the predictive model, determining whether to output a notification on the user device inviting the user to order the food item; and in response to determining whether to output the notification on the user device inviting the user to order the food item, selectively outputting the notification on the user device inviting the user to order the food item. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 20)
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9. A system comprising:
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one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising; receiving a particular set of user data, the particular set of user data including user data obtained from a user device and data indicating one or more of (i) an inclination of the user to cook, (ii) an inclination of the user to dine out, (iii) a likelihood that the user has already placed an order with an ordering service for delivery of food within a recent time interval, and (iv) a likelihood that the user has performed an activity other than eating or visiting a restaurant that is associated with ordering food; obtaining a predictive model that estimates a likelihood of the user to order a food item, wherein the predictive model is generated using observation data that includes historic user data and user data from other user devices; providing the particular set of user data to the predictive model; obtaining, from the predictive model, an indication of the likelihood of the user to order the food item; based on the indication of the likelihood of the user to order the food item obtained from the predictive model, determining whether to output a notification on the user device inviting the user to order the food item; and in response to determining whether to output the notification on the user device inviting the user to order the food item, selectively outputting the notification on the user device inviting the user to order the food item. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising:
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receiving a particular set of user data, the particular set of user data including user data obtained from a user device and data indicating one or more of (i) an inclination of the user to cook, (ii) an inclination of the user to dine out, (iii) a likelihood that the user has already placed an order with an ordering service for delivery of food within a recent time interval, and (iv) a likelihood that the user has performed an activity other than eating or visiting a restaurant that is associated with ordering food; obtaining a predictive model that estimates a likelihood of the user to order a food item, wherein the predictive model is generated using observation data that includes historic user data and user data from other user devices; providing the particular set of user data to the predictive model; obtaining, from the predictive model, an indication of the likelihood of the user to order the food item; based on the indication of the likelihood of the user to order the food item obtained from the predictive model, determining whether to output a notification on the user device inviting the user to order the food item; and in response to determining whether to output the notification on the user device inviting the user to order the food item, selectively outputting the notification on the user device inviting the user to order the food item. - View Dependent Claims (17, 18, 19)
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Specification