Data mesh based zero effort shopping

Abstract

A system and method for data mesh-based zero effort shopping is provided. In example embodiments, attribute data associated with a user is received from a plurality of attribute sources. Demand indications are extracted from the attribute data. The demand indications may be indicative of anticipatory demand by the user for a particular item. An item is identified from the attribute data based on the extracted demand indications. User characteristics pertaining to the user are inferred from the attribute data. A purchase associated with the identified item is facilitated based, at least in part, on the user characteristics.

What is claimed is: 
     
         1 . A system comprising:
 an attribute module to receive attribute data associated with a user from a plurality of attribute sources;   an item module to extract demand indications from the attribute data, the demand indications being indicative of anticipatory demand by the user for a particular item;   an analysis module, implemented by a hardware processor of a machine, to identify a pertinent item from the attribute data based on the extracted demand indications;   a characteristic module to infer user characteristics pertaining to the user from the attribute data; and   an order module to determine transaction parameters for a suggested transaction associated with the pertinent item based, at least in part, on the user characteristics and facilitating the suggested transaction according to the determined transaction parameters.   
     
     
         2 . The system of  claim 1 , wherein the at least one order parameter includes at least one of a quantity, a delivery time, a payment time, a delivery method, a delivery destination, a merchant, or a product. 
     
     
         3 . A method comprising:
 receiving attribute data associated with a user from a plurality of attribute sources;   extracting demand indications from the attribute data, the demand indications being indicative of anticipatory demand by the user for a particular item;   identifying, using a hardware processor of a machine, a commerce item from the attribute data based on the extracted demand indications;   inferring user characteristics pertaining to the user from the attribute data;   determining order parameters for a user purchase associated with the commerce item based, at least in part, on the inferred user characteristics; and   facilitating the user purchase according to the determined order parameters.   
     
     
         4 . The method of  claim 3 , wherein the at least one order parameter includes at least one of a quantity, a delivery time, a payment time a delivery method, a delivery destination, a merchant, or a product. 
     
     
         5 . The method of  claim 3 , further comprising:
 extracting a current inventory level of the commerce item from the attribute data;   determining an inventory threshold for the commerce item by modeling usage of the commerce item based on the extracted current inventory level and the inferred user characteristics;   identifying a mismatch between the inventory threshold and the current inventory level; and   based on the mismatch, automatically performing the user purchase on behalf of the user.   
     
     
         6 . The method of  claim 3 , further comprising:
 identifying a purchase motive of the user for the commerce item by analyzing the inferred user characteristics, the purchase motive corresponding to a motive time;   determining temporal order parameters, included in the order parameters, based on the motive time; and   facilitating the user purchase according to the determined temporal order parameters.   
     
     
         7 . The method of  claim 3 , further comprising:
 identifying similar users, from among a plurality of other users, that are similar to the user based on the inferred user characteristics and respective user characteristics of the plurality of other users; and   determining the order parameters based on the user characteristics of the identified similar users.   
     
     
         8 . The method of  claim 3 , further comprising:
 accessing purchase criteria corresponding to the user; and   automatically purchasing the commerce item on behalf of the user according to the purchase criteria.   
     
     
         9 . The method of  claim 8 , wherein the purchase criteria include at least one criterion corresponding to a budget; and
 wherein the automatically purchasing the commerce item on behalf of the user is based, at least in part, on the budget.   
     
     
         10 . The method of  claim 8 , further comprising:
 determining an item category for the commerce item, the purchase criteria including criteria corresponding to the item category; and   facilitating the user purchase of the commerce item according to the purchase criteria corresponding to the determined item category.   
     
     
         11 . The method of  claim 3 , further comprising:
 generating a notification that includes an option to make the user purchase, the notification including the determined order parameters;   causing presentation of the notification to the user;   receiving a user selection of the option to make the user purchase; and   responsive to receiving the user selection, performing the user purchase according to the determined order parameters.   
     
     
         12 . The method of  claim 11 , further comprising:
 identifying presentation parameters for presentation of the notification to the user based on the inferred user characteristics, the presentation parameters including a presentation time and a presentation device; and   causing presentation of the notification according o the presentation. parameters.   
     
     
         13 . The method of  claim 11 , further comprising:
 adapting the presentation of the notification to the user based, at least in part, on the inferred user characteristics.   
     
     
         14 . The method of  claim 1  further comprising:
 detecting a trigger action of the user based on real-time data included in the attribute data; and 
 based on the detected trigger action, causing presentation of the notification to the user. 
 
     
     
         15 . The method of  claim 3 , further comprising:
 calculating a demand metric for the commerce item based on the demand indications corresponding to the commerce item; and   facilitating the user purchase associated with the commerce item based, at least in part, on the demand metric.   
     
     
         16 . The method of  claim 15 , further comprising:
 automatically performing the user purchase on behalf of the user based on the demand metric exceeding a threshold.   
     
     
         17 . The method of  claim 15 , further comprising:
 based on demand metric exceeding a threshold, generating a notification providing the user an option to purchase the commerce item, the notification including the determined order parameters; and   causing presentation of the notification to the user.   
     
     
         18 . A machine readable medium having no transitory signals and storing instructions that, when executed by at least one processor of a machine, cause the machine to perform operations comprising:
 receiving attribute data associated with a user from a plurality of attribute sources;   extracting demand indications from the attribute data, the demand indications being indicative of anticipatory demand by the user for a particular item;   identifying an item from the attribute data based on the extracted demand indications;   inferring user characteristics pertaining to the user from the attribute data;   determining order parameters for a user purchase associated with the commerce item based, at least in part, on the inferred user characteristics; and   facilitating the user purchase according to the determined order parameters.   
     
     
         19 . The machine-readable medium of  claim 18 , wherein the at least one order parameter includes at least one of a quantity, a delivery time, a payment time, a deliver method, a delivery destination, a merchant, or a product. 
     
     
         20 . The machine-readable medium of  claim 18 , wherein the operations further comprise:
 extracting a current inventory level of the commerce item from the attribute data;   determining an inventory threshold for the commerce item by modeling usage of the commerce item based on the extracted current inventory level and the inferred user characteristics;   identifying a mismatch between the inventory threshold and the current inventory level; and   based on the mismatch, automatically performing the user purchase on behalf of the user.