Machine learning collaboration techniques
US-2024420212-A1 · Dec 19, 2024 · US
US2018315110A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2018315110-A1 |
| Application number | US-201816028203-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jul 5, 2018 |
| Priority date | May 8, 2012 |
| Publication date | Nov 1, 2018 |
| Grant date | — |
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Embodiments of the invention provide a nexus between a user's presence within or proximate to a brick and mortar store outside of an explicit user transaction within the store, that is based solely upon the user's presence within the store, and not on any affirmative actions taken by the user by maintaining location awareness of the user and by communicating this awareness in real time, as the user moves from location to location, to brick and mortar stores at or near to the user's location. In this way, embodiments of the invention link the user's virtual presence, for example via the Internet, and all of the user-related information that is available for data mining, for example using big data techniques, to the user's physical presence at a physical location to create an enhanced user experience within the physical location in real time.
Opening claim text (preview).
1 . A computer implemented method, comprising: processing, by a central server, data logged during user interactions across a plurality of different communications channels to determine links between user interactions across the plurality of different communications channels and thereby associate the user interactions with a particular user; generating, by the central server, a profile for the particular user based on the interactions associated with the particular user, the profile indicative of preferences and/or behavioral patterns of the particular user; tracking, by the central server, a location of the particular user based on user location data received from an application at a user device associated with the particular user, the user location information generated by the application at the user device based on signals from built-in sensors at the user device; determining, by the central server, based on the tracking, that the particular user is within proximity to and/or moving towards a physical facility that includes an object of interest to the particular user based on the preferences and behavioral patterns of the particular user indicated by the generated profile; and causing, by the central server, the application at the user device to present information regarding the object of interest to the particular user in real time as the particular user is within proximity to and/or moving towards the physical facility. 2 . The method of claim 1 , wherein determining links between user interactions across the plurality of different communications channels includes processing non-personally identifiable information (non-PII) included in the logged data using machine learning to: predict a likely unique identifier associated with the particular user; and/or associate a combination of several types of non-PII information included in the logged data with the particular user. 3 . The method of claim 1 , further comprising: identifying, by the central server, based on data logged during user interactions by the particular user across the plurality of different communications channels, objects associated with user inquires and/or user purchases, wherein the object is of interest to the particular user if the object is the same or similar to the objects associated with the user inquires and/or user purchases. 4 . The method of claim 1 , further comprising: identifying, by the central server, an online purchase by the particular user based on data logged during user interactions across the plurality of different communications channels; wherein the object is of interest to the particular user if the object is a product that fulfills the online purchase; and wherein causing the application at the user device to present information regarding the object of interest includes presenting an option for in-store pickup of the object of interest to fulfil the online purchase. 5 . The method of claim 4 , further comprising: transmitting, by the central server, a notification to the physical facility to prepare the object of interest for in store pickup by the particular user before the particular user enters the physical facility. 6 . The method of claim 1 , further comprising: linking, by the central server, online and/or phone purchases to the profile of the particular user to offer related and/or complementary products to the particular user proactively when the particular user enters a store for in-store pickup of the online and/or phone purchases. 7 . The method of claim 1 , wherein the object is of interest to the particular user if the object is the same as, similar to, related to, and/or complementary to a product that the particular user previously purchased, a product that the particular user searched for but did not purchase, or a product that the particular user is likely to purchase based on preferences and/or behavioral patterns indicated in the profile for the particular user. 8 . The method of claim 1 , further comprising: tracking, by the central server, a location of the object of interest based on location data received from a device attached to the object of interest. 9 . The method of claim 8 , wherein information regarding the object of interest is presented to the particular user via the application at the user device when the particular user is within a minimum distance to the object of interest. 10 . The method of claim 1 , wherein information regarding the object of interest includes any of an option to purchase the object of interest, an option for in-store pickup of the object of interest, an incentive offer regarding the object of interest, a location of the object of interest within the physical facility, an offer of assistance by a sales representative at the physical facility, and/or a recommendation for related and/or complementary products. 11 . The method of claim 1 , the plurality of different communications channels comprising any of online, online chat, email, social media, interactive voice response (IVR), and call center. 12 . The method of claim 1 , the physical facility comprising any of an aircraft, a vehicle, an airport, a bus, a hospital, a bank, a hotel, a restaurant, a store, a mall, a department store, a service office, an insurance or medical facility, an entertainment venue, a gym, and a movie theater. 13 . The method of claim 1 , the user device comprising a wireless device that can be passively interrogated or that passively identifies the user's location. 14 . A computing system comprising: a processor; and a memory storing instructions, execution of which by the processor will cause the computing system to perform a process including: processing data logged during user interactions across a plurality of different communications channels to determine links between user interactions across the plurality of different communications channels and thereby associate the user interactions with a particular user; generating a profile for the particular user based on the interactions associated with the particular user, the profile indicative of preferences and/or behavioral patterns of the particular user; tracking a location of the particular user based on user location data received from an application at a user device associated with the particular user, the user location information generated by the application at the user device based on signals from built-in sensors at the user device; determining, based on the tracking, that the particular user is within proximity to and/or moving towards a physical facility that includes an object of interest to the particular user based on the preferences and behavioral patterns of the particular user indicated by the generated profile; and causing, the application at the user device to present information regarding the object of interest to the particular user in real time as the particular user is within proximity to and/or moving towards the physical facility. 15 . The system of claim 14 , wherein determining links between user interactions across the plurality of different communications channels includes processing non-personally identifiable information (non-PII) included in the logged data using machine learning to: predict a likely unique identifier associated with the particular user; and/or associate a combination of several types of non-PII information included in the logged data with the particular user. 16 . The system of claim 14 , the memory storing further instructions, execution of which by the processor will cause the computing system to perform a process further inc
Electronic shopping [e-shopping] · CPC title
based on user location · CPC title
Recommending goods or services · CPC title
using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds · CPC title
Managing shopping lists, e.g. compiling or processing purchase lists (shipping orders G06Q10/083; order filling G06Q10/087) · CPC title
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