Identifying purchase patterns and marketing based on user mood
View Patent ↗A system and method for facilitating electronic commerce over a network, according to one or more embodiments, includes communicating with a user via a user device and a business entity via a business entity device over the network, monitoring user navigation events over the network, determining a mood of the user based on user navigation behavior, marketing to the user based on the mood of the user, and storing user information related to the user navigation events and the mood of the user.
1. A system comprising:
a non-transitory memory; and
one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising:
receiving, by a service provider server, first interactions with first digital content via a user device of a user;
determining, based on the first interactions with the first digital content and further based on a pattern identification, a current mood of the user, wherein the pattern identification is based on a browsing session of the user;
receiving, by the service provider server after the determining the current mood of the user, second interactions with second digital content via the user device, wherein the second digital content comprises a plurality of different websites, the plurality of different websites associated with a plurality of merchants, developers, or social network providers, and wherein the second interactions comprise user interactions with the plurality of different websites, the user interactions including one or more purchase events;
arranging each of the merchants, developers, or social network providers into a plurality of different categories;
determining, at least in part based on the one or more purchase events, merchant information and a user purchasing pattern;
adjusting, in real time based at least in part on the merchant information and the user purchasing pattern and further based on the arranging, the current mood of the user;
determining, based on the adjusted current mood of the user, one or more likelihoods of the user to be interested in the first digital content or the second digital content; and
providing, by the service provider server, an advertisement or an offer for display on the user device based on the determined one or more likelihoods.
2. The system of claim 1 , wherein the operations further comprise: further adjusting the current mood of the user based on a purchase history of the user.
3. The system of claim 1 , wherein the first interactions correspond to interactions from one or more previous browsing sessions, and wherein the second interactions correspond to interactions from a current browsing session.
4. The system of claim 1 , wherein the first interactions or the second interactions include browser navigation or selection events.
5. The system of claim 1 , wherein the first digital content or the second digital content comprises social networking content provided by one of the social network providers.
6. The system of claim 1 , wherein the current mood or the adjusted current mood of the user comprises a self-improvement mood, a philanthropic mood, a mobile gaming mood, or a money-spending mood.
7. The system of claim 1 , wherein the advertisement is provided through an alert or a notification via the user device.
8. The system of claim 1 , wherein the operations further comprise determining a specific time for providing the advertisement or the offer, and wherein the advertisement or the offer is provided for display at the determined specific time.
9. The system of claim 1 , wherein the user interactions with the plurality of different websites comprise user navigation history of the plurality of different websites.
10. The system of claim 9 , wherein the operations further comprise storing the user navigation history on the service provider server.
11. A method comprising:
determining, based on a first set of interactions with a first set of digital content via a user device of a user, a current mood of the user, wherein the current mood of the user is determined using a pattern identification on at least one of one or more previous browsing sessions or a current browsing session of the user;
receiving a second set of interactions with a second set of digital content via the user device, the second set of interactions comprising user visits, searches, or purchases from a plurality of different websites, the plurality of different websites associated with a plurality of different entities;
arranging the plurality of different entities into a plurality of different categories;
adjusting, in real time based on the second set of interactions that comprise the user visits, searches, or purchases from the plurality of different websites and further based on the arranging, the current mood of the user;
determining, based on the adjusted current mood of the user, one or more likelihoods of the user to be interested in the first set of the digital content or the second set of the digital content; and
causing a recommendation for a product or a service to be displayed on the user device based on the determined one or more likelihoods.
12. The method of claim 11 , wherein the first set of interactions or the second set of interactions includes browser navigation or selection events.
13. The method of claim 11 , wherein the first set of digital content or the second set of digital content comprises social networking content provided by a social network provider.
14. A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising:
receiving, by a service provider server, first interactions with first digital content via a user device of a user;
determining, based on the first interactions with the first digital content, a current mood of the user, wherein the current mood of the user is determined using a pattern identification on at least one of the one or more previous browsing sessions or the current browsing session;
receiving, after the determining the current mood of the user, second interactions with second digital content via the user device, the second interactions comprising user interactions with a plurality of different websites, the plurality of different websites associated with a plurality of merchants, developers, or social networking entities;
classifying each of the merchants, developers, or social networking entities into a plurality of different categories;
adjusting, in real time based on the second interactions with the second digital content including the user interactions with the plurality of different websites and further based on a result of the classifying, the current mood of the user;
determining, based on the adjusted current mood of the user, one or more likelihoods of the user to be interested in the first digital content or the second digital content; and
causing a suggestion for the user to purchase one or more goods or services to be displayed on the user device based on the determined one or more likelihoods.
15. The non-transitory machine-readable medium of claim 14 , wherein the first interactions correspond to interactions from one or more previous browsing sessions, and wherein the second interactions correspond to interactions from a current browsing session.
16. The non-transitory machine-readable medium of claim 14 , wherein the first digital content or the second digital content comprises social networking content provided by a social network provider, the social network provider being one of the social networking entities.