Initiation of purchase transaction in response to a reply to a recommendation

• US 10,346,895 B2
• Filed: 05/08/2015
• Issued: 07/09/2019
• Est. Priority Date: 05/17/2012
• Status: Active Grant

• Current Assignee: Walmart Apollo, LLC (WalMart Inc.)
• Original Assignee: Walmart Apollo, LLC (WalMart Inc.)
• Inventors: Stoll, Nathan, Ellerhorst, Andrew Mark
• Primary Examiner(s): Misiaszek, Michael
• Assistant Examiner(s): Ramphal, Latasha D
• Application Number:
  US14/708,069
• Publication Number:
  US 20150242931A1
• Time in Patent Office: 1,523 Days
• Field of Search: 705 64, 705 30, 705238, 705 26- 27
• CPC Class Codes: G06Q 30/0214 Referral reward systems
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 30/0635 Processing of requisition or of purchase orders
• CPC Class Codes: G06Q 30/0641 Shopping interfaces
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

In one embodiments, initiation of purchase transaction in response to a reply to a recommendation comprises a method. The method comprises, at a computer system having one or more processors and non-transitory memory storing one or more programs for execution by the one or more processors, detecting a recommendation associated with a first user, the recommendation associated with a product or service. The method further comprises detecting a response from a second user to the recommendation, determining whether the response from the second user comprises a purchase decision, and in accordance with a determination that the response from the second user comprises the purchase decision, initiating a transaction for the second user to purchase the product or service associated with the recommendation. Other embodiments are described herein.

Claims

1. A method of improving efficiency of initiating online purchases from recommendations, the method comprising:

at a server environment computer system having one or more processors and non-transitory memory storing one or more programs for execution by at least one of the one or more processors, the server environment computer system comprising at least a server system, wherein the server system comprises a recommendation system, a purchasing system, and a software application (“

app”

), wherein the software app is coupled to the recommendation system and the purchasing system, the software app configured to be installed on a mobile device of a first user, wherein the software app comprises a first communication system and a first user interface, wherein the recommendation system is configured to access the recommendations from users stored within a trust network of the first user, wherein the trust network comprises one or more levels of trust that the first user has for each user on the trust network, wherein the recommendations are based on categories for products or services, and wherein the recommendation system is configured to retrieve the recommendations from a content host without activating a second user interface of the content host, wherein the content host comprises a second communication system configured to receive and send the recommendations from the users within the trust network of the first user;

receiving, by a third communication system (a) of the recommendation system and (b) coupled to the software app via the first communication system and (c) from the second communication system of the content host without activating the second user interface of the content host, one or more recommendations of the recommendations for the products or services by the first user posted to the content host, wherein the content host comprises a networking service, to permit the first user and other users having the first user within their respective trust networks, and also to permit further users having the other users within their respective trust networks, to (a) view a recommendation of the one or more recommendations posted by the first user via the content host, (b) provide a response to the recommendation posted by the first user via the content host by at least a reply, a comment, a like, an upvote, or a share, and (c) view the response to the recommendation posted by the other users or the further users, wherein;

the other users determine a respective trustworthiness of the first user who is within the respective trust networks of the other users, wherein the respective trust networks of the other users comprise one or more levels of trust the other users have for each user on the respective trust networks of the other users, wherein the recommendations are based on the categories for the products or services;

the further users determine a respective trustworthiness of the other users who are within the respective trust networks of the further users, wherein the respective trust networks of the further users comprise one or more levels of trust the further users have for each user on the respective trust networks of the further users, wherein the recommendations are based on the categories for the products or services; and

a trustworthiness of the one or more recommendations by the first user for at least one of the further users is (a) the trustworthiness of the first user, as determined by at least one of the other users, multiplied by (b) the trustworthiness of the at least one of the other users, as determined by the at least one of the further users, such that the at least one of the other users is within a first level of the one or more levels of trust of the at least one of the further users, and such that the first user is within a second level of the one or more levels of trust of the at least one of the further users, and such that the first user is within a first level of the one or more levels of trust of the at least one of the other users;

detecting and receiving, by the recommendation system (a) coupled to the software app by the first communication system and (b) from the second communication system of the content host without activating the second user interface of the content host, a target response from a third user posted in reply to the recommendation from the first user, who is within a trust network of a second user, who is within a trust network of the third user, wherein the at least one of the further users comprises the third user and wherein the at least one of the other users comprises the second user;

determining, by the purchasing system, wherein the purchasing system comprises a fourth communication system coupled to the first communication system of the software app, whether the target response from the third user comprises a purchase decision regarding a desire to purchase a product or service, as recommended, by the first user via the content host, wherein the determining includes at least one of;

determining whether the target response comprises one or more predefined keywords;

determining whether the target response comprises one or more words from a set of words pre-determined by the third user to indicate the purchase decision;

or

using natural language processing; and

in accordance with determining that the target response from the third user comprises the purchase decision;

initiating, by the purchasing system to increase an efficiency of a purchase transaction of an online purchase for the third user to purchase the product or service associated with the recommendation from the first user, including;

retrieving, by the purchasing system, information required for the purchase transaction from a user profile associated with the third user comprising payment information;

when the information is sufficient to proceed with the purchase transaction, the purchasing system is further configured to proceed with the purchase transaction using the information, as received;

when the information is not sufficient to proceed with the purchase transaction the purchasing system is further configured to prompt the third user to provide missing information required for the purchase transaction;

confirming, by the purchasing system, the purchase transaction with the third user before finalizing the purchase transaction, wherein, during the confirming, the purchasing system is further configured to permit the third user to (a) edit details of the purchase transaction or (b) cancel the purchase transaction; and

when the third user has not canceled the purchase transaction during the confirming, identifying, by the purchasing system, a vendor listed in a vendor database that sells the product or service, to allow the third user to purchase the product or service through the purchasing system coupled to the software app; and

increasing, by the recommendation system coupled to the software app, a trust level from the third user toward the second user within the trust network of the third user after completing the purchase transaction for the third user.

2. The method of claim 1, wherein the server system further comprises:

storing, using the recommendation system, in a recommendation database, the recommendations by the first user, the other users, and the further users, wherein a portion of the recommendations by the first user are retained for a pre-set period of time based on at least one of a date of the portion of the recommendations by the first user, the respective trustworthiness of the first user, the other users, and the further users, or a popularity of the recommendation by the first user.

3. The method of claim 2, wherein the server system further comprises:

storing in the recommendation database, responses to the recommendation of the first user determined to comprise purchase decisions by the other users and the further users for a pre-set period of time.

4. The method of claim 1 further comprising ranking multiple recommendations based on the respective trustworthiness of the first user, wherein the recommendation associated with the first user is one of the multiple recommendations.

5. The method of claim 1, wherein the server system further comprises:

storing, using the recommendation system, in a recommendation database, the recommendations by the first user, the other users, and the further users, wherein a portion of the recommendations by the first user are retained for a pre-set period of time based on at least one of a date of the portion of the recommendations by the first user, the respective trustworthiness of the first user, the other users, and the further users, or a popularity of the recommendation by the first user; and

wherein the method further comprises;

ranking multiple recommendations based on the respective trustworthiness of the first user, wherein the recommendation associated with the first user is one of the multiple recommendations; and

determining whether the response comprises one or more predefined keywords, text, emoticons, or images.

6. The method of claim 5, wherein the information further comprises:

data describing connections of the first user, the other users, and the further users;

trust levels comprising opinions and recommendations of the first user, the other users, and the further users; and

an inferred trust information from an action of the first user, the other users, and the further users.

7. The method of claim 1, wherein the one or more recommendations of the recommendations for the products or services by the first user are posted to a content feed or collection of content items organized in chronological order.

8. A system, comprising:

an input device;

a video display;

one or more processors; and

one or more non-transitory memory storage storing computer instructions configured to run on the one or more processors comprising at least a server system, comprising a recommendation system, a purchasing system, and a software application (“

app”

), wherein the software app is coupled to the recommendation system and the purchasing system, the software app configured to be installed on a mobile device of a first user, wherein the software app comprises a first communication system and a first user interface, wherein the recommendation system is configured to access recommendations from users stored within a trust network of the first user, wherein the trust network comprises one or more levels of trust that the first user has for each user on the trust network, wherein the recommendations are based on the categories for products or services, and wherein the recommendation system is configured to retrieve the recommendations from a content host without activating a second user interface of the content host, wherein the content host comprises a second communication system configured to receive and send the recommendations from the users within the trust network of the first user, wherein the computer instructions, when executed, cause to be performed;

receiving, by a third communication system (a) of the recommendation system and (b) coupled to the software app via the first communication system and (c) from the second communication system of the content host without activating the second user interface of the content host, one or more recommendations of the recommendations for the products or services by the first user posted to the content host, wherein the content host comprises a networking service to permit the first user, and other users having the first user within their respective trust networks, and also to permit further users having the other users within their respective trust networks, to (a) view a recommendation of the one or more recommendations posted by the first user via the content host, (b) provide a response to the recommendation posted by the first user via the content host by at least a reply, a comment, a like, an upvote, or a share, and (c) view the response to the recommendation posted by the other users or the further users, wherein;

the other users determine a respective trustworthiness of the first user who is within the respective trust networks of the other users, wherein the respective trust networks of the other users comprise one or more levels of trust the other users have for each user on the respective trust networks of the other users, wherein the recommendations are based on the categories for the products or services;

the further users determine a respective trustworthiness of the other users who are within the respective trust networks of the further users, wherein the respective trust networks of the further users comprise one or more levels of trust the further users have for each user on the respective trust networks of the further users, wherein the recommendations are based on the categories for the products or services; and

a trustworthiness of the one or more recommendations by the first user for at least one of the further users is (a) the trustworthiness of the first user, as determined by at least one of the other users, multiplied by (b) the trustworthiness of the at least one of the other users, as determined by the at least one of the further users, such that the at least one of the other users is within a first level of the one or more levels of trust of the at least one of the further users, and such that the first user is within a second level of the one or more levels of trust of the at least one of the further users, and such that the first user is within a first level of the one or more levels of trust of the at least one of the other users;

detecting and receiving, by the recommendation system (a) coupled to the software app by the first communication system and (b) from the second communication system of the content host without activating the second user interface of the content host, a target response from a third user posted in reply to the recommendation from the first user, who is within a trust network of a second user, who is within a trust network of the third user, wherein the at least one of the further users comprises the third user and wherein the at least one of the other users comprises the second user;

determining, by the purchasing system, wherein the purchasing system comprises a fourth communication system coupled to the first communication system of the software app, whether the target response from the third user comprises a purchase decision regarding a desire to purchase a product or service, as recommended, by the first user via the content host, wherein the determining includes at least one of;

determining whether the target response comprises one or more predefined keywords;

determining whether the target response comprises one or more words from a set of words pre-determined by the third user to indicate the purchase decision;

or

using natural language processing; and

in accordance with determining that the target response from the third user comprises the purchase decision;

initiating, by the purchasing system to increase an efficiency of a purchase transaction of an online purchase for the third user to purchase the product or service associated with the recommendation from the first user, including;

retrieving, by the purchasing system, information required for the purchase transaction from a user profile associated with the third user comprising payment information;

when the information is sufficient to proceed with the purchase transaction, the purchasing system is configured to further proceed with the purchase transaction using the information, as received;

when the information is not sufficient to proceed with the purchase transaction the purchasing system is further configured to prompt the third user to provide missing information required for the purchase transaction;

confirming, by the purchasing system, the purchase transaction with the third user before finalizing the purchase transaction, wherein, during the confirming, the purchasing system is further configured to permit the third user to (a) edit details of the purchase transaction or (b) cancel the purchase transaction; and

when the third user has not cancelled the purchase transaction during the confirming, identifying, by the purchasing system, a vendor listed in a vendor database that sells the product or service, to allow the third user to purchase the product or service through the purchasing system coupled to the software app; and

increasing, by the recommendation system coupled to the software app, a trust level from the third user toward the second user within the trust network of the third user after completing the purchase transaction for the third user.

9. The system of claim 8, wherein the server system further comprises the computer instructions, when executed, cause to be performed:

storing, using the recommendation system in a recommendation database, the recommendations by the first user, the other users, and the further users, wherein a portion of the recommendations by the first user are retained for a pre-set period of time based on at least one of a date of the portion of the recommendations by the first user, the respective trustworthiness of the first user, the other users, and the further users, or a popularity of the recommendation by the first user.

10. The system of claim 9, wherein the server system further comprises:

storing in the recommendation database, responses to the recommendation of the first user determined to comprise purchase decisions by the other users and the further users for a pre-set period of time.

11. The system of claim 8, wherein the set of words comprises one or more predefined keywords, text, emoticons, or images.

12. The system of claim 8, further comprising ranking multiple recommendations based on the respective trustworthiness of the first user, wherein the recommendation associated with the first user is one of the multiple recommendations.

13. The system of claim 8 wherein the one or more non-transitory memory storage storing the computer instructions are further configured to run on the one or more processors and to rank multiple recommendations based on the respective trustworthiness of the first user, wherein the recommendation associated with the first user is one of the multiple recommendations.

14. The system of claim 8, wherein the server system further comprises:

storing in a recommendation database, the recommendations by the first user, the other users, and the further users, wherein a portion of the recommendations by the first user are retained for a pre-set period of time based on at least one of a date of the portion of the recommendations by the first user, the respective trustworthiness of the first user, the other users, and the further users, or a popularity of the recommendation by the first user; and

wherein the computer instructions, when executed further cause to be performed;

determining whether the response comprises one or more predefined keywords, text, emoticons, or images; and

to rank multiple recommendations based on the respective trustworthiness of the first user, wherein the recommendation associated with the first user is one of the multiple recommendations.

15. The system of claim 8, wherein the one or more recommendations of the recommendations for the products or services by the first user are posted to a content feed or collection of content items organized in chronological order.

16. A non-transitory computer readable storage medium storing one or more programs configured for execution by an electronic device, the one or more programs comprising instructions for:

receiving a software application (“

app”

) coupled to a recommendation system and a purchasing system, the software app configured to be installed on a mobile device of a first user, wherein the software app comprises a first communication system and a first user interface, wherein the recommendation system is configured to access recommendations from users stored within a trust network of the first user, wherein the trust network comprises one or more levels of trust that the first user has for each user on the trust network, wherein the recommendations are based on the categories for products or services, and wherein the recommendation system is configured to retrieve the recommendations from a content host without activating a second user interface of the content host, wherein the content host comprises a second communication system configured to receive and send the recommendations from the users within the trust network of the first user;

receiving, by a third communication system (a) of the recommendation system and (b) coupled to the software app via the first communication system and (c) from the second communication system of the content host without activating the second user interface of the content host, one or more recommendations of the recommendations for the products or services by the first user posted to the content host, wherein the content host comprises a networking service to permit the first user and other users having the first user within their respective trust networks, and also to permit further users having the other users within their respective trust networks, to (a) view a recommendation of the one or more recommendations posted by the first user via the content host, (b) provide a response to the recommendation posted by the first user via the content host by at least a reply, a comment, a like, an upvote, or a share, and (c) view the response to the recommendation posted by the other users or the further users, wherein;

the other users determine a respective trustworthiness of the first user who is within the respective trust networks of the other users, wherein the respective trust networks of the other users comprise one or more levels of trust the other users have for each user on the respective trust networks of the other users, wherein the recommendations are based on the categories for the products or services;

the further users determine a respective trustworthiness of the other users who are within the respective trust networks of the further users, wherein the respective trust networks of the further users comprise one or more levels of trust the further users have for each user on the respective trust networks of the further users, wherein the recommendations are based on the categories for the products or services; and

a trustworthiness of the one or more recommendations by the first user for at least one of the further users is (a) the trustworthiness of the first user, as determined by at least one of the other users, multiplied by (b) the trustworthiness of the at least one of the other users, as determined by the at least one of the further users, such that the at least one of the other users is within a first level of the one or more levels of trust of the at least one of the further users, and such that the first user is within a second level of the one or more levels of trust of the at least one of the further users, and such that the first user is within a first level of the one or more levels of trust of the at least one of the other users;

detecting and receiving, by the recommendation system (a) coupled to the software app by the first communication system and (b) from the second communication system of the content host without activating the second user interface of the content host, a target response from a third user posted in reply to the recommendation from the first user, who is within a trust network of a second user, who is within a trust network of the third user, wherein the at least one of the further users comprises the third user and wherein the at least one of the other users comprises the second user;

determining, by the purchasing system, wherein the purchasing system comprises a fourth communication system coupled to the first communication system of the software app, whether the target response from the third user comprises a purchase decision regarding a desire to purchase a product or service, as recommended by the first user via the content host, wherein the determining, includes at least one of;

determining whether the target response comprises one or more predefined keywords;

determining whether the target response comprises one or more words from a set of words pre-determined by the third user to indicate the purchase decision;

or

using natural language processing; and

in accordance with determining that the target response from the third user comprises the purchase decision;

initiating, by the purchasing system to increase an efficiency of a purchase transaction of an online purchase for the third user to purchase the product or service associated with the recommendation from the first user, including;

retrieving, by the purchasing system, information required for the purchase transaction from a user profile associated with the third user comprising payment information;

when the information is sufficient to proceed with the purchase transaction, the purchasing system is further configured to proceed with the purchase transaction using the information, as received;

when the information is not sufficient to proceed with the purchase transaction the purchasing system is further configured to prompt the third user to provide missing information required for the purchase transaction; and

confirming, by the purchasing system, the purchase transaction with the third user before finalizing the purchase transaction, wherein, during the confirming, the purchasing system is further configured to permit the third user to (a) edit details of the purchase transaction or (b) cancel the purchase transaction; and

when the third user has not cancelled the purchase transaction during the confirming, identifying, by the purchasing system, a vendor listed in a vendor database that sells the product or service, to allow the third user to purchase the product or service through the purchasing system coupled to the software app; and

increasing, by the recommendation system coupled to the software app, a trust level from the third user toward the second user within the trust network of the third user after completing the purchase transaction for the third user.

17. The non-transitory computer readable storage medium of claim 16, wherein the one or more programs further comprising instructions for:

storing in a recommendation database, the recommendations by the first user, the other users, and the further users, wherein a portion of the recommendations by the first user are retained for a pre-set period of time based on at least one of a date of the portion of the recommendations by the first user, the respective trustworthiness of the first user, the other users, and the further users, or a popularity of the recommendation by the first user.

18. The non-transitory computer readable storage medium of claim 17, wherein the one or more programs further comprising an instruction for:

storing in the recommendation database, responses to the recommendation of the first user determined to comprise purchase decisions by the other users and the further users for a pre-set period of time.

19. The non-transitory computer readable storage medium of claim 16, wherein the one or more programs further comprising instructions for:

storing in a recommendation database, the recommendations by the first user, the other users, and the further users, wherein a portion of the recommendations by the first user are retained for a pre-set period of time based on at least one of a date of the portion of the recommendations by the first user, the respective trustworthiness of the first user, the other users, and the further users, or a popularity of the recommendation by the first user; and

wherein the one or more programs further comprise instructions for;

determining whether the response comprises one or more predefined keywords, text, emoticons, or images; and

to rank multiple recommendations based on the respective trustworthiness of the first user, wherein the recommendation associated with the first user is one of the multiple recommendations.

20. The non-transitory computer readable storage medium of claim 16, wherein the one or more recommendations of the recommendations for the products or services by the first user are posted to a content feed or collection of content items organized in chronological order.