# US 10,313,476 B2 · Systems and methods of audit trailing of data incorporation

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- Number: US 10,313,476 B2
- Document ID: US10313476B2
- Status: Granted
- Kind: B2
- Application number: 15/489,072
- Filed: 2017-04-17
- Published: 2017-08-03
- Granted: 2019-06-04
- Earliest claimed: 2012-03-08
- Assignees: salesforce.com, inc.
- Applicants: salesforce.com, inc.
- Inventors: Charlie Isaacs; Antony Passemard; Harish Peri; Seema Kumar
- Web page: https://patentgrep.com/patent/US10313476B2

## CPC

- H04L 67/306: User profiles
- G06F 16/9535: Search customisation based on user profiles and personalisation
- G06F 16/9536: Search customisation based on social or collaborative filtering
- G06F 21/604: {Tools and structures for managing or administering access control systems}
- G06F 21/62: Protecting access to data via a platform, e.g. using keys or access control rules
- G06Q 30/02: Marketing; Price estimation or determination; Fundraising
- H04L 63/10: {for controlling access to devices or network resources}
- H04L 63/102: {Entity profiles}
- H04L 63/20: {for managing network security; network security policies in general (filtering policies H04L63/0227)}
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

The technology disclosed relates to creating an audit trail of data incorporation in user profiles. In particular, it relates to linking trust objects to fields of the user profiles. The technology disclosed also relates to maintaining an opt trail that captures user opt-ins by recording the circumstances surrounding opt-in actions. In particular, it relates to linking trust objects to user profiles that connect users to an advertising campaign. The technology disclosed further relates to tracking and measuring reputation of product models in consumer markets. In particular, it relates to assembling consumer feedback on the product models from online social networks and service records of the product models and applying sentiment analysis on the consumer feedback.

## Claims

### Claim 1

A method of controlling flow of information from computer to computer using a database server, including:
maintaining opt trail fields in a trust object linked to a user profile that connects a target user to an information source of an information about a product or service, wherein the opt trail fields include information that assists the target user to recall circumstances in which the target user opted into the information source of the information about the product or service including a time, a date, and a location of an opt-in action;
providing information included in the opt trail fields to the target user;
receiving instructions setting a preference of the target user to continue or discontinue receipt of the information about the product or service from the information source of the information about the product or service and updating the trust object according to the preference; and
using the trust object updated, controlling sending of information by the information source of the information about the product or service to the target user based upon the preference stored in the trust object updated.

### Claim 2 (depends on 1)

The method of claim 1, further including:
appending reputation objects to data objects, wherein the data objects track product models after sales of products in consumer markets;
assembling consumer feedback on one or more of the product models, including receiving user generated content from online social networks that mentions the product models;
receiving service records of the product models;
automatically categorizing the consumer feedback based on sentiment analysis;
updating fields of the reputation objects based on the consumer feedback on the product models; and
using the fields updated of the reputation objects, providing the consumer feedback on the product models to target users that indicated in respective trust objects an interest in receiving information about the products.

### Claim 3 (depends on 2)

The method of claim 2, further including:
calculating one or more reputation metrics for the product models based on the reputation objects.

### Claim 4 (depends on 2)

The method of claim 2, wherein the sentiment analysis includes identifying tones and sentiments of consumers.

### Claim 5 (depends on 3)

The method of claim 3, further including:
categorizing the product models into reputation hierarchies based on the reputation metrics, wherein the reputation hierarchies stratify the products models into product families and product lots.

### Claim 6 (depends on 5)

The method of claim 5, further including:
automatically updating the reputation metrics of the product models in a reputation hierarchy responsive to changes in the reputation metrics of other product models in the reputation hierarchy.

### Claim 7 (depends on 1)

The method of claim 1, wherein the opt trail fields, for a voice opt-in, include:
a time and a date of a dispatch of a call soliciting the voice opt-in; and
information related to a device from which the opt-in action took place.

### Claim 8 (depends on 7)

The method of claim 7, wherein the opt trail fields, for the voice opt-in, further include a transcript of a conversation via which the voice opt-in was presented.

### Claim 9 (depends on 1)

The method of claim 1, wherein the opt trail fields, for an SMS opt-in, include:
a time and a date of a dispatch of an SMS soliciting the SMS opt-in;
a text of a message body via which the SMS opt-in was presented; and
information related to a device from which the opt-in action took place.

### Claim 10 (depends on 1)

The method of claim 1, wherein the opt trail fields, for an email opt-in, include:
a time and a date of a dispatch of an email soliciting the email opt-in;
a text of an email body via which the email opt-in was presented; and
information related to a device from which the opt-in action took place.

### Claim 11 (depends on 1)

The method of claim 1, wherein the opt trail fields, for a website opt-in, include:
a unified resource locator of a web site on which the web site opt-in occurred;
a history of activity of the target user on the website on which the website opt-in occurred;
a copy of a webpage via which the website opt-in was presented; and
information related to a device from which the opt-in action took place.

### Claim 12 (depends on 1)

The method of claim 1, wherein the opt trail fields, for a paper opt-in, include:
information that identifies an event at which the paper opt-in occurred; and
a particular medium via which the paper opt-in was presented.

### Claim 13

A non-transitory computer readable storage medium configured with instructions for controlling flow of information from computer to computer using a database server, which instructions, when executed by one or more processors, implement:
maintaining opt trail fields in a trust object linked to a user profile that connects a target user to an information source of an information about a product or service, wherein the opt trail fields include information that assists the target user to recall circumstances in which the target user opted into the information source of the information about the product or service including a time, a date, and a location of an opt-in action;
providing information included in the opt trail fields to the target user;
receiving instructions setting a preference of the target user to continue or discontinue receipt of the information about the product or service from the information source of the information about the product or service and updating the trust object according to the preference; and
using the trust object updated, controlling sending of information by the information source of the information about the product or service to the target user based upon the preference stored in the trust object updated.

### Claim 14 (depends on 13)

The non-transitory computer readable storage medium of claim 13, further including instructions that implement:
appending reputation objects to data objects, wherein the data objects track product models after sales of products in consumer markets;
assembling consumer feedback on one or more of the product models, including receiving user generated content from online social networks that mentions the product models;
receiving service records of the product models;
automatically categorizing the consumer feedback based on sentiment analysis;
updating fields of the reputation objects based on the consumer feedback on the product models; and
using the fields updated of the reputation objects, providing the consumer feedback on the product models to target users that indicated in respective trust objects an interest in receiving information about the products.

### Claim 15 (depends on 14)

The non-transitory computer readable storage medium of claim 14, further including instructions that implement:
calculating one or more reputation metrics for the product models based on the reputation objects.

### Claim 16 (depends on 14)

The non-transitory computer readable storage medium of claim 14, wherein the sentiment analysis includes identifying tones and sentiments of consumers.

### Claim 17 (depends on 15)

The non-transitory computer readable storage medium of claim 15, further including instructions that implement:
categorizing the product models into reputation hierarchies based on the reputation metrics, wherein the reputation hierarchies stratify the products models into product families and product lots.

### Claim 18 (depends on 17)

The non-transitory computer readable storage medium of claim 17, further including instructions that implement:
automatically updating the reputation metrics of the product models in a reputation hierarchy responsive to changes in the reputation metrics of other product models in the reputation hierarchy.

### Claim 19

A system for controlling information flow from computer-to-computer, comprising:
a processor coupled to a computer readable storage medium storing instructions, which instructions, when executed by the processor, cause the processor to perform:
maintaining opt trail fields in a trust object linked to a user profile that connects a target user to an information source of an information about a product or service, wherein the opt trail fields include information that assists the target user to recall circumstances in which the target user opted into the information source of the information about the product or service including a time, a date, and a location of an opt-in action;
providing information included in the opt trail fields to the target user;
receiving instructions setting a preference of the target user to continue or discontinue receipt of the information about the product or service from the information source of the information about the product or service and updating the trust object according to the preference; and
using the trust object updated, controlling sending of information by the information source of the information about the product or service to the target user based upon the preference stored in the trust object updated.

### Claim 20 (depends on 19)

The system of claim 19, wherein the computer readable storage medium further includes instructions that implement:
appending reputation objects to data objects, wherein the data objects track product models after sales of products in consumer markets;
assembling consumer feedback on one or more of the product models, including receiving user generated content from online social networks that mentions the product models;
receiving service records of the product models; automatically categorizing the consumer feedback based on sentiment analysis;
updating fields of the reputation objects based on the consumer feedback on the product models; and
using the fields updated of the reputation objects, providing the consumer feedback on the product models to target users that indicated in respective trust objects an interest in receiving information about the products.