Abstract:
The technology disclosed relates to enhancing trust for person-related data sources by tracking person-related sources using trust objects that hold trust metadata. In particular, it relates to generating trust-enhanced data by appending trust metadata to social media content and other business-to-business entities, and further using the trust-enhanced data to develop social engagement models based on customer preferences. The trust metadata described includes names, interface categories and origins of the person-related data sources along with customer engagement preferences and connection types.
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.
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.
Abstract:
The technology disclosed relates to enhancing trust for person-related data sources by tracking person-related sources using trust objects that hold trust metadata. In particular, it relates to generating trust-enhanced data by appending trust metadata to social media content and other business-to-business entities, and further using the trust-enhanced data to develop social engagement models based on customer preferences. The trust metadata described includes names, interface categories and origins of the person-related data sources along with customer engagement preferences and connection types.
Abstract:
The technology disclosed relates to incorporating social data in CRM systems by a single social syn action. In particular, it relates to appending social data to prospect or contact objects of CRM systems by finding multiple social handles for the prospect or contact objects. The multiple social handles identify social profiles of the corresponding prospects or contacts on various social network platforms.The technology disclosed also relates to personalizing customer service experience of customers. In particular, it relates to identifying conversation preferences and interests of the customers based on information specified in their social profiles on different social network platforms. The conversation preferences and interests are used to customize interactions with the customer during the course of the customer service.
Abstract:
The technology disclosed relates to automated compliance with data privacy laws of varying jurisdictions. In particular, it relates to constructing trust filters that automatically restrict collection, use, processing, transfer, or consumption of any person-related data that do not meet the data privacy regulations of the applicable jurisdictions. The trust filters are constructed dependent on associating person-related data entities with trust objects that track person-related data sources.
Abstract:
The technology disclosed relates to automated compliance with data privacy laws of varying jurisdictions. In particular, it relates to constructing trust filters that automatically restrict collection, use, processing, transfer, or consumption of any person-related data that do not meet the data privacy regulations of the applicable jurisdictions. The trust filters are constructed dependent on associating person-related data entities with trust objects that track person-related data sources.
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.
Abstract:
The technology disclosed relates to incorporating social data in CRM systems by a single social syn action. In particular, it relates to appending social data to prospect or contact objects of CRM systems by finding multiple social handles for the prospect or contact objects. The multiple social handles identify social profiles of the corresponding prospects or contacts on various social network platforms.The technology disclosed also relates to personalizing customer service experience of customers. In particular, it relates to identifying conversation preferences and interests of the customers based on information specified in their social profiles on different social network platforms. The conversation preferences and interests are used to customize interactions with the customer during the course of the customer service.