System and method for providing a social customer care system
Social customer service and support systems integrated with social media and social networks are disclosed. A social customer care platform allows customer service agents to identify, prioritize, match and triage customer support requests that may arise through a social network and may be serviced using a social network. It manages and tracks a high-volume of customer interactions and provides for monitoring of Internet social network posts relevant to a business's products or services along with the ability to capture, monitor, filter, make sense of and respond to, in near real-time, tens of thousands of social interactions. It includes role specific user-interface and functionality for social customer service and support environments, automated prioritization and matching for increased agent productivity, and an automated enterprise workflow to align social media support with existing business processes.
1. A computer system comprising:
a processor;
a memory coupled to the processor;
a display device;
wherein the memory stores a program that automatically locates, identifies and unifies user profiles across Internet-based social network websites, when executed by the processor causes the processor to:
input a user profile and designating the user profile as a search subject;
extract user-identifying data attributes from the user profile;
search at least one Internet-based social network website for users with profiles containing data attributes similar to the search subject user-identifying data attributes;
identify a social network site profile for a third party from the social network website based on a closeness of a match of social network site profile attributes for the third party to the search subject user-identifying data attributes;
use the social network site profile attributes for the third party and the user-identifying attributes, running a scoring algorithm to produce a likelihood score that the third party and the search subject from the user profile is the same person;
if the likelihood score meets a certainty threshold criteria, use the social network site profile attributes for the third party and the user-identifying data attributes in the user profile for the search subject to search additional Internet-based social network websites for data for the search subject based on the social network site profile attributes user profiles and the user-identifying data attributes running the scoring algorithm to produce a likelihood score that the third party and the search subject from the user profile is the same person; and
a peer-to-peer enterprise workflow function that controls and coordinates the actions of the customer care system and its interactions with user, wherein the peer-to-peer enterprise workflow function controls input to and output from external systems and data stores;
in response to a user issue raised by the user, the peer-to-peer enterprise workflow function searches social media networks to find a resolution to the user issue;
a resolver matching function that automatically locates, identifies, consolidates and manages third party relevant social media network found resolutions to the user issue across the social media networks and stores the relevant social media network resolutions;
the peer-to-peer enterprise workflow function receives the stored relevant social media network found resolutions and sends the resolutions to the user issue to the user via the social media network without requiring agent-based support;
capture survey answers from at least two sources;
i) at least one first answer that includes at least one hashtag from at least one social media interaction, and
ii) at least one second answer from follow-up social network responses as determined by utilizing a language clustering pattern function to infer language detected within a follow-up answer that falls within a satisfaction range found in the at least one first answer that includes the at least one hashtag to compensate for the at least one second answer being unassociated with either the hashtag or a uniform resource locator for the at least one social media interaction; and
aggregate the captured survey answers from multiple communication channels and normalize the aggregated contents of the survey answers to rate the resolution to the user issue.
2. The computer system of claim 1 wherein the likelihood score is a total match score that uses scores selected from the group consisting of: an attribute score, a fuzzy match score, a friend overlap score and a concept overlap score.
3. The computer system of claim 1 further comprising repeating the searching, identifying and using steps for multiple databases resulting in a total match score for each social network site profile identified on the respective Internet-based social network.
4. A computer system comprising:
a processor;
a memory coupled to the processor;
a display device;
wherein the memory stores a program that automatically locates, identifies and unifies user profiles across databases, when executed by the processor causes the processor to:
input a user profile and designating the user profile as a search subject;
extract user-identifying data attributes from the user profile;
search at least one database for data for the search subject based on user profiles containing data attributes similar to the search subject user-identifying data attributes;
identify a third party profile from the database based on a closeness of a match of third party profile attributes for the third party to the search subject user-identifying data attributes;
use the third party profile attributes and the user-identifying data attributes, running a scoring algorithm to produce a likelihood score that the third party and the search subject from the user profile is the same person;
if the likelihood score meets a certainty threshold criteria, use the third party profile attributes for the third party and the user-identifying data attributes in the user profile for the search subject to search additional databases for data for the search subject based on the third party profile attributes and the user-identifying data attributes, running the scoring algorithm to produce a likelihood score that the third party and the search subject from the user profile is the same person;
a peer-to-peer enterprise workflow function that controls and coordinates the actions of the customer care system and its interactions with user, wherein the peer-to-peer enterprise workflow function controls input to and output from external systems and data stores;
in response to a user issue raised by the user, the peer-to-peer enterprise workflow function searches social media networks to find a resolution to the user issue;
a resolver matching function that automatically locates, identifies, consolidates and manages third party relevant social media network found resolutions to the user issue across the social media networks and stores the relevant social media network resolutions;
the peer-to-peer enterprise workflow function receives the stored relevant social media network resolutions and sends the resolutions to the user issue to the user via the social media network without requiring agent-based support; and
capture survey answers from at least two sources;
i) at least one first answer that includes at least one hashtag from at least one social media interaction, and
ii) at least one second answer from follow-up social network responses as determined by utilizing a language clustering pattern function to infer language detected within a follow-up answer that falls within a satisfaction range found in the at least one first answer that includes the at least one hashtag to compensate for the at least one second answer being unassociated with either the hashtag or a uniform resource locator for the at least one social media interaction; and
aggregate the captured survey answers from multiple communication channels and normalize the aggregated contents of the survey answers to rate the resolution to the user issue.
5. The computer system of claim 4 wherein the likelihood score is a total match score that uses scores selected from the group consisting of: an attribute score, a fuzzy match score, a friend overlap score and a concept overlap score.
6. The computer system of claim 4 further comprising repeat the search, and identify and use for multiple databases resulting in a total match score for each third party profile identified on the respective database.
7. The computer system of claim 4 wherein the database is a customer relationship management database.
8. The computer system of claim 4 wherein the database is a profile-type database.
9. The computer system of claim 4 further comprising compute a link relationship indicator that links the user profile for the search subject with the social network site profile for the third party.