Directly Software, Inc.

Directly, Inc.

The Dun Bradstreet Corporation

Hoover's Inc.

Jeff Patterson

Vlad Georgescu

Jean Tessier

Eugene Mandel

Scott Golubock

Antony Brydon

Stephen D Hsu

Ruben Kislaki

Jason Fama

Antony Fenwick Brydon

Tanausu Cerdeña

In a crowd sourcing approach, responses to customer service inquiries are provided by routing a subset of the inquiries to an independent group of experts. The customer service inquiries are optionally routed to specific experts based on matches between identified subject matter of the inquiries and expertise of the experts. Embodiments include methods of classifying customer service inquiries, training a machine learning system, and/or processing customer service inquiries. Multiple experts may provide responses to a particular customer service inquiry, optionally within a single chat window.

CRM including multi-thread messaging

In a crowd sourcing approach, responses to customer service inquiries are provided by routing the inquiries to an independent group of experts. Machine learning based systems are used in combination with contact center staff and/or the independent experts to resolve the customer service inquiries. The AI based systems can be configured to determine which of the customer service inquiries should be routed to the independent experts, and/or to generate content for inclusion in responses to the customer service inquiries. The machines systems are optionally trained based on scored responses to prior customer service inquiries. These scored responses can include content provided by a machine learning system and/or a human expert.

Al based CRM system

In a crowd sourcing approach, responses to customer service inquiries are provided by routing a subset of the inquiries to an independent group of experts. The customer service inquiries are optionally routed to specific experts based on matches between identified subject matter of the inquiries and expertise of the experts. Embodiments include an expert system configured to identify clusters of inquiries that can be responded to using predetermined response content. The expert system is optionally trained based on scored responses to prior customer service inquiries.

Cluster based CRM

In a crowd sourcing approach, responses to customer service inquiries are provided by routing a subset of the inquiries to an independent group of experts. The customer service inquiries are optionally routed to specific experts based on matches between identified subject matter of the inquiries and expertise of the experts. Embodiments include methods of classifying customer service inquiries, training a machine learning system, and/or processing customer service requests.

Methods of AI based CRM

In a crowd sourcing approach, responses to customer service inquiries are provided by routing a subset of the inquiries town independent group of experts. The customer service inquiries are optionally routed to specific experts based on matches between identified subject matter of the inquiries and expertise of the experts. Embodiments include an AI based system configured to determine which of the inquiries should be routed to the independent group of experts. The expert system is optionally trained based on scored responses to prior customer service inquiries.

Predictive routing

In a crowd sourcing approach, responses to customer service inquiries are provided by providing the inquiries to an independent group of experts. These experts are typically able to resolve the inquiry before the inquiries are routed to a traditional contact center. The customer service inquiries are routed to specific experts based on matches between identified subject matter of the inquiries and expertise of the experts. In some embodiments, more than one expert can contribute to the resolution of an inquiry.

Expert based customer service

Customer service routing

The present application describes systems and methods for Relationship Capital Management ('RCM'). An RCM system mines relationship capital, which it correlates to eliminate redundancies, that is made available for searching. An initial result set of the search may be narrowed to a single individual, e.g., the target. Weighted paths are identified that connect the user to the target, which may comprise one or more intermediaries between the two. Weighted paths are presented as maps, which may be embedded in other applications to improve business processes such as selling, marketing, hiring, etc. Selection of a path to the target initiates processing of requests for access to relationship capital and responses between the user and the one or more intermediaries. The processing of requests ultimately leads to the approval, conditional approval or denial of access to the relationship capital to which the user wishes to obtain access.

System and method for enforcing privacy in social networks

The present invention provides methods and systems for facilitating business processes in an enterprise application. The method according to one embodiment of the present invention comprises obtaining information regarding one or more entities and analyzing the information regarding the one or more entities to determine one or more paths between the one or more entities and one or more members of an enterprise. Information regarding the one or more entities is distributed to the one or more members of the enterprise where one or more paths exist between the one or more members of the enterprise and the one or more entities.

Growing community of inventors

Pleasant Hill, CA, United States of America

Jeff Patterson