SYSTEMS AND METHODS FOR CUSTOMER RELATIONSHIP MANAGEMENT

Abstract

According to various exemplary embodiments, a social media message posted by a user on a social media system is accessed, and a prioritization level is determined based on the social media message. The prioritization level may indicate a measurement of importance of the social media message. Further, the social media message may be inserted into a prioritized message queue, based on the determined prioritization level associated with the social media message.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the priority benefits of U.S. Provisional Application No. 61/618,541 , filed Mar. 30, 2012 and U.S. Provisional Application No. 61/646,052, filed May 11, 2012 which are both incorporated herein by reference in their entirety.

TECHNICAL FIELD

This patent document pertains generally to tools for customer service, and more particularly, but not by way of limitation, to systems and methods for customer relationship management.

BACKGROUND

In conventional approaches to customer service, customer relationship management (“CRM”) call centers of companies receive customer inquiries via traditional channels of communication, such as telephone calls and emails. The customer service agents of the company typically respond to the customers via the same channels of communication, which allows the company to address any customer issues with a degree of privacy and confidentiality.

Now, a new channel for expressing customer issues is emerging—the Social Media space. For example, many companies and other organizations have their own social media presence, such as a TWITTER® feed, or a FACEBOOK® page with a wall, such that users can post messages regarding that company and its products that are widely viewable.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings in which:

FIG. 1 is a schematic diagram depicting a data flow, within which one example embodiment may be deployed.

FIG. 2 is a block diagram of an example system, according to various embodiments.

FIG. 3 is a block diagram of a social activity management platform, according to various embodiments.

FIG. 4 is a block diagram of a database, according to various embodiments.

FIG. 5 illustrates an example portion of a user interface, according to various embodiments.

FIG. 6 illustrates an example portion of a user interface, according to various embodiments.

FIG. 7 illustrates an example portion of a user interface, according to various embodiments.

FIG. 8 illustrates an example portion of a user interface, according to various embodiments.

FIG. 9 is a flowchart illustrating an example method, according to various embodiments.

FIG. 10 is a flowchart illustrating an example method, according to various embodiments.

FIG. 11 illustrates an example of social media identity information and an example of an internal customer record, according to various embodiments.

FIG. 12 illustrates an example portion of a user interface, according to various embodiments.

FIG. 13 illustrates an example portion of a user interface, according to various embodiments.

FIG. 14 is a flowchart illustrating an example method, according to various embodiments.

FIG. 15 is a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.

DETAILED DESCRIPTION

In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of some example embodiments. It may be evident, however, to one skilled in the art that the present invention may be practiced without these specific details.

Overview

A “social activity management system” described in various

embodiments may receive social media postings from social media users and facilitate the management of a company's resources to resolve the problems that are described in the social media postings. The description of problems in the social media postings may be related to a company's products/services. The problems may be resolved by utilizing the resources of the social activity management system including agents, experts, local and third party knowledgebases as well as a multiplicity of internal systems that facilitate the prioritization, management, and resolution of customer problems. To this end, the social activity management system (also referred to as “Service OnDemand” throughout this disclosure) may be utilized to manage interactions with the customer until the problem is resolved.

FIG. 1 is a schematic diagram depicting a data flow with respect to various social activity management systems, such as the aforementioned social activity management system. In particular, FIG. 1 illustrates user case scenarios 10 anticipated in the utilization of the social activity management system to resolve customer problems. The user case scenarios 10 may include social media systems 22 (e.g., social media platforms or social networking platforms) on the left and a social activity management system 26 on the right. A typical problem resolution is illustrated. Broadly, a customer 101 on the left posts a social media message (such as a “social feed” 102 about a problem) to the social media systems 22 that, in turn, communicate the social media message 102 to the social activity management system 26 where it is analyzed and prioritized 103 before being inserted into a queue. A service agent 104 may review the queue and assign the social media message to his/her self for resolution. The service agent 104 may clarify the problem by utilizing the social media systems 22 to further communicate with the customer in 105, where the customer may participate in this discussion in 106. Not shown are various systems/services that the service agent 104 may utilize to resolve the problem and provide a solution at 107. These systems are briefly described below and extensively described later in this disclosure. Towards resolution of the problem, the service agent may invite a support engineer 108 to collaborate in 109, where the support engineer 108 may accept the collaboration request at 110. The support engineer 108 may accept the invitation to collaborate at 110 and collaborate with the service agent at 111 in finding a solution to the problem at 107. Finally, the solution may be communicated in social media to the customer at 112. While the service agent 104 and support engineer 108 are shown as being external to the social activity management system 26 in FIG. 1, such agents and engineers may also be viewed as being included in the social activity management system 26, as described in more detail below.

FIG. 2 is a block diagram illustrating a customer relationship management system 20, according to an embodiment that may be implemented to address the previously described user case scenarios 10 (see FIG. 1). The customer relationship management system 20 may include the social media systems 22 (e.g., social media platforms or social networking platforms), a network 24 (e.g., Internet), and the social activity management system 26. The social media system 22 may be utilized by social media users (e.g., users) who operate client computers (not shown) that are connected over the network 24 with the social media system 22 to exchange social media messages/postings with the social activity management system 26. The social media system 22 may be embodied as FACEBOOK®, a social networking service and website launched in February 2004, operated and privately owned by Facebook Inc. of Menlo Park, Calif. or TWITTER®, an online social networking service and microblogging service that enables its users to send and read text-based posts of up to 140 characters, known as “tweets,” operated by Twitter Inc. of San Francisco, Calif. A social media message may be communicated by the customer via one of multiple portals on the social media system 22 (e.g., company wall etc.) to a particular company and describe a problem with a product or service that is provided by the company. The social media system 22, in turn, may communicate the social media message over the network 24 to the social activity management system 26.

The social activity management system 26 may include a social activity management platform 28 that is coupled to a database 30, and a third party system 32 that is coupled to another database 34. The social activity management platform 28 may communicate over the network 24 with the social media system 22, the third party system 32, and company personal 31 (e.g., service agent) who operate client computers that are connected with the social activity management platform 28. The social activity management platform 28 is further shown to be coupled to a database 30 that stores information.

The social activity management system 26 may communicate contextual content in a single user interface. For example, content identified by the social activity management system 26 (e.g., similar messages, knowledgebase articles, product, customer) may be included in a single user interface, as described in various embodiments below.

FIG. 3 is a block diagram illustrating the social activity management, platform 28, according to an embodiment. The social activity management platform 28 may include a prioritized message queue 28a that includes social media messages 28a 1, 28a2, 28a3, etc., as well as multiple systems 2811-2818 respectively including hardware or software modules 2811a-2818a that are utilized to manage social media messages, a communication module 2819 that is utilized to communicate with the social media system 22 and a text analysis system 2820, as described below. The systems 2811-2818 may include a queue prioritization system 2811 that includes a queue prioritization module 2811a, a customer identification system 2812 that includes a customer identification module 2812a, a similar message system 2813 that includes a similar message module 2813a, a recommended knowledgebase system 2814 that includes recommended knowledgebase module 2814a, an interaction history system 2815 that includes an interaction history module 2815a, a collaboration system 2816 that includes a collaboration module 2816a, an expert finder system 2817 that includes an expert finder module 2817a, and a consistent experience system 2818 that includes a consistent experience module 2818a.

The queue prioritization system 2811 may be utilized to provide auto prioritization of the message queue containing incoming social media messages to help agents focus on high profile customers and key issues. The queue prioritization system may be utilized to evaluate incoming social media messages based on different parameters including but not limited to customer influence, message sentiment, customer level and service level agreement (SLA). These parameters may be computed into a single priority score which determines and assigns a priority (e.g., Urgent, Normal and Low) to each message.

The customer identification system 2812 may be utilized to automatically identify the customer and create a customer record in the database 30. The customer record may be created with information in the customers' social profile. The customer identification system may further map the social customer identity (e.g., social media system identity) to an internal customer record. If there are multiple customers with same name, the customer identification system may display a list of matching customers thereby enabling a service agent to identify a customer based on the available information.

The similar message system 2813 may be utilized to display messages that are similar to the social media message that is presently being processed by the service agent. The similar message may include a response/solution that may be applicable to the social media message and utilized by the service agent to resolve the problem.

The recommended knowledgebase system 2814 may be utilized to recommend articles and other documents to the customer that may be helpful in resolving the problem of the customer. The recommended knowledgebase system may utilize the text analysis system 2820 to perform a text analysis and keyword identification of the social media message to identify a product and issue(s) in the social media message. The recommended knowledgebase system 2814 may utilize the identified product and issue to provide a recommendation of articles to the customer that may be attached as links in a response that is communicated to the customer. The recommended knowledgebase system 2814 may retrieve articles from a knowledgebase repository 3004 that is stored on the database 30 (see FIG. 4) or, via the third party system 32, from a knowledgebase repository that is stored on the database 34 (see FIG. 3).

The interaction history system 2815 may be utilized to respond to the customer, takes notes and collaborate internally with other agents in such a way that all the information is recorded to show a complete history of interactions with the customer in a chronological order. Accordingly, reassignment of the social media message to another agent or escalation to another agent may not hinder the newly assigned agent in responding to the customer because the newly assigned agent may utilize the history of interactions.

The collaboration system 2816 may be utilized to locate specific colleagues and then collaborate with them to resolve the problem described in the social media message. The collaboration system 2816 may ensure that all collaborators have access to information regarding the problem described in the social media message. The collaboration system 2816 may further ensure that interactions between collaborators are contained within the interaction history associated with the social media message.

The expert finder system 2817 may be utilized to automatically identify and present a list of experts that are available to the company based on the text analysis of social media message. The expert finder system 2817 may utilize the text analysis system 2820 to identify the product and other keywords mentioned in the social media message and provide a list of recommended experts within the context of the social media message.

The consistent experience system 2818 may be utilized to automatically aggregate information about the social media messages, other types of messages (e.g., email, telephone, etc.), and interaction history for a particular customer and automatically present this information to the service agent.

According to various embodiments, the above described aspects and/or functions of each of the systems 2811-2818 may be performed and/or implemented by the modules 2811a-2818a, respectively (see FIG. 3), which may correspond to hardware modules or software modules executed by one or more processors.

FIG. 4 is a block diagram illustrating the database 30, according to an embodiment. The database 30 may store customer information 3001, company resource information 3002, product information 3003, a knowledgebase repository 3004, configuration information 3005 and message information 3006. The customer information 3001 may be customer records that include information that describe the customer (e.g., identity information) and information that, describes interactions with the customer. The company resource information 3002 may include a personal profile for each of the employees of the company including the domains in which a particular employee has acquired knowledge that may be useful in resolving problems and a level of sufficiency for each of the domains. The product information 3003 may include product catalogues including profiles describing products. The knowledgebase repository 3004 may be utilized to store articles and other documents that may be communicated to customers to facilitate a resolution of a problem. The configuration information 3005 may include parameters that may be configured by an administrator of the social activity management platform, to customize one of the above mentioned systems.

1: Queue Prioritization

In current customer relationship management systems, customer service agents (e.g. call center agents) of a company have no way to prioritize the large number of social media messages of the company, such as messages posted on the FACEBOOK® or TWITTER® pages.

Moreover, companies tend to deal with such customer issues in an ad-hoc manner. For example, often it is not customer service agents, but rather information technology (IT) and/or marketing staff that monitor the social media space for customer feedback and messages regarding the company and it's products. Moreover, the staff may have to access multiple internal and external systems to gather information and respond appropriately. In addition, the staff are forced to monitor the company's social media profile by attempting to parse through all of the messages and posts from customers regarding the company, which may become extremely time consuming. Moreover, once the company's staff does find a customer issue, they may copy the customer's messages and pass it on to other customer service representatives, in an informal, ad-hoc process. Thus, the social media messages of the customer are not routed to customer service agents in a formal, consistent, efficient and transparent manner nor are they automatically prioritized to facilitate triage by the customer service agents.

According to an exemplary embodiment described herein, a queue prioritization system 2811 of a customer relationship management system 20 automatically prioritizes a set of incoming social media messages into a prioritized queue of messages, to help agents identify and triage problems for resolution. For example, the high priority messages may be identified to address the most important products or issues, or those messages originating from customers identified as important or customers identified as having the greatest influence in one or more social media systems.

Broadly, the queue prioritization system 2811 may receive incoming social media messages, and then automatically evaluate the incoming messages for their importance using one or more procedures and based on one or more parameters including message source, message sentiment, message following, customer influence, customer level, customer service level agreement product classification, problem level, and social amplification. All of the above mentioned parameters may be utilized to compute a single overall message score for a message which, in turn, may be utilized to assign apriority level (e.g. Urgent, Normal and Low) to the message.

The queue prioritization system 2811 first collects and accesses all customer messages and posts relevant to a company. For example, in one embodiment, the communication module 2819 may crawl through all the social media messages posted on a social media system 22 (e.g., social media platform) such as FACEBOOK® and TWITTER® that refer to the company or its products, and/or crawl through all the messages/posts on the company's own stream, page or wall. In yet another embodiment, the communication module 2819 may retrieve or be fed the messages from application programming interfaces that are exposed by the respective social medial platforms. Thereafter, the queue prioritization system 2811 may analyze each message to determine an overall message score for the message. The queue prioritization system 2811 may utilize the overall message score may to determine a priority level indicating the message's importance, using a combination of the above mentioned parameters as follows:

1.) Message Source: The queue prioritization system 2811 may determine a message source score based on a location in a social media system 22 (e.g., social networking platform). For example, if the message is posted on a user's own social networking page then the message may have a lower score than if it is posted on one of the social networking pages that are owned by a company. In addition, a specific social networking page of the company may further be utilized to determine the score associated with the message source. For example, if the message is posted on a product support page of the company (or a product-specific page or service-specific page of the company) the score may have a lower importance than if it is posted directly on the main social network profile page that is associated with the company. Accordingly, a message source score may be factored into the overall determination of the overall message score of the message.

2) Message Sentiment: The queue prioritization system 2811 may utilize text analysis system 2820 to perform a text analysis (e.g. words) of the message to determine a message sentiment score. For example, the system may include a list or database of words or phrases such as “disappointed”, “angry”, “waiting, ” “junk,” and “excellent” to determine the sentiment of the author of the message. Words or phrases that signify a bad or poor sentiment may result in a message sentiment score that contributes towards a higher overall message score, rather than words or phrases that are neutral or positive. For example, the identification of a bad or poor sentiment may result in a higher message sentiment score and higher overall message score that causes the message to be assigned to an agent more quickly and processed with greater urgency. On the other hand, a good sentiment may result in a lower message sentiment score and lower overall message score that results in a greater amount of time for assignment and resolution.

According to various exemplary embodiments, a similar type of message sentiment score may also be calculated for other comments responding to the original social media message, such as an average message sentiment score indicating the average sentiment of all the comments responding to the original social media message. This message sentiment score for responses/comments to the original social media message may also be factored into the determination of the message sentiment score and/or the overall message score for the original social media message. For example, the identification of bar or poor sentiment in the response comments may result in a higher message sentiment score and/or overall message score for the message that causes the message to be assigned to an agent more quickly and processed with greater urgency.

According to various exemplary embodiments, a social sentiment aggregate score indicating a history of the sentiment of the user's other messages posted on social media platforms may be generated. This social sentiment aggregate score may also be factored into the determination of the message sentiment score and/or overall message score for the original social media message.

According to various exemplary embodiments, an internal sentiment aggregate score indicating a sentiment of the user's other private communications with a specific company (e.g., complaints, requests for service, customer feedback) may be generated. This internal sentiment aggregate score may also be factored into the determination of the message sentiment score and/or overall message score for the original social media message.

3) Message Following: The queue prioritization system 2811 may determine a message following score of the message/post based on a number of views, feedback indicators (e.g., “likes”), messages, follow-up comments, shares, reposts, etc. that are posted by other users in association with the original message. For example, other messages posted in association with the original message may include a quantity of messages authored by other users that “like” the message/post, “share” the message/pest, re-post the message/post, “follow” the message/post, view the message/post and so on. The message following score may also take into account a number of views, likes, comments, or other feedback associated with the comments to the original message. The queue prioritization system 2811 may access an application programming interlace that is provided by a social networking platform to retrieve such information. Based on this information, the system may determine a message following score of the message and this information may be factored into the overall message score.

4) Problem Classification: The queue prioritization system 2811 may utilize text analysis system 2820 to perform a text analysis of the content (e.g. words) of the social media message, in order to determine a problem classification or issue that is communicated in the message. For example, the queue prioritization system 2811 may access multiple lists of known problem classification words that are stored en the database 30. A list for identifying a malfunctioning classification may include words such as “broken”, “fix”, “troubleshooting,” “documentation” and so forth that, if identified in the message with the text analysis system 2820, may be utilized to associate the message with a problem classification type for a malfunctioning product. Similarly, the queue prioritization system 2811 may access a list for identifying an overpricing classification and may include words, such as “expensive”, “overpriced”, “ripoff” and so forth that, if identified in the message with the text analysis system 2820 may be utilized to associate the message with a problem classification type for an overpriced product. A particular problem classification (e.g., “malfunctioning product”) may result in a problem classification score that contributes towards a higher message score rather than another problem classification (e.g., “overpriced product”), based on the severity of the problem reported in the message. Accordingly, the problem classification score may be used by the queue prioritization system 2811 to prioritize the type of problem related in the message, whether it is a minor problem or major problem, etc., and may be factored into the determination of the message score.

5) Product Classification: The queue prioritization system 2811 may utilize text analysis system 2820 to perform a text analysis of the content (e.g. words) of the message, in order to determine a particular product that is the subject of the message. For example, the queue prioritization system 2811 may access a list that is stored in the database 30 and utilize words or phrases in the list that describe known products such as “TV”, “processor”, “camera” and so forth that, if identified in the message with the text analysis system 2820 may contribute towards the identification of a particular product classification that is associated with the message. Further, for example, the system may include a list of words or phrases that describe model numbers or signature features that contribute towards the identification of the particular product classification such as “ZOS600D,” “auto-lighting optimizer,” or “ZX7000D.” One product classification may result in a higher product classification score as compared to another product classification. For example, a product classification score for a recently released product may be greater than a product classification score for a product that has been in the field for an extended period of time and considered stable. Accordingly, the product classification score may be used by the queue prioritization system 2811 to prioritize the type of product related in the message and factored into the determination of the overall message score.

6) Customer Level: The queue prioritization system 2811 may determine the customer level of the customer based on the identity of the customer that authored the message. The queue prioritization system 2811 may determine the identity of the customer by, for example, utilizing, the text analysis system 2820 to perform a text analysis of the message to identify social media identity information for the customer (e.g. name, telephone number, facsimile number, email address, username, etc.), which may be compared to a database of individuals, such as directory, or the company's own database of customer records to identify the customer. In yet another embodiment the queue prioritization system 2811 may access an application programming interface that is provided by the social media system 22 to retrieve the social media identity information for the user as registered on the social media system 22 based on a message identifier or some other identification information obtained from a text analysis of the message.

Once the customer is identified, the queue prioritization system may also determine the internal or external importance of the customer. Internal importance refers to the importance of the customer, based on their specific relations with the organization. For example, many companies may store information or history regarding known customers in an internal customer record or customer relationship management (CRM) record (e.g., how long has the user been a customer, what is the quantity of products/services they have procured from the company, a user's previous purchase history with respect to the company, what is the sentiment history of messages/posts from the customer, etc.), which may be used to determine an internal importance of the customer. Also for example, the internal importance of the customer may be represented in internal customer records as a customer level (e.g., platinum, gold, sliver, etc.) that may be associated with a score that may be used to compute a customer level score.

External importance of the customer, notwithstanding any specific relationship the customer may have with the organization, may further be identified and utilized by the queue prioritization system 2811 to identify a customer level. For example, even if the customer has never conducted business with the company before, the queue prioritization system 2811 may crawl a database or network (such as web pages accessible via the world wide web) for Information regarding the customer. Depending on the quantity, sources and nature of information received, the queue prioritization system 2811 may determine that the customer is an “externally important” individual (e.g. a politician, celebrity, high profile business executive, etc.) that is associated with a score that may be used to compute a customer level score.

Based on this information, the queue prioritization system 2811 may identify a score for the customer level of the customer that posted the message, and this customer level score may be factored into the determination of the overall message score of the message.

7) Customer Influence: The queue prioritization system 2811 may determine a score for customer influence of the customer that approximates the influence of the customer on various social media systems 22 (e.g., social networking platforms). The queue prioritization system 2811 may determine the customer influence score based on criteria that may or may not be tied to the particularities of a message. Such criteria may include the number of “friends”, “followers”, “fans”, etc., of the customer in one or more of the social media systems 22. This is an important factor in the social media space for the reason that the quantity of friends, followers or fans of the user may indicate their influence and ability to spread their opinions to other users. Accordingly, customer service agents may enhance the public image of their company by addressing the concerns of such people in a timely fashion. The queue prioritization system 2811 may access an application programming interface that is provided by a social media system 22 to retrieve such information. Based on this information, the queue prioritization system 2811 may determine a score for the customer influence of the customer that approximates the influence of the customer on social networking platforms, and this score may be factored into the determination of the overall message score of the message. A Klout score may be used as the customer influence score.

According to various embodiments, the queue prioritization system 2811 may determine an aggregate social influence score which may be similar to the customer influence described above, except that it applies to the importance or social influence of the users that commented, liked, re-tweeted, or provided other feedback or comments associated with the original message. This aggregate social influence score may also be factored into the determination of the overall message score for the original social media message.

8) Customer Service Level Agreement: The queue prioritization system 2811 may determine a customer service level agreement for a customer based on the identity of the customer. For example, the queue prioritization system 2811 may utilize the identify of the customer, as described above, to identity an internal customer record that includes a service level agreement that is associated with the customer. A customer who pays a premium for service may be associated with a higher service level agreement score than one who pays less thereby entitling the customer to immediate or enhanced access to agents. For example, in one embodiment, a service level agreement may be characterized as “Very important Customer” (VIC), “Important Customer” (IC) and “Valued Customer” (VC). Accordingly, the queue prioritization system 2811 may determine a customer service level agreement score for the message that may be factored into the determination of the overall message score of the message.

9) Social Amplification: The queue prioritization system 2811 may determine a social amplification score of the message/post based on a number of same or similar messages/posts as reported by other users on social media systems. For example, the problem and product classification for the present message may be utilized to identify a quantity messages that are received on the same or other social networking problems that report the same or similar problem, deal with the same or similar product or service, etc. Accordingly, the queue prioritization system 2811 may determine a social amplification score for the message that may be factored into the determination of the message score of the message.

The various parameters scores for each of the aforementioned parameters may each be associated with a weight that may be individually configured to customize the computation of respective weighted scores that are utilized to compute the overall message score for the message. Alternatively, the various parameters scores may each be associated with a default weight for the computation of respective weighted scores. In one embodiment, a parameter score may be multiplied by its associated weight before the product of the multiplication is utilized to compute the overall message score.

For example, FIG. 5 illustrates an example of a user interface screen 500, according to an embodiment. The user interface 500 may be displayed by the queue prioritization system 2811 to enable a user (such as a customer service agent) to adjust weighting for each of the aforementioned parameter scores (e.g., message source score, message sentiment score, message following score, problem classification score, product classification score, customer level score, customer influence score, customer service level agreement score, and social amplification score). The user interface 50 may be utilized to increase or decrease the importance of each parameter score relative to the other parameter scores. For example, the user interface 500 lists a parameter score (e.g., 501) for each of the aforementioned parameters, which in the example of FIG. 5 is a number from 0 to 2 (e.g., 0 corresponding to a low priority), (e.g., 1 corresponding to a medium priority), and (e.g., 2 corresponding to a high priority). The user interface 500 may also include slide rules (e.g., 502) allowing the user to adjust the weight for each parameter score (e.g., a weighting from 0 to 1), and also indicates the weighted score (e.g., 503) for each parameter (e.g., the customer influence score of 2 multiplied by the weight of 0.5 produces the weighted score of 1). Configuring a weight to 0 turns off a parameter, configuring a weight to 0.5 gives the parameter half of the importance relative to other weights of 1, and configuring a weight to some number greater than 1 (not shown in the user interface 500) may proportionally increase the importance of a particular parameter relative to other weights of 1.

In one embodiment the overall message score for the message may be the sum of each of the weighted parameter scores (i.e., the sum of each of the parameter scores multiplied by each of the associated weights). For example, as seen in FIG. 5, the overall message score 504 is 12/15, since the maximum possible score given the user-adjusted weights is (2×7)+(1×1)+(1×0)=15, and the overall message score is (2+2+2+2+2+1+1)=12. In another embodiment, the overall message score for the message may be the product of the weighted parameter scores. In another embodiment, the overall message score for the message may be the average of the of the weighted parameter scores. The overall message score may be calculated in other ways that reflect the parameters and/or weighted scores.

Once the overall message score 504 for the social media message is calculated, the priority level 505 of the message may be determined. For example, assignment of a priority level 505 that is assigned to the message (e.g., low, medium, high) for display in a message queue may be based on thresholds values for the overall, message score 504 that are configured by the user.

For example, FIG. 6 illustrates an example of a user interface 600, according to an embodiment, that is displayed by the queue prioritization system 2811. The user interface 600 may include a threshold slider tool that allows the user (e.g., customer service agent) to specify that, if the relevant overall message score 504 is between threshold score A and threshold score B, this corresponds to a score for a medium priority, everything below threshold score A corresponds to a score for a low priority, and everything above threshold score B corresponds to a score for a high priority.

The user interfaces of FIGS. 5 and 6 are merely exemplary, and the user of the queue prioritization system 2811 (e.g., a customer service agent) may define the contribution of each of the parameter scores to the calculation of the overall message score. For example, according to another embodiment, the queue prioritization system 2811 may display a user interface that allows the user to define the contribution of the problem classification score as 10% towards the overall message score, the contribution of the message sentiment score as 15% towards the overall message score, and so on.

Moreover, according to another embodiment, the queue prioritization system 2811 may display a user interface that allows the user to define different contribution settings for different channels or social media platforms. For example, if the original social media message is posted on FACEBOOK®, the contribution the customer SLA score may be defined by the agent as 0% of the overall message score for the original social media message, whereas if the original social media message is posted on TWITTER®, the contribution of customer SLA score may be defined by the agent as 20% of the overall message score for the original social media message, and so on. Similarly, the user may define different weights for a given parameter value of a message (see FIG. 5), for different channels or social media systems (e.g., depending on whether the message is posted on FACEBOOK® or TWITTER®).

Assignment of the various parameter scores by the queue prioritization system 2811 may be further customized by the user. For example, the queue prioritization system 2811 may display a user interface enabling the user to define product classification scores for various products that may be described in the message, or problem classification scores for various problems that may be described in the message, or message source scores for various webpages where the message may be posted, or message sentiment scores for various message sentiments, or various customer level scores or customer service level agreement scores for particular internal customer level of platinum, gold, etc., and so forth. Further, the queue prioritization system 2811 may permit the user to set a threshold number of friends for a given customer influence score, or a threshold number of views for a given message following score, and so forth. Since it may be difficult for the customer service agents to set an upper threshold (e.g. difficult to contemplate the number of views of a post that corresponds to a “high” score or “normal” score), a user interface of the system may include a threshold slider tool that allows the customer agent to specify that, if the relevant value is between score A and score B, this corresponds to a score for a medium priority, everything below that corresponds to a score for a low priority, above that corresponds to a score for a high priority.

For example, FIG. 7 illustrates a user interface 700, according to an embodiment. The user interface 700 may include a threshold slider tool that allows the customer agent to specify that, if the relevant number of likes is between score A and score B, this corresponds to a message following score for a medium priority (such as a message following score of 1), everything below that corresponds to a message following score for a low priority (such as a message following score of 0), above that corresponds to a message following score for a high priority (such as a message following score of 2). The user interface 700 also permits the user to specific whether the thresholds apply to views, likes, shares, comments, etc., or some combination thereof. A similar slide rule may be utilized to set thresholds for other parameters scores, such as a slide rule for user configuration of thresholds for the customer influence score, and so on.

Thus, the queue prioritization system 2811 of this exemplary embodiment automatically combines and analyzes all the aforementioned parameter scores (e.g., see 501 in FIG. 5) in order to determine a single overall message score of the message (504) and, ultimately, the assigned priority level of the message (505). Thereafter, the queue prioritization system 2811 may insert the social media message into a prioritized message queue based on the determined prioritization level corresponding to the social media message, and display the prioritized message queue to the user via a user interface.

For example, FIG. 8 illustrates a user interface 800 of the queue prioritization system 2811 of this exemplary embodiment. The queue prioritization interface 800 may include two user interface areas 801 and 802. User interface area 801 depicts plural social media messages received by the system, as well as priority levels that have been assigned to each message. The priority levels illustrated in the example of FIG. 8 include “Low”, “Medium” and “High”, but such priority levels are merely exemplary, and other priority level naming schemes may be utilized. For example, the priority levels may be “Urgent”, “Normal” and “Not Urgent”, or instead may be alpha-numeric rankings, such as “A” through “Z”, or “1” through “10”, etc,

The user interface area 802 depicts a prioritized message queue of social media messages. That is, after all the messages have been assigned a priority level, as seen in user interface area 801, the messages are displayed based on their assigned priority level in the user interface area 802. For example, all the social media messages may be sorted such that the social media messages having the highest priority level (e.g. “High”) are displayed at the head or top of the queue as seen in FIG. 8, followed by the social media messages having the next highest priority (e.g. “Medium”), followed by the social media messages having the next highest priority (e.g. “Low”), and so forth.

As further seen to the right of FIG. 8, a user interface area 803 may indicate some of the factors used to determine the priority level of a currently selected message as “HIGH”. For example, the currently selected message, which may be the message at the top of the prioritized message queue in user interface area 802, may include a message sentiment score corresponding to a “Moderate Sentiment,” a customer influence score corresponding to a user having more than 500 friends, and a customer level score corresponding to the user having an internal importance of a “Gold Customer.” In this way, the customer service agents may be able to focus on the most Important messages that require the most immediate attention.

FIG. 9 is a flowchart illustrating an example method 900, according to various embodiments. The method 900 may be performed at least in part by, for example, the queue prioritization system 2811 illustrated in FIG. 3. In 901, the communication module 2819 may access a social media message posted by a user on a social media system. In 902, the queue prioritization system 2811 may determine a prioritization level based on the social media message, the prioritization level indicating a measurement of importance of the social media message. For example, see prioritization level 505 illustrated in FIG. 5. In 903, the queue prioritization system 2811 may insert the social media message into a prioritized message queue based on the determined prioritization level associated with the social media message. The determination in 902 of the prioritization level corresponding to a particular social media message is described in more detail with reference to FIG. 10.

FIG. 10 is a flowchart illustrating an example method 1000, according to various embodiments. The method 1000 may be performed at least in part by, for example, the queue prioritization system 2811 illustrated in FIG. 3.

In 1001, the queue prioritization system 2811 may determine a message source score based on a location of the posting of the social media message on the social media system 22. For example, the message source score may be determined based on whether the social media message is posted on a user profile page in the social media system 22 that is associated with the user, a main profile page in the social media system 22 that is associated with an entity, a product-specific page in the social media system 22 that is associated with the entity, or a service-specific page in the social media system 22 that is associated with the entity. In 1002, the queue prioritization system 2811 may determine a message sentiment score indicating a measurement of sentiment of the content of the social media message. In 1003, the queue prioritization system 2811 may determine a message following score indicating a quantity of views, feedback indicators, reposts or follow-up messages posted by other users in response to the social media message. In 1004, the queue prioritization system 2811 may determines problem classification score indicating a particular problem and/or issue described in the content of the social media message. In 1005, the queue prioritization system 2811 may determine a product classification score indicating a particular product described in the content of the social media message. In 1006, the queue prioritization system 2811 may determine a customer level score indicating a measurement of an importance of the user. For example, the customer level score is determined based on at least one of an internal customer record of the user managed by an entity and one or more publically-accessible webpages describing the user. In 1007, the queue prioritization system 2811 may determine a customer influence score indicating a measurement of an influence of the user in the social networking platform. For example, the customer influence score may be determined based on a number of user connections, friends, or followers of the user on the social networking platform. In 1008, the queue prioritization system 2811 may determine a customer service level agreement, associated with the user and an entity. In 1009, the queue prioritization system 2811 may determine a social amplification score indicating a number of similar social media messages posted by other users on the social networking system. The similar social media messages may describe a product or problem also described in the social media message.

Finally, in 1010, the queue prioritization system 2811 may determine an overall message score corresponding to the social media message based on at least one of the aforementioned parameter scores generated in 1001-1009, and utilizes the overall message score to determine or assign a priority level to the social media message. Thus, the priority level of the social media message may be determined based on at least, one of the message source score, message sentiment score, message following score, product classification score, problem classification score, customer level score, customer influence score, customer service level agreement score, and social amplification score. The ordering of 1001-1009 in FIG. 10 may be modified.

While the previous embodiments have described various parameters that may be used to generate the overall message score and, thus, the priority level of the message, it should be understood that the aforementioned parameters are merely exemplary. For example, the manner in which the various parameters are factored to generate the overall message score may vary, and other parameters and parameters scores may be factored into the calculation of the overall message score, and the factors used to generate each of the parameter scores may be modified, and the various factors may be combined in various ways to generate other parameters scores capturing other parameters, and so forth.

The above described aspects and/or functions of the queue prioritization system 2811, according to an embodiment, may be implemented and/or performed by the queue prioritization module 2811a (see FIG. 3), which may correspond to a hardware module or a software module executed by one or more processors.

2: Customer Identification

In current customer relationship management systems, the identification of customers and the recording customer information is an essential task for a customer service agent. Manually eliciting and entering this information into form fields of an application or database, which is the conventional practice of customer service agents, consumes a great deal of time. This becomes especially challenging in social media space, where users of a social media network that post messages may use different names, accounts, profiles and aliases, which can potentially create duplicate records and make it difficult to map a social media customer with an internal customer record.

According to an exemplary embodiment, the communication module 2819 accesses a social media message posted on a social media system 22 (e.g., social media platform), as described above with reference to the queue prioritization system 2811. Thereafter, the customer identification system 2812 illustrated in FIG. 3 may automatically identify the user that posted the message (e.g., the customer) by obtaining “social media identity information” of the user, which may be any information identifying the user that is obtained from the social media message and/or the social media system 22. For example, the customer identification system 2812 may obtain the social media identity information by requesting a text analysis system 2820 to perform a text analysis of the message to identify the social media identity information that is included in the message (e.g. name, social media handle, telephone contact number, facsimile number, gender, email address, location, network, employer, education, username, etc.).

As another example, the customer identification system 2812 may access the social media system 22 itself to obtain the social media identity information of the user from information available in the user's social profile (e.g. by identifying the username of the user that posted the message, and then accessing a link to the social profile page associated with the username to retrieve the social media identity information). Publically available social media identity information regarding the user may be obtained from other social media systems or online sources as well. Social media systems 22 may expose social media identity information with an application programming interface (API) that is accessible by the system. For example, in one embodiment the social media system 22 may access an application programming interface that is provided by the social networking platform to retrieve the social media identity information that includes the identity of the user as registered on the social network system 22 (e.g., social media platform) based on a message identifier or some other Identification information obtained from a text analysis of the message. After the social media identity information is obtained by the customer identification system 2812, the social media identity information may be stored as a record or in a database or similar data structure (e.g., database 30 illustrated in FIG. 4). For example, FIG. 11 illustrates social media identity information 1100 of a user John Smith that is stored as a record in a database.

Once the social media identity information of a user that posted a social media message is obtained by the customer identification system 2812, the corresponding social media identity information may be compared against a database of internal customer records (e.g., customer information 3001 included in database 30 illustrated in FIG. 4. For example, FIG. 11 illustrates an example of a single internal customer record 1150 for a customer John Smith. Such customer records may be obtained from a company directory, or the company's own internal database of known customers, or CRM records, and so on. The customer identification system 2812 may compare the social media identity information with the internal customer records to see if there is a match between the social media identity information and one (or more) of the internal customer records. For example, the customer identification system may determine that the social media identity information 1100 matches the customer record 1150, based on a similarity in name, email, location/address, etc. between the social media identity information 1100 and the customer record 1150.

If there's a match, the social media identity information from the social media space is attached to and populated in the appropriate internal customer record (if it is not already present) by the customer identification system 2812. For example, any information in the social media identity information 1100 that is not included in the customer record 1150 (e.g., social media handle, or a copy of the social media message itself) may be populated into the customer record 1150. If there is no match, the customer identification system 2812 may generate a new internal customer record that includes the obtained social media identity information.

In the process of matching the social media identity information of the social media customer with the internal customer records, if there are multiple internal customer records that match at least partially with social media identity information, then the customer identification system 2812 may generate and display a list of candidate customer records to a customer service agent, as described in more detail below in connection with FIG. 12. This system 2812 enables the agent to identify a candidate customer from the list of candidate customer records as the identity of the author of the original social media message. By default, the customer identification system 2812 may also select the closest matching customer record as the author of the original social media message. Implementation of the customer identification system of this disclosure results in minimum to no manual data entry needed for customer identification on the part of customer service agents.

FIG. 12 illustrates an exemplary user interface 1200 that is displayed by the customer identification system 2812 of this exemplary embodiment. The user interface 1200 includes a customer identification area 1202, “other candidates” identification area 1203, and product identification area 1204. The customer identification area 1202 identifies the customer or user that posted a social media message, and includes any component of the aforementioned social media identity information and/or internal customer record corresponding to the user. For example, customer identification area 1202 may include a name (e.g., “Nick Greyson”), social media name/handle (e.g., “nick-greyson”), email, location, address, gender, age, birthdate, contact telephone number, classification (e.g., customer level), employer, education, and so forth. Thus, the customer identification area 1202 may include any information from the company's internal customer records (e.g., customer levels such as “gold” or “silver,” message sentiment history indicated by the expression on the face icon, etc.), as well as the social media identity information from the social media message posted on the social media system 22 (e.g., social networking platform) or information from publically available social media profiles (e.g., a number of followers of the user, a number of comments to the social media message, etc.).

The “other candidates' identification area 1203 may include candidate profiles that approximately match (e.g., fuzzy match) the social media identity information of the user that posted the message, along with a match measurement indicator indicating the accuracy of the match (e.g., see match measurement bars in 1203). In one embodiment the candidate profiles may be ordered in a list in the other candidates identification area 1203 based on the match measurement indicator. The information in each of the candidate profiles, like the information in customer identification area 1202, may be obtained from the customer records, from publically available social media profiles, from publicly accessible webpages, etc., as described above. The candidate profiles may identify one or more characteristics that were utilized to identify the match, such as a name social media name/handle, email address, location, gender, contact telephone number, classification (e.g., customer level), and so forth. The customer identification system 2812 may automatically select the candidate profile with the closest match as the author of the message. For example, FIG. 12 illustrates that the customer identification system 2812 has selected the candidate profile for “Nick Greyson” as the closest match with the social media identity information obtained from the social media message (e.g., Facebook name “nick-greyson”), as indicated by a check that is located under the “select” column on the far right of the record, and the information from this candidate profile has been populated into the customer identification area 1202. The “ether candidates” area 1203 is further shown to include a channels selection box on the top left that may be used to filter the “other candidate” list by selecting one or more social media channels (e.g., All Channels, TWITTER®, FACEBOOK®, etc.), and an input search box on the top right that may be used to filter the “other candidates” presented based on user inputted search keywords.

The product identification area 1204 includes identification information of the product that may be referenced in the message. For example, the queue prioritizations system 2182 may utilize the text analysis system 2820 to perform a text analysis of the content (e.g. words) of the message, in order to identify keywords that signify a particular product that is referenced in the message. For example, the customer identification system 2812 may access a list that is stored in the database 30 of known products such as “TV”, “processor”, “camera 600D” and so forth (e.g., product information 3003 in database 30), that if detected in the message through text analysis, indicates a particular product that may be referenced in the message. The product identification area 1204 may then display the information corresponding to the product that is obtained from the internal database of products and/or external, publically available information of the product.

If the product identification area 1204 indicates that multiple products have been found in the social media message, then the user may select or click within the product identification area 1204 in FIG. 12, and then the other candidate's identification area 1203 may be replaced by an “other products” Identification area 1305, as illustrated in user interface 1300 of FIG. 13. The other product identification area 1305 lists products that seem to match the product keywords found in the message, when multiple products are identified. The information for the other products may be obtained from the company's internal database 30 of products and/or external, publically available information of the product, wherein the other products may be tagged with one or more keywords that match the product keywords detected in the message.

FIG. 14 is a flowchart illustrating an example method 1400, according to various embodiments. The method 1400 may be performed at least in part by, for example, the customer identification system 2812 illustrated in FIG. 3. In 1401, the communication module 2819 may access a social media message posted on a social media system 22 (e.g., social media platform). In 1402, the customer identification system 2812 may obtain social media identity information indicating an identity of a user that posted the social media message. For example, the social media identity information may include at least one of a user name, social media handle, telephone number, location, gender and email address, and may be included in the social media message. The social media identity information may be obtained by, for example, utilizing the text analysis system 2820 to perform a textual analysis of the social media message to detect the social media identity information in the social media message. Instead or in addition, the social media identity information may be obtained by accessing a user profile page on the social media system 22 that is linked to the social media message and utilizing the text analysis system 2820 to perform a textual analysis of the user profile page to detect the social media identity information in the user profile page. FIG. 11 illustrates an example of social media identity information 1100 of a user John Smith that is stored in a database.

In 1403, the customer identification system 2812 may determine that the social media identity information matches a particular internal customer record maintained by an entity. FIG. 11 illustrates an example of an internal customer record 1150 for a customer John Smith. According to various embodiments, the customer identification system 2812 may determine that the social media identity information at least partially matches a number of internal customer records maintained by an entity. The customer identification system 2812 may display, to a customer service agent, a list identifying a plurality of candidate internal customer records determined to at least partially match the social media identity information and a corresponding plurality of match measurement indicators (e.g., see other candidate identification area 1203 in FIG. 12). Each of the match measurement indicators may indicate a match accuracy between the corresponding internal customer record and the social media identity information. The customer identification system 2812 may automatically associate a specific candidate internal customer record with the social media message (i.e., determine that the user identified in the particular customer record corresponds to the author of the original social media message), based on the match measurement indicator corresponding to the specific candidate internal customer record. The customer identification system 2812 may receive a user selection (from the customer service agent) of one of the candidate internal customer records, and instead associate that selected record with the original social media message. In such case, the customer identification system 2812 may determine that the user identified in the selected customer record corresponds to the author of the original social media message.

In 1404, the customer identification system 2812 inserts the social media identity information into the particular internal customer record determined in 1403. The customer identification system 2812 many insert other information into the particular internal customer record, such as the actual contents of the social media message, any feedback, comments, responses, etc., to that message, a history of other social media messages posted by the user, and so forth. Note that if no matching or partially matching internal customer record is identified in 1403, the customer identification system 2812 may generate a new internal customer record in 1404, and populate the new record with the social media identity information obtained in 1402.

The above described aspects and/or functions of the customer identification system 2812, according to an embodiment, may be implemented and/or performed by the customer identification module 2812a (see FIG. 3), which may correspond to a hardware module or a software module executed by one or more processors.

Modules, Components and Logic

Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied (1) on a non-transitory machine-readable medium or (2) in a transmission signal) or hardware-implemented modules. A hardware-implemented module is tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more processors may be configured by software (e.g., an application or application portion) as a hardware-implemented module that operates to perform certain operations as described herein.

In various embodiments, a hardware-implemented module may be implemented mechanically or electronically. For example, a hardware-implemented module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC))to perform certain operations. A hardware-implemented module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware-implemented module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.

Accordingly, the term “hardware-implemented module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily or transitorily configured (e.g., programmed) to operate in a certain manner and/or to perform certain operations described herein. Considering embodiments in which hardware-implemented modules are temporarily configured (e.g., programmed), each of the hardware-implemented modules need not be configured or instantiated at any one instance in time. For example, where the hardware-implemented modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware-implemented modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware-implemented module at one instance of time and to constitute a different hardware-implemented module at a different instance of time.

Hardware-implemented modules can provide information to, and receive information from, other hardware-implemented modules. Accordingly, the described hardware-implemented modules may be regarded as being communicatively coupled. Where multiple of such hardware-implemented modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the hardware-implemented modules. In embodiments in which multiple hardware-implemented modules are configured or instantiated at different times, communications between such hardware-implemented modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware-implemented modules have access. For example, one hardware-implemented module may perform an operation, and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware-implemented module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware-implemented modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).

The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules.

Similarly, the methods described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or processors or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.

The one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., Application Program Interfaces (APIs))

Electronic Apparatus and System

Example embodiments may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. Example embodiments may be implemented using a computer program product, e.g., a computer program tangibly embodied in an information carrier, e.g., in a machine-readable medium for execution by, or to control the operation of, data processing apparatus, e.g., a programmable processor, a computer, or multiple computers.

A computer program can be written in any form of programming language, including compiled or interpreted languages, and if can be deployed in any form, including as a stand-alone program or as a module, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network.

In example embodiments, operations may be performed by one or more programmable processors executing a computer program to perform functions by operating on input data and generating output. Method operations can also be performed by, and apparatus of example embodiments may be implemented as, special purpose logic circuitry, e.g., a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC).

The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In embodiments deploying a programmable computing system, it will be appreciated that that both hardware and software architectures require consideration. Specifically, it will be appreciated that the choice of whether to implement certain functionality in permanently configured hardware (e.g., an ASIC), in temporarily configured hardware (e.g., a combination of software and a programmable processor), or a combination of permanently and temporarily configured hardware may be a design choice. Below are set out hardware (e.g., machine) and software architectures that may be deployed, in various example embodiments.

Example Machine Architecture and Machine-Readable Medium

FIG. 15 is a block diagram of machine in the example form of a computer system 1500 within which instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

The example computer system 1500 includes a processor 1502 (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory 1504 and a static memory 1506, which communicate with each other via a bus 1508. The computer system 1500 may further include a video display unit 1510 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 1500 also includes an alphanumeric input device 1512 (e.g., a keyboard or a touch-sensitive display screen), a user interface (UI) navigation device 1514 (e.g., a mouse), a disk, drive unit 1516, a signal generation device 1518 (e.g., a speaker) and a network interface device 1520.

Machine-Readable Medium

The disk drive unit 1516 includes a machine-readable medium 1522 on which is stored one or more sets of instructions and data structures (e.g., software) 1524 embodying or utilized by any one or more of the methodologies or functions described herein. The instructions 1524 may also reside, completely or at least partially, within the main memory 1504 and/or within the processor 1502 during execution thereof by the computer system 1500, the main memory 1504 and the processor 1502 also constituting machine-readable media.

While the machine-readable medium 1522 is shown in an example embodiment to be a single medium, the term “machine-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more instructions or data structures. The term “machine-readable medium” shall also be taken to include any tangible medium that is capable of storing, encoding or carrying instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present invention, or that is capable of storing, encoding or carrying data structures utilized by or associated with such instructions. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media. Specific examples of machine-readable media include non-volatile memory, including by way of example semiconductor memory devices, e.g., Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

Transmission Medium

The instructions 1524 may further be transmitted or received over a communications network 1526 using a transmission medium. The instructions 1524 may be transmitted using the network interface device 1520 and any one of a number of well-known transfer protocols (e.g., HTTP). Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), the Internet, mobile telephone networks, Plain Old Telephone (POTS) networks, and wireless data net-works (e.g., WiFi and WiMax networks). The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.

Although an embodiment has been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. The accompanying drawings that form a part hereof, show by way of illustration, and not of limitation, specific embodiments in which the subject matter may be practiced. The embodiments illustrated are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed herein. Other embodiments may be utilized and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.

Such embodiments of the inventive subject matter may be referred to herein, individually and/or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Thus, although specific embodiments have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description.

Claims

1. A method comprising:

accessing a social media message posted by a user on a social media system;

determining, a prioritization level based on the social media message, the prioritization level indicating a measurement of importance of the social media message; and

inserting the social media message into a prioritized message queue based on the determined prioritization level associated with the social media message.

2. The method of claim 1, wherein the prioritization level is determined based at least in part on a message source score indicating a particular location of the posting of the social media message on the social media system.

3. The method of claim 2, wherein the particular location is selected from a group of locations consisting of a user profile page associated with the user, a main profile page associated with an entity, a product-specific page associated with the entity, and a service-specific page associated with the entity.

4. The method of claim 1, wherein the prioritization level is determined based at least in part on a message sentiment score indicating a measurement of sentiment of the content of the social media message.

5. The method of claim 1, wherein the prioritization level is determined based at least in part on a message following score indicating at least one of a quantity of views, feedback indicators, reposts and follow-up messages posted by other users in response to the social media message.

6. The method of claim 1, wherein the prioritization level is determined based at least in part on a problem classification score indicating at least one of a particular problem described in the content of the social media message and issue described in the content of the social media message.

7. The method of claim 1, wherein the prioritization level is determined based at least in part on a product classification score indicating a measurement of a particular product described in the content of the social media message.

8. The method of claim 1, wherein the prioritization level is determined based at least in part on a customer level score indicating a measurement of an importance of the user.

9. The method of claim 8, wherein the customer level score is determined based on at least one of an internal customer record of the user managed by an entity and one or more publically-accessible webpages describing the user.

10. The method of claim 1, wherein the prioritization level is determined based at least in part on a customer influence score indicating a measurement of an influence of the user on the social networking system.

11. The method of claim 10, wherein the customer influence score is determined based on at least one of a number of user connections, a number of friends, and a number of followers of the user on the social networking system.

12. The method of claim 1, wherein the prioritization level is determined based at least in part on a customer service level agreement associated with the user and an entity.

13. The method of claim 1, wherein the prioritization level is determined based at least in part on at least one of a social amplification score indicating a number of similar social media messages posted by other users on the social networking system and the similar social media messages describing a product or problem corresponding to a product or problem described in the social media message.

14. A system comprising:

a communication module configured to access a social media message posted by a user on a social media system; and

a queue prioritization module configured to: determine a prioritization level based on the social media message, the prioritization level indicating a measurement of importance of the social media message; and insert the social media message into a prioritized message queue based on the determined prioritization level associated with the social media message.

15. A non-transitory machine-readable storage medium having embodied thereon instructions executable by one or more machines to perform operations comprising:

accessing a social media message posted by a user on a social media system;

determining a prioritization level based on the social media message, the prioritization level indicating a measurement of importance of the social media message; and

inserting the social media message into a prioritized message queue based on the determined prioritization level associated with the social media message.

16. A method comprising;

accessing a social media message posted on a social media system;

obtaining social media identity information based on information included in the social media message, the social media identity information indicating an identity of a user that posted the social media message;

determining that the social media identity information matches a particular infernal customer record maintained by an entity; and inserting the social media identity information into the particular internal customer record maintained by the entity.

17. The method of claim 16, further comprising;

displaying a list identifying a plurality of candidate internal customer records determined to match the social media identity information and a corresponding plurality of match measurement indicators, each of the match measurement indicators indicating a match accuracy between the corresponding internal customer record and the social media identity information.

18. The method of claim 16, further comprising:

automatically associating a specific candidate internal customer record with the social media message, based on the match measurement indicator corresponding to the specific candidate internal customer record.

19. A system comprising:

a communication module configured to access a social media message posted by a user on a social media system; and

a customer identification module configured to; obtain social media identity information based on information included in the social media message, the social media identity information indicating an identity of a user that posted the social media message;

determine that the social media identity information matches a particular internal customer record maintained by an entity; and

insert the social media identity information into the particular internal customer record maintained by the entity.

20. A non-transitory machine-readable storage medium having embodied thereon instructions executable by one or more machines to perform operations comprising:

accessing a social media message posted on a social media system;

obtaining social media identity information based on information included in the social media message, the social media identity information indicating an identity of a user that posted the social media message;

determining that the social media identity information matches a particular internal customer record maintained by an entity; and

inserting the social media identity information into the particular internal customer record maintained by the entity.