Generating and Displaying Customer Commitment Framework Data

Abstract

Systems and methods for generating and displaying customer commitment framework data are provided. Exemplary methods for determining the shareability of online content may include obtaining, via a digital intelligence system, customer experience data regarding any of a product, a brand, and customer responses for a first entity, as well as periodically calculating, via the digital intelligence system, customer commitment framework data from the customer experience data, and generating a customer commitment dashboard that comprises a graphical representation of the customer commitment framework data.

What is claimed is: 
     
         1 . A social intelligence system, comprising:
 means for determining social media participants in at least one phase of a product cycle for a product;   means for obtaining social media data from one or more social media platforms for the social media participants relative to the product;   means for calculating a product commitment score that represents a commitment level of the social media participants to the product; and   means for providing the product commitment score to an end user client device by the social media intelligence system.   
     
     
         2 . The system according to  claim 1 , wherein the means for calculating the product commitment score comprises a product commitment score module implemented on a computing system and configured for evaluating the social media data by determining keywords included in the social media data that reflect product commitment, the social media data being determined from social media conversations of an author. 
     
     
         3 . The system according to  claim 2 , wherein determining keywords comprises comparing keywords in the social media data to a matrix of words that reflect any of assess, prefer, and buy behaviors of the author. 
     
     
         4 . The system according to  claim 2 , wherein the product commitment score module is further configured for computing an author rank for the author, the author rank comprising an analysis of any of social media connections, social status, and combinations thereof, wherein the author rank is associated with an influence for the author. 
     
     
         5 . The system according to  claim 4 , further comprising computing an adjusted author rank score by dividing the author rank by a sum of author ranks for a plurality of authors, the author rank being one of the plurality of author ranks. 
     
     
         6 . The system according to  claim 5 , further comprising calculating a component weight for a conversation of the author. 
     
     
         7 . The system according to  claim 6 , further comprising:
 determining a product commitment score scaling factor, based upon an analysis of keywords included in the social media conversations;   adjusting the scaling factor, such that:   the scaling factor for keywords associated with buy behaviors is highest;   the scaling factor for keywords associated with prefer behaviors is lower than the scaling factor for keywords associated with buy behaviors; and   the scaling factor for keywords associated with assess behaviors is lower than the scaling factor for keywords associated with prefer behaviors.   
     
     
         8 . The system according to  claim 7 , further comprising multiplying the adjusted author rank with the component weight and the scaling factor to generate the product commitment score. 
     
     
         9 . The system according to  claim 2 , wherein the author includes a trusted author and evaluating the social media data further includes semiotic analysis of the social media conversations of the author to categorize the social media conversations as being within a product commitment score domain. 
     
     
         10 . A system, comprising:
 one or more processors; and   logic encoded in one or more tangible media for execution by the one or more processors and when executed operable to perform operations comprising:   means for determining, via a data gathering module, social media participants in at least one phase of a product cycle for a product;   means for obtaining social media data from one or more social media platforms for the social media participants relative to the product;   means for evaluating the social media data to categorize social media conversations of the social media data as being within a product commitment score domain;   means for calculating a product commitment score that represents a commitment level of the social media participants to the product; and   means for providing the product commitment score to an end user client device by the social media intelligence system.   
     
     
         11 . The system according to  claim 10 , wherein the means for calculating the product commitment score comprises a product commitment score module configured to evaluate the social media data by determining keywords included in the social media data that reflect product commitment, the social media data being determined from social media conversations of an author. 
     
     
         12 . The system according to  claim 11 , wherein the product commitment score module is further configured to determine keywords by comparing keywords in the social media data to a matrix of words that reflect any of assess, prefer, and buy behaviors of the author. 
     
     
         13 . The system according to  claim 12 , wherein the product commitment score module is further configured to calculate an author rank for the author, the author rank comprising an analysis of any of social media connections, social status, and combinations thereof, wherein the author rank is associated with an influence for the author. 
     
     
         14 . The system according to  claim 13 , wherein the product commitment score module is further configured to compute an adjusted author rank score by dividing the author rank by a sum of author ranks for a plurality of authors, the author rank being one of the plurality of author ranks. 
     
     
         15 . The system according to  claim 14 , wherein the product commitment score module is further configured to a component weight for a conversation of the author. 
     
     
         16 . The system according to  claim 15 , wherein the product commitment score module is further configured to:
 determine a product commitment score scaling factor, based upon an analysis of keywords included in the social media conversations;   adjust the scaling factor, such that:   the scaling factor for keywords associated with buy behaviors is highest;   the scaling factor for keywords associated with prefer behaviors is lower than the scaling factor for keywords associated with buy behaviors; and   the scaling factor for keywords associated with assess behaviors is lower than the scaling factor for keywords associated with prefer behaviors.   
     
     
         17 . The system according to  claim 16 , wherein the product commitment score module is further configured to multiply the adjusted author rank with the component weight and the scaling factor to generate the product commitment score. 
     
     
         18 . The system according to  claim 11 , wherein the author includes a trusted author, and wherein categorizing the social media conversations of the author as being within the product commitment score domain includes semiotic analysis of the social media conversations of the author. 
     
     
         19 . The system according to  claim 1 , further comprising:
 means for segmenting social media data into groups of social media conversations based on content of the social media conversations;   means for generating a model to predict, for tracking, a group of the segmented social media conversations that will provide accurate and relevant information about a consumer;   means for tracking the predicted group of social media conversations based on the generated model; and   means for directing merchant resources based on the tracked conversations.   
     
     
         20 . The system according to  claim 10 , further comprising:
 means for segmenting social media data into groups of social media conversations based on content of the social media conversations;   means for generating a model to predict a group of social media conversations to track to glean the accurate and relevant information about a consumer;   means for directing merchant resources based on the generated model.