Industry Specific Brand Benchmarking System Based On Social Media Strength Of A Brand

Abstract

A brand monitoring platform (BMP) for brand benchmarking based on a brand's social media strength is provided. The BMP acquires input information on the brand and identifies industries related to the brand and competing brands. The BMP acquires social media information related to the brand and the competing brands from multiple social media sources via a network, dynamically generates categories in one or more hierarchical levels in each of the industries based on an independent analysis of the social media information, and sorts the social media information into the categories using a sorting interface. The BMP generates an aggregate score using an audience score determined by measuring an aggregate reach of the brand and the competing brands based on weighted audience score metric parameters, and an engagement score determined by measuring interaction between the brand and the competing brands and their followers based on weighted engagement score metric parameters.

We claim: 
     
         1 . A computer implemented method for benchmarking a brand based on social media strength of said brand, comprising:
 providing a brand monitoring platform comprising at least one processor configured to monitor said brand in a virtual social media environment;   acquiring input information on said brand by said brand monitoring platform;   identifying industries related to said brand and competing brands in said identified industries using said acquired input information on said brand by said brand monitoring platform;   acquiring social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment by said brand monitoring platform via a network;   dynamically generating categories in one or more hierarchical levels in each of said identified industries by said brand monitoring platform;   sorting said acquired social media information by said brand monitoring platform using a sorting interface provided by said brand monitoring platform; and   determining an audience score, determining an engagement score, generating an aggregate score, and determining said social media strength of said brand and each of said competing brands in said virtual social media environment by said brand monitoring platform;   whereby said brand is benchmarked in comparison with said competing brands based on said social media strength of said brand.   
     
     
         2 . The computer implemented method of  claim 1 , wherein said dynamic generation of categories is based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources, and comprises:
 location of each of said identified industries related to said brand and said each of said competing brands;   location of each of a plurality of authors of said social media information;   types of said social media sources utilized by said brand and said each of said competing brands; and   marketing elements.   
     
     
         3 . The computer implemented method of  claim 2 , wherein said independent analysis further comprises the step of:
 determining clusters of similar content portions from said acquired social media information and identifying one or more common categories applicable to said brand and said each of said competing brands in said each of said identified industries from said determined clusters of said similar content portions.   
     
     
         4 . The computer implemented method of  claim 1 , wherein said sorting said acquired social media information by said brand monitoring platform further comprises:
 acquiring inputs related to said brand and said competing brands in said each of said identified industries; and   sorting said acquired inputs into one or more of said dynamically generated categories in said one or more hierarchical levels using said sorting interface.   
     
     
         5 . The computer implemented method of  claim 1 , wherein said determination of said audience score for said brand and said each of said competing brands by said brand monitoring platform comprises:
 normalizing measures corresponding to each audience score metric parameter;   assigning individual weights to said audience score metric parameters;   determining a weighted average of said normalized measures corresponding to said each of said audience score metric parameters using said assigned individual weights; and   measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment based on one or more of a plurality of said weighted audience score metric parameters using said sorted social media information.   
     
     
         6 . The computer implemented method of  claim 5 , further comprising:
 normalizing measures corresponding to each of said weighted audience score metric parameters by said brand monitoring platform for reducing statistical differences between extreme said measures corresponding to said each of said weighted audience score parameters.   
     
     
         7 . The computer implemented method of  claim 5 , wherein said weighted audience score metric parameters comprise:
 number of followers of said brand and said each of said competing brands at said each of said social media sources;   rate of growth of said number of followers of said brand and said each of said competing brands;   number of recommendations for said brand and said each of said competing brands at said each of said social media sources from each of said followers;   number of references made to said brand and said each of said competing brands at said each of said social media sources by said followers; and   aggregate responses to one or more of products, services, and events associated with said brand and said each of said competing brands.   
     
     
         8 . The computer implemented method of  claim 1 , wherein said determination of said engagement score for said brand and said each of said competing brands by said brand monitoring platform comprises:
 normalizing measures corresponding to each engagement score metric parameter;   assigning individual weights to said engagement score metric parameters;   determining a weighted average of said normalized measures corresponding to said each of said engagement score metric parameters using said assigned individual weights; and   measuring interaction between said brand and said each of said competing brands and said followers of said brand and said each of said competing brands by said brand monitoring platform based on one or more of a plurality of said weighted engagement score metric parameters using said sorted social media information.   
     
     
         9 . The computer implemented method of  claim 8 , further comprising:
 normalizing measures corresponding to each of said weighted engagement score metric parameters by said brand monitoring platform for reducing statistical differences between extreme said measures corresponding to said each of said weighted engagement score parameters.   
     
     
         10 . The computer implemented method of  claim 8 , wherein said weighted engagement score metric parameters comprise:
 nature of responses to one or more brand actions of said brand and said each of said competing brands from each of said followers of said brand and said each of said competing brands;   number of brand notification messages, sentiments of said followers towards said brand and said each of said competing brands;   number of fan posts extracted from said acquired social media information; and   relevance of said fan posts to said brand and said each of said competing brands.   
     
     
         11 . The computer implemented method of  claim 1 , wherein said determination of said audience score and said engagement score for said brand and said each of said competing brands by said brand monitoring platform further comprises:
 normalizing measures corresponding to one or more of said audience score metric parameters and one or more of said engagement score metric parameters, based on said location of each of said identified industries related to said brand and said each of said competing brands, for reducing statistical differences in said measures triggered by a difference of said location of said each of said identified industries related to said brand and said each of said competing brands.   
     
     
         12 . The computer implemented method of  claim 1 , further comprising:
 configuring one or more of said weighted audience score metric parameters and one or more of said weighted engagement score metric parameters for said determination of said audience score and said engagement score respectively, by said brand monitoring platform based on a predetermined criteria.   
     
     
         13 . The computer implemented method of  claim 1 , wherein said brand monitoring platform generates said aggregate score for said brand and said each of said competing brands by determining a weighted average of said determined audience score and said determined engagement score. 
     
     
         14 . The computer implemented method of  claim 1 , wherein determining said social media strength of said brand in comparison with said competing brands by said brand monitoring platform comprises:
 assigning a rank to said brand and said each of said competing brands based on said generated aggregate score; and   determining said social media strength of said brand in comparison with said competing brands by comparing said assigned ranks of said brand and said each of said competing brands.   
     
     
         15 . A computer implemented system for benchmarking a brand based on social media strength of said brand, comprising:
 a brand monitoring platform comprising at least one processor configured to execute modules of said brand monitoring platform for monitoring said brand in a virtual social media environment, said modules of said brand monitoring platform comprising:
 an information acquisition module that acquires input information on said brand; 
 an industry identification module that identifies industries related to said brand and competing brands in said identified industries using said acquired input information on said brand; 
 said information acquisition module that acquires social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment via a network; 
 a category generation module that dynamically generates categories in one or more hierarchical levels in each of said identified industries; 
 a sorting module that sorts said acquired social media information using a sorting interface; and 
 a scoring module that determines an audience score, determines an engagement score, generates an aggregate score, and determines said social media strength of said brand and each of said competing brands; 
 whereby said brand is benchmarked in comparison with said competing brands based on said social media strength of said brand. 
   
     
     
         16 . The computer implemented system of  claim 15 , wherein said dynamic generation of categories by said category generation module is based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources, and comprises:
 location of each of said identified industries related to said brand and said each of said competing brands;   location of each of a plurality of authors of said social media information;   types of said social media sources utilized by said brand and said each of said competing brands; and   marketing elements.   
     
     
         17 . The computer implemented system of  claim 16 , wherein said independent analysis by said category generation module further comprises the step of:
 determining clusters of similar content portions from said acquired social media information and identifying one or more common categories applicable to said brand and said each of said competing brands in said each of said identified industries from said determined clusters of said similar content portions.   
     
     
         18 . The computer implemented system of  claim 15 , wherein said sorting module further performs the steps of:
 acquiring inputs related to said brand and said competing brands in each of said identified industries; and   sorting said acquired inputs into one or more of said dynamically generated categories in said one or more hierarchical levels using said sorting interface.   
     
     
         19 . The computer implemented system of  claim 15 , wherein determination of said audience score for said brand and said each of said competing brands by said scoring module comprises:
 normalizing measures corresponding to each audience score metric parameter;   assigning individual weights to said audience score metric parameters;   determining a weighted average of said normalized measures corresponding to said each of said audience score metric parameters using said assigned individual weights for said determination of said audience score for said brand and said each of said competing brands; and   measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment based on one or more of a plurality of said weighted audience score metric parameters using said sorted social media information.   
     
     
         20 . The computer implemented system of  claim 19 , wherein said scoring module further performs the step of:
 normalizing measures corresponding to each of said weighted audience score metric parameters for reducing statistical differences between extreme said measures corresponding to said each of said weighted audience score metric parameters.   
     
     
         21 . The computer implemented system of  claim 19 , wherein said weighted audience score metric parameters comprise:
 number of followers of said brand and said each of said competing brands at said each of said social media sources;   rate of growth of said number of followers of said brand and said each of said competing brands;   number of recommendations for said brand and said each of said competing brands at said each of said social media sources from each of said followers;   number of references made to said brand and said each of said competing brands at said each of said social media sources by said followers; and   aggregate responses to one or more of products, services, and events associated with said brand and said each of said competing brands.   
     
     
         22 . The computer implemented system of  claim 15 , wherein said determination of said engagement score for said brand and said each of said competing brands by said scoring module comprises:
 normalizing measures corresponding to each engagement score metric parameter;   assigning individual weights to said engagement score metric parameters;   determining a weighted average of said normalized measures corresponding to said each of said engagement score metric parameters using said assigned individual weights for said determination of said engagement score for said brand and said each of said competing brands; and   measuring interaction between said brand and said each of said competing brands and said followers of said brand and said each of said competing brands by said brand monitoring platform based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information.   
     
     
         23 . The computer implemented system of  claim 22 , wherein said scoring module further performs the step of:
 normalizing measures corresponding to each of said weighted engagement score metric parameters for reducing statistical differences between extreme said measures corresponding to said each of said weighted engagement score metric parameters.   
     
     
         24 . The computer implemented system of  claim 22 , wherein said weighted engagement score metric parameters comprise:
 nature of responses to one or more brand actions of said brand and said each of said competing brands from each of said followers of said brand and said each of said competing brands;   number of brand notification messages, sentiments of said followers towards said brand and said each of said competing brands;   number of fan posts extracted from said acquired social media information; and   relevance of said fan posts to said brand and said each of said competing brands.   
     
     
         25 . The computer implemented system of  claim 15 , wherein said scoring module further performs the step of:
 normalizing measures corresponding to one or more of said audience score metric parameters and one or more of said engagement score metric parameters respectively, based on said location of each of said identified industries related to said brand and said each of said competing brands, for reducing statistical differences in said measures triggered by a difference of said location of said each of said identified industries related to said brand and said each of said competing brands.   
     
     
         26 . The computer implemented system of  claim 15 , wherein said modules of said brand monitoring platform further comprises:
 a configuration module that configures one or more of said weighted audience score metric parameters and one or more of said weighted engagement score metric parameters for said determination of said audience score and said engagement score respectively, based on a predetermined criteria.   
     
     
         27 . The computer implemented system of  claim 15 , wherein said scoring module generates said aggregate score for said brand and said each of said competing brands by determining a weighted average of said determined audience score and said determined engagement score. 
     
     
         28 . The computer implemented system of  claim 15 , wherein said scoring module further performs the steps of:
 assigning a rank to said brand and said each of said competing brands based on said generated aggregate score; and   determining said social media strength of said brand in comparison with said competing brands by comparing said assigned ranks of said brand and said each of said competing brands.   
     
     
         29 . A computer program product comprising a non-transitory computer readable storage medium, said non-transitory computer readable storage medium storing computer program codes comprising instructions executable by at least one processor, said computer program codes comprising:
 a first computer program code for acquiring input information on a brand;   a second computer program code for identifying industries related to said brand and competing brands in said identified industries using said acquired input information on said brand;   a third computer program code for acquiring social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in a virtual social media environment via a network;   a fourth computer program code for dynamically generating categories in one or more hierarchical levels in each of said identified industries based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources;   a fifth computer program code for sorting said acquired social media information related to said brand and said competing brands in said each of said identified industries into one or more of said dynamically generated categories in said one or more hierarchical levels using a sorting interface;   a sixth computer program code for determining an audience score for said brand and each of said competing brands by measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment based on one or more of a plurality of weighted audience score metric parameters using said sorted social media information;   a seventh computer program code for determining an engagement score for said brand and said each of said competing brands by measuring interaction between said brand and said each of said competing brands and their followers based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information;   an eighth computer program code for generating an aggregate score for said brand and said each of said competing brands using said determined audience score and said determined engagement score;   said eighth computer program code further assigning a rank to said brand and said each of said competing brands based on said generated aggregate score; and   said eighth computer program code further determining social media strength of said brand in comparison with said competing brands in said virtual social media environment by comparing said assigned ranks of said brand and said each of said competing brands.