Method and apparatus to calculate real-time customer satisfaction and loyalty metric using social media analytics

• US 9,542,712 B2
• Filed: 03/21/2014
• Issued: 01/10/2017
• Est. Priority Date: 02/15/2011
• Status: Active Grant

• Current Assignee: Dell Products LP (Dell Technologies Inc.)
• Original Assignee: Dell Products LP (Dell Technologies Inc.)
• Inventors: Gupta, Munish, Dandekar, Shree A., Chen, Dongxia, Daruvalla, Keisha, Melinat, Brian, Palaniandavan, Guhan
• Primary Examiner(s): Lai, Michael C
• Application Number:
  US14/221,377
• Publication Number:
  US 20140207562A1
• Time in Patent Office: 1,026 Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A method and system are disclosed for providing a near-real-time measurement of sentiment and advocacy associated with user interactions within a social media environment. A first and second set of social media data, respectively associated with a first and second set of social media interactions, are processed to generate a first and second set of social network advocacy (SNA) data in near-real-time. The resulting first and second sets of SNA data are then processed to generate a first and second set of SNA Pulse (SNAP) metric data, which respectively indicate a near-real-time measurement of sentiment and advocacy for a given aspect of an organization. The first and second sets of SNAP metric data are then processed to generate a set of SNAP metrics differential data, which indicates a corresponding improvement or decline in sentiment or advocacy.

Claims

1. A computer-implementable method for providing a near-real-time measurement of sentiment within a social media environment, comprising:

processing a first set of social media data to generate a first set of social network advocacy (SNA) data in near-real-time, the first set of social media data associated with a first set of user interactions within a social media environment, the processing the first set of social media data comprising associating sentiment values for the first set of user interactions;

processing the first set of SNA data to generate a first set of SNA Pulse (SNAP) metric data, the processing the first set of SNA data comprises generating the first set of SNAP metric data using the sentiment values;

processing a second set of social media data to generate a second set of SNA data in near-real-time, the second set of social media data associated with a second set of user interactions within the social media environment, the processing the second set of social media data comprising associating sentiment values for the second set of user interactions;

processing the second set of SNA data to generate a second set of SNAP metric data, the processing the second set of SNA data comprises generating the second set of SNAP metric data using the sentiment values for the second set of user interactions; and

processing the first and second sets of SNAP metric data to generate a set of SNAP metrics differential data; and

wherein

the first and second sets of SNA data respectively comprise a numeric value corresponding to sentiment, a numeric value corresponding to gravity, a numeric value corresponding to domain influence, a numeric value corresponding to reach and a numeric value corresponding to relevance; and

,

the first and second SNAP metrics are respectively generated by processing at least two of the numeric value corresponding to sentiment, the numeric value corresponding to gravity, the numeric value corresponding to domain influence, the numeric value corresponding to reach and the numeric value corresponding to relevance.