NLP in Social Monitoring, Analysis, and Interaction

Natural Language Processing (NLP) technology, frequently called text analytics technology, is key to analyzing what customers are saying about your company. So leveraging NLP in a big part of the best social-service products. NLP input is the content of customers’ posts, messages, and feedback, while NLP output is a tree structure that represents and contains their syntax, semantics, context, and intent. NLP processing performs tasks such as:

  • Corrects spelling
  • Parses content to determine parts of speech and their relationships
  • Extracts entities and facts
  • Resolves vague pronoun antecedents (anaphora)
  • Determines the meaning of unknown words using their morphological attributes
  • Identifies phrases
  • Identifies relationships between words and phrases

This week’s report is about Clarabridge Analyze, Clarabridge Collaborate, and Clarabridge Engage—the Voice of the Customer/ social-service offering from Clarabridge, Inc., a privately-held software supplier based in Reston, VA. Clarabridge Analyze listens, analyzes, reports, and alerts on customer conversations on social and on internal channels. Analyze’s alerts are sent to Collaborate for their assignment and management. From within Collaborate, facilities of Engage let agents respond to and interact with customers.

NLP is a core analysis component of Clarabridge Analyze and the key IP of Clarabridge, Inc. Clarabridge did not supply the details of the functionality of its NLP, certainly not its internals and not very much about its externals.

Clarabridge characterizes its NLP as “proprietary.” While the company owns a few patents, none of them is for its NLP. It protects this IP through minimal disclosure. Other VoC and social monitoring, analysis, and interaction products that we’ve evaluated have taken the steps to patent their NLP technology or have been willing to discuss the details of the technologies that they’ve used to analyze customer conversations. Patents protect the technology from competitors who might copy it but, at the same time, patents reveal the technology to those, like us, who evaluate the products that contain it and those who purchase and use the products. This revealing enables product comparisons and helps ensure that selection decisions address requirements.  (For evaluations of other text analytics-based social monitoring, analysis, and interaction products, we really have read the patents and the patent applications.)

On one hand, understanding what a product does and how it does it are critical to actionable evaluations. For VoC and social monitoring, analysis, and interaction products these are important factors for a product’s performance, throughput and scalability, accuracy, and consistency. Without detailed information on NLP, you’ll be buying a black box. That can be risky. Selection will rely on demonstrations, limited trials, and references.

On the other hand, we’re not language scientists. Our evaluations do not consider the internals of the algorithms that an NLP implementation uses for parsing customer verbatims or for extracting entities, facts, and relationships from them. But, we sure want to know that these products have facilities for automating the analysis of the huge and ever increasing volumes of customer conversations, for performing these analyses quickly and consistently, and for identifying which verbatims need follow-up actions. Clarabridge Analyze does have these facilities. Along with Clarabridge Engage, Clarabridge Analyze can help businesses deliver effective social-service.

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