Gartner Research

Sentiment Analysis Cracks the Code on Unstructured Voice of the Customer Analytics

Published: 30 April 2015

ID: G00273027

Analyst(s): Jamie Popkin


VoC analytics relies on four primary data sources for insight into customer wants, needs and behaviors. Unstructured content is the most challenging source to analyze. Sentiment analysis enables deep interpretation of customer content sources, adding value to predictive and prescriptive analytics.

Table Of Contents


  • Sentiment Analysis of Unstructured VoC Content Needs to Do More Than Mine for Emotional Polarity
  • How to Diagnose the Health of the Customer Relationship by Applying Sentiment Analysis to the VoC Unstructured Content Channel
    • Descriptive Analytics: What Are Customers Feeling?
    • Diagnostic Analytics: Why Are Customers Feeling the Way They Do?
    • Predictive Analytics: How Do Expressed Emotional Patterns Predict Loyalty Behavior?
    • Prescriptive Analytics: How Can Sentiment Analysis Be Used in a VoC Analytics Process to Boost Loyalty?
  • What Are the Technical Challenges of Using Sentiment Analysis for Voice of the Customer Analytics?
    • Selecting the Right Technical Approach for Generating Sentiment Input for a VoC Analytics System
    • Truly Objective, Labeled Data: The Holy Grail of VoC Analytics
  • Strengths
  • Weaknesses


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