Dan Somers of Warwick Analytics explains how machine learning is improving the lack of accuracy and relevance associated with sentiment analysis.
Sentiment Analysis is widely used to supplement the analysis of text data in surveys, complaints, reviews and other contact centre data. In theory, Sentiment Analysis categorises opinions expressed in a piece of text just as a human might.
However, as the volume and complexity of customer data grows, growing issues with Sentiment Analysis are providing flawed information and preventing companies from getting the full picture from their data. Key customer feedback that could drive positive business change is being missed.