Customer sentiment analysis is a method of processing information, generally in text format and often from social media sources, to determine customer opinions and responses. Analysis of the data allows organizations to assess whether customer reaction to a new product was positive or negative, or whether owners of a product are experiencing major technical difficulties. Analysis of aggregated data over time provides insights into trends, while analysis of individual cases in near real time lets companies address and resolve customer issues quickly.
At the heart of customer sentiment is text analysis, a complex process based on statistical and linguistic analyses. Text analysis is used for many different applications, including fraud detection and analysis of scientific or intelligence data. The broader the range of content, the more difficult it is to get a clear interpretation. In addition, many of the social media streams are filled with slang, abbreviations and sarcasm, all of which are difficult for analytical tools to process. Depending on the application and the software tool, users of customer sentiment solutions have varying degrees of success.