Sentiment Analysis
Sentiment analysis is the use of AI and natural language processing to determine the emotional tone behind open-text customer feedback — classifying responses as positive, negative, or neutral, and often identifying specific themes or emotions within the text.
This matters because a large share of valuable CX feedback comes in unstructured form — a comment box, a support chat transcript, a social media mention — that traditional survey scoring can’t capture. Sentiment analysis allows organisations to process this feedback at scale, rather than relying on manual review of every comment.
Sentiment Analysis vs Simple Keyword Matching
Basic keyword matching flags specific words (“delay,” “rude,” “excellent”) but misses context and nuance — sarcasm, mixed sentiment within one comment, or comments that don’t use obvious keywords at all. Modern AI-driven sentiment analysis can interpret tone and context far more accurately, which matters significantly in a multilingual market like India where direct translation often loses nuance.
How LitmusWorld Helps
LitmusWorld’s capabilities apply sentiment analysis across open-text feedback at scale, surfacing emerging themes and flagging emotionally negative responses for urgent follow-up — even across multiple Indian languages.
Related terms: What Is a CX Platform? · Voice of Customer