Challenges to Expect When Conducting Sentiment Analysis

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Analyzing human speech is tricky, so you need to overcome several challenges while employing sentiment analysis. It’s hard to preset all scenarios. People may use slang, synonyms, sarcasm, or mispronounce/misspell words. One word may have different meanings in various contexts, leading to ambiguity.

As it’s possible to train AI to understand long-form and edited texts, errors, metaphors, or emojis are another story. Is the word “bad” actually negative? What about this word in the context, such as “I want it so bad”? That’s why sentiment analysis software requires regular improvements and training to compete with humans in understanding phone number lead the nuances of different languages.

5 Ways to Enhance Customer Experience Using Sentiment Analysis
Listening is the best and most accurate way to learn what makes a client feel positively or negatively. What do people have to say? To answer this question, you need a text-mining tool. With its help, you can provide a faultless customer experience by converting people’s voices into valuable data. The most popular ones include Hubspot’s Service Hub, Hootsuite Insights, MonkeyLearn, Awario, Lexalytics, and others.

But having data is only the first step. You should know how to apply knowledge and act. Let’s examine how sentiment analysis benefits a company’s efforts to enhance the customer experience.