For example, identify customers who are dissatisfied with their experience, and proactively offer solutions or improvements to address their concerns.
Natural language processing (NLP) techniques can be used to extract insights from unstructured data such as customer comments and reviews. Sentiment analysis can be used to classify the feedback as positive, negative, or neutral, and identify the underlying reasons for customer dissatisfaction.
Another approach is to use machine learning algorithms to identify patterns in customer behavior that may indicate dissatisfaction. For example, if a customer who normally engages with the company frequently suddenly reduces their engagement or stops using the company's services altogether, this could be an indication of dissatisfaction.
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