Which linguistic analysis technique is MOST commonly used by major retailers to predict customer churn from support interactions?

Natural Language Processing (NLP) has transformed how retailers understand and connect with customers. From analyzing sentiment in product reviews to powering sophisticated chatbots, language AI is reshaping retail experiences. This poll tests your knowledge about how language technology is being deployed in cutting-edge retail applications, particularly for predicting and preventing customer churn.

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Sentiment analysis combined with topic modeling to identify frustration patterns
Phonological pattern recognition to detect stress in customer voice recordings
Syntactic parsing to measure sentence complexity as an indicator of customer patience
Morphological analysis to identify diminishing word counts in sequential interactions