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This article examines in detail how businesses in both B2B and B2C contexts are leveraging AI, sentimentanalysis, voice-of-customer (VoC) platforms, predictive analytics, and streaming data to capture customer insights in the moment. AI can infer customer sentiment from what theyre already saying or writing.
In simple terms, text analytics tools leverage machine learning, NLP, and other AI capabilities to break down unstructureddata from customer feedback, online reviews, customer support chat, etc. This helps extract meaningful insights from the feedback by identifying recurring patterns, themes, and sentiments.
Compared to Qualtrics Where It Wins: Stronger real-time feedback loops More robust out-of-the-box integrations AI-powered text and sentimentanalysis via Ask Athena Where It Falls Short: Fewer pre-built survey templates Less flexible for custom survey design High pricing and complexity make it a poor fit for smaller organizations 2.
Revuze’s software utilizes NLP, a form of artificial intelligence, and computational linguistics to filter for words that reveal customer attitudes and emotion, which are revealed in a sentimentanalysis report. Interestingly, Revuze was named by CB Insights as an “early stage Israeli B2B Software Company to Watch.”
Unstructureddata is invaluable for understanding customers’ feelings and thoughts, but only if your analysis respects the nuances. When customers give feedback through surveys and in day-to-day conversations with your company, that’s unstructureddata. It depends. Tagging is tagging.
Lesson #22 Revisited: Start Small with Transactional VoCYoull Thank Me Later AI is changing the game in transactional VoC programs with predictive insights and automated sentimentanalysis. Still, its human expertise that interprets those insights and drives impactful customer experience changes.
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