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Customer Sentiment Analysis: Definition, Benefits and Best Practices

SurveySparrow

By the end of this blog, you will be clear about the definition, importance, benefits, and use cases. There are two approaches- Lexicon-Based and Machine Learning. Lexicon-Based Approach This method relies on pre-made lists of words and phrases labeled with positive, negative, or neutral sentiments. Offer personalized support.

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Digital Customer Success vs COVID – One Year Anniversary Recap

Totango

In order to support their 311% growth last year, they had to act fast to scale operations – building a CS team from scratch, defining a customer journey, implementing a Customer Success platform, and automating the processes, communications, and customer experiences needed to scale – in a matter of weeks.

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5 Creative Ways to Use AI for Sentiment Analysis

Lumoa

From enhancing customer support experiences to predicting market trends, AI empowers businesses across industries to make data-driven decisions that resonate with their audience. Traditional methods often use sentiment lexicons or predefined lists of words and phrases associated with specific sentiments.

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Embrace Digital Channels to Drive Transformation

Upstream Works

The term “digital channels” has become core to the contact center lexicon recently, and for good reason. Both AI and mobility create a broad range of attractive use cases for digital communication channels, and this simply makes the customer engagement opportunity larger than what traditional communication channels can support.

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The Stability of Customers' Sentiment, Satisfaction and Recommendation Intentions

Bob Hayes

I employed machine learning to create a sentiment lexicon to scale each word along a sentiment continuum. product quality, account management, tech support) were more highly related to recommendation intentions (average r =.53) Customer Sentiment: Customers were asked, " Using one word, please describe COMPANY'S products/services. "

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