Sentiment Analytics

Understand what customers are feeling about their experience.

Sentiment Analytics

Understand what customers are feeling about their experience.

Get beyond what was said. Use sentiment analysis for insight into how customers feel about conversations, chatbots, IVR's and brand and entity level points of view.

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Sentiment analysis shows information by channel, brand, entity, agent and customer to provide insights along the customer journey.

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Sentiment unlocks a critical element of customer experience learning

SuccessKPI's five styles of sentiment analysis allow you to understand agent sentiment, sentiment over time, sentiment by channel and sentiment around entities like brands, locations or custom products. Combine positive, negative and neutral scores with other data to derive knowledge of what correlates to emotions within your conversations.

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Gain a connected understanding of the entire conversation and customer journey through all channels

Understand what was said, what was meant, and what was felt. Re-think your conversation strategies, develop new tools to improve agent awareness and transform digital conversations with this deep contextual understanding across the contact center.

Sentiment in conversations is recorded by assigning labels (Negative, Positive, Neutral) and confidence scores, which are stored in the enterprise data warehouse. In SuccessKPI, use these label assignments and confidence scores as attributes and metrics for data discovery and business intelligence reporting. As well, use sentiment as a condition to drive your Playbooks.

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Sentiment over multiple languages

Launching a new product or service across multiple regions? SuccessKPI detects sentiment in more than 30+ languages. Perform sentiment analysis by language and better understand the general sentiment.
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Understanding sentiment unlocks a new, highly valuable dimension in your Customer Experience analytics toolkit by identifying how people feel about their conversations with your company.

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5 styles of sentiment analysis

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Our five styles of sentiment analysis uncover answers to these kinds of questions:

  1. Sentiment over time
    Do your agents improve, recover, or degrade over the course of a call or over a chat or SMS? When do customers tire of your chatbot?
  2. Sentiment by channel
    Do customers prefer certain channels? Do they perceive the same information and the same communication in the same channel and with the same tone?
  3. Sentiment by agent vs. customer
    How do the interplay of emotion and sentiment impact your team's delivery of customer experiences?
  4. Sentiment by brand
    Which brands attract the most positive and negative sentiment?
  5. Sentiment by entity
    What's happening at the elemental level? For example, if a customer says "the fries were tasty but the restaurant was dirty," - how will you use this information to change the overall customer experience?