Advanced

Sentiment Analysis

LLM-based Sentiment Analysis goes beyond merely capturing what customers are saying, it delves into their emotional state as well. By effectively addressing negative sentiments, companies can enhance customer retention and so much more.

Understand & Analyze Sentiment

Every conversation is analyzed and provided with a total sentiment score, individual scores for the agent and customer, and a detailed explanation to justify the score.

Leverage Insightful Data

Aggregated sentiment data helps identify trends in customer emotions. This allows companies to make informed, data-driven decisions, optimize their strategies, and strengthen customer relationships.

Quickly Visualize & Refine

Using sentiment heatmaps or filtering data by sentiment label/score helps quickly identify and address issues. By understanding sentiments effectively, companies can improve customer retention.

Sentiment Score

Decode & Evaluate Customer Sentiments

Each conversation undergoes sentiment analysis, then produces a comprehensive overview of its emotional tone. This includes a total numerical score ranging from -100 to +100, along with separate scores for both the agent and the customer.

The analysis provides a detailed explanation and reasoning to justify each score. This also includes highlighting specific phrases within the conversation to help visualize what contributed to the overall sentiment assessment.

Leveraging Aggregated Data for Strategic Insights

Over time, aggregated sentiment analysis data can be utilized to identify trends and patterns in customer emotions related to specific products, services, or processes. By analyzing how customer emotions evolve, businesses can proactively address issues and enhance their offerings to better meet customer needs.

This comprehensive understanding of customer emotions enables companies to make data-driven decisions, optimize their approaches, and ultimately build stronger, more resilient customer relationships.

Sentiment Trend Analysis and Reporting
Narrow-down Search Sentiment Score

Identify & Address Key Issues

Whether you utilize the sentiment heatmap or filter aggregate data by sentiment labels or score ranges, these tools enable companies to spotlight calls with potential issues for immediate review. By prioritizing conversations that reflect recurring problems, you can swiftly address and resolve the most pressing concerns. Additionally, this functionality helps managers develop targeted training plans by highlighting common themes and issues, ensuring a more focused approach to improving customer experience.

Experience MiaRec's Sentiment Analysis

MiaRec Sentiment Analysis feature is leveraging the latest advancements in Generative AI and LLM technologies.
Discover how it can evaluate customer, agent, and overall sentiments to provide a complete view of your interactions.
Click below to start the interactive product walkthrough:
 

Sentiment Analysis FAQs

Is sentiment scoring based on tone of voice?

No. Sentiment scoring is based on the contents of the transcription. We have found that sentiment scoring based on text is more accurate than tone of voice because it captures the specific words and phrases used, providing clear context and meaning. Whereas tone of voice can be ambiguous and influenced by various factors, leading to potential misinterpretations.

Can we set up alerts to notify supervisors if a call has a low sentiment score?

Yes. Alerts can be automatically sent out to specific email addresses based on certain criteria. For example: Send an alert to john.smith@acme.com if a call has a sentiment label of “Very Negative.”

How does MiaRec’s sentiment scoring handle ambiguous or mixed sentiment within a single call?

MiaRec’s Generative AI-powered Sentiment Analysis scores calls based on the entire context of a conversation. For example, if 99% of a call is negative but the agent resolves the customer's issue at the end, the call would be scored as "Positive."

Please note that sentiment scoring may vary depending on how the sentiment analysis prompt is customized.

How do we define a positive vs a negative call?
  • You can customize the Sentiment Analysis prompt in MiaRec by going to the Administration Tab > AI Assistant > Prompt Library > Sentiment Score

Edit Prompt

  • Scroll down to “System Instructions”
  • Edit the instructions (prompt) accordingly

Prompt Instructions

 

Experience MiaRec

See How Customer Sentiment Can Transform Your Organization

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