Moving Beyond Pitch and Volume: Importance of Keywords for Accurate Call Sentiment Analysis

Welcome to the world of call sentiment analysis, where understanding customer emotions goes beyond just tone of voice. Accurate sentiment analysis is crucial for deciphering customer interactions and extracting meaningful insights. And while sentiment analysis has gained popularity, one key ingredient often goes overlooked – keywords. Keywords play a pivotal role in achieving precise call sentiment analysis, as they provide crucial context, and industry-specific insights, and allow for customization. Let’s explore the paramount importance of keywords in unlocking the true potential of call sentiment analysis. Join us on this insightful journey to uncover the secrets behind accurate call sentiment analysis and how keywords hold the key to unraveling the sentiment puzzle. Get ready to transform your understanding of customer sentiments with the power of keywords! 

Avoiding Call Sentiment Confusion- The Importance of Keywords in Accurate Analysis 

Call sentiment is often determined by the pitch and volume of the customer’s voice because they are easily measurable. But there may be a lot of confusion while determining sentiments through call recording, since a surprised, loud customer can be mistaken for an angry customer, or a quiet customer who has lost hope about resolving the issue can be misunderstood as being satisfied with the deliverables. As a result, the output generated can be inaccurate or completely false. To avoid such confusion and inaccurate results, relying on keywords is important. 

Decoding the Call Sentiment with CX Analytics 

It is critical to understand what is stated during a conversation in order to identify call sentiments. Thus, the keywords detected during the call script play a crucial part in determining whether the call was positive, negative, or neutral. Based on the keywords, a call might be classified as positive or negative. 

Our CX Analytics solution analyzes the agent-customer interaction and converts the speech into text. The text is further used to extract keywords to detect accurate sentiments. 

It provides a separate sentiment report for both customers and agents highlighting the percentage of each sentiment. 

It also provides a separate report to showcase the top keywords used for numerous sentiments. For example, the keyword “thank you” denotes a pleasant attitude. As a result, a call can be classified as positive if the consumer uses the phrase “thank you” frequently.  

The percentage of “thank you” in the graphic below is 18%, indicating that it was a positive call. 

Our CX Analytics also has a smart featured keyword detection. It outputs the percentage of the product’s specific keywords that were used by the customer and the agent.  This makes it simple to update the product to offer better customer service because it is clear what the agent is focusing on and what features customers expect from the product.

Accurate call sentiment analysis goes beyond just the pitch and volume of a customer’s voice. By leveraging the power of keywords, call centers can gain valuable insights into customer emotions, preferences, and pain points, enabling them to make informed decisions and improve customer satisfaction. 

Are you ready to unlock the true potential of call sentiment analysis with the power of keywords? Don’t miss out on the opportunity to gain actionable insights from your customer interactions. Contact us today to learn more about how our advanced call sentiment analysis tools can help you optimize your call center operations and enhance customer experiences. 

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