Sentiment Analysis

Gain clear insight into customer attitudes with sentiment analysis

CallMiner’s Eureka conversation analytics platform captures customer interactions and analyzes sentiment across all channels.

Driving business performance starts with understanding your customers

The decisions of customers are driven by sentiment. From attitudes about a brand to opinions of products or services, sentiment plays an outsized role in customer churn, loyalty, and satisfaction. Savvy companies capture sentiment analysis to identify their customers’ positive, neutral, or negative leanings and use that data to better understand customers’ opinions, address their needs, and deliver exceptional experiences.

Analyzing sentiment is an incredibly complex endeavor and choosing the right tools is critical. Survey-based solutions will deliver insight into only a small fraction of your audience. Technology that mines contact center conversations offers a more comprehensive approach – but it requires best-of-breed, automated tools to ensure accuracy, ease-of-use, and cost efficiency.

CallMiner offers a leading sentiment analysis solution in its Eureka conversation analytics platform. By measuring the acoustics in a speaker’s voice and evaluating the overall content and context of a conversation, Eureka enables you determine the true meaning behind spoken words and gain deeper insight into your customers’ sentiment.

The Forrester Wave™: Conversation Intelligence for Customer Service, Q3, 2023

Essential elements of a sentiment analysis solution

Automation. Sentiment analysis tools offer incredible insight – but they can be incredibly difficult to configure as well. Fully automated conversation analytics solutions allow you to reap greater insight without requiring a lot of hands-on oversight.

Multiple languages. Evaluating 100% of your customer conversations for sentiment analysis usually requires solutions that have multilingual capabilities.

Demographics tracking. The ability to dynamically filter out data based on demographic traits can help uncover essential details and enable more targeted analytics campaigns.

Omnichannel support. Your customers communicate with you on more than one channel, which is why your sentiment analytics solution must monitor multiple channels as well. Choose a solution that can capitalize on vast volumes of data from public forums, blogs, surveys, and other sources.

Custom reports. Because your reporting needs are unique, your sentiment analysis technology must enable a significant degree of customization. The right product will allow you to choose visuals that support your goals without requiring a great deal of technical knowledge in data analytics.

The CallMiner Eureka platform

CallMiner provides speech analytics solutions that help drive call center optimization and enhance the customer journey experience. Our Eureka conversation analytics platform transforms the voice of customers and agents into operational intelligence through automated performance scoring, sentiment analysis, topic discovery, and omnichannel customer journey mapping .

CallMiner’s sentiment analysis scores interactions by combining the acoustic characteristics of a speaker’s voice with the context of the conversation. With a sentiment analysis score, you can easily measure relative sentiment in various cross sections of calls, agent groups, and time frames .

To evaluate sentiment, we measure several vocal characteristics, including the amount of physical stress in the voice, the changes in stress, and the rate of speech. This data can help you swiftly identify and act on the root cause of issues, addressing a customer’s problems before they reach critical mass.

Benefits of sentiment analysis with CallMiner

By scoring the sentiment in conversations with your customers, you can:

• Uncover opinions about your brand’s reputation and take steps to improve it.

• Gain insight into customers’ attitudes about your products and services as well as specific campaigns and other topics.

• Enjoy a unified view of the complete customer journey.

• Get insight into the effectiveness of contact center agents and customer support representatives by evaluating how well they engage with callers and move the needle on customer sentiment.

• Identify common pain points across segments and pinpoint areas for improvement in customer support or satisfaction with product lines and services.

• Minimize customer churn by providing agents with coaching and real-time prompts based on customer sentiment that enable them to better address the needs of each caller.

Why CallMiner is #1

CallMiner is ranked #1 in overall customer satisfaction among speech analytics vendors. Which is not surprising, given the way our company has pioneered the speech analytics industry since 2002. With billions of hours of conversations mined, we’ve developed a suite of highly effective solutions that deliver exceptional performance at scale and enable companies to better hear and understand the voice of their customers.

Our sentiment and conversation analytics solutions are agnostic to the source of system that captures data. We integrate easily with all the market-leading technologies for call recording, chat, and email as well as popular social networking sites.

Additionally, we provide a customer success organization that ensures our customers realize the ROI they’re seeking from our technology. We offer solution packs with prebuilt use cases and topics based on content for rapid time to value. And our Playbooks provide step-by-step instructions for utilizing your Eureka content to achieve quantifiable ROI.

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Frequently asked questions.

Sentiment analysis is a form of speech analytics that monitors conversations and evaluates language and voice inflection to quantify the attitudes and opinions of an individual speaker. Companies use sentiment analysis to evaluate how customers feel about the business, a product or service, or a specific topic.

After using natutral langage processing (NLP) to identify the words used in a conversation and evaluating the acoustics of a speaker’s voice, sentiment analysis uses articifical intelligence and machine learning to score the interaction and quantify the speaker’s positive, neutral, or negative attitudes or opinions. The acoustic components of the converdation that affect the sentiment score inlude the rate of speech, the amount of stress or frustration in a customer’s voice, and changes in stress levels indicated by the person’s speech.

Sentiment analytics can help brands better understand their reputation among customers and take action to improve it. Sentiment analysis can also reveal customer attitudes toward specific products, services, and campaigns. By providing real-time insight and prompts for agents based on the sentiment customers are expressing, sentiment analytics can help agents to take the right steps to positively resolve difficult conversations and minimize customer churn.

  1. Use natural laguage processing (NLP) and speaker separation to identify the words spoken on the call (content) my both the customer and the agent.
  2. Use speech analytics to measure the acoustics of the call for pace, stress, agitation, etc., (context) in the caller's speech.
  3. Use artificial intelligence and machine learning algorithms to score the conversation.
  4. Separate the scores into positive, negative and neutral segments for purposes of assigning to each conversation you hold with a customer.


We can not only tell our customers what their patients are saying, we can tell them how they feel when they call us.

Peter Hamlin

Sr. Director, Product Development - Avadyne Health