Decode Your Conversations with Topic Extraction

Uncover key themes, spot trends, and gain actionable insights—all without the manual effort. Topic Extraction leverages AI-powered speech analytics to turn conversations into actionable insights to help you make smarter and faster decisions.

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Let AI Reveal What Truly Matters

Save Up to 40% of Your Time

AI-powered Topic Extraction cuts processing time by 30–40%, eliminating manual note-taking and human analysis.

Embrace AI-driven Precision

Let AI pull out the most important parts of your conversations so you can find the most relevant information.

Uncover Hidden Opportunities

Unlock future opportunities by identifying hidden customer patterns and needs, allowing you to stay ahead of the game.

We’ve helped thousands of global companies

Case studies featuring customers who are building faster.

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Revolutionizing Revolut’s Efficiency and Saving 40+ Hours

“Thanks to CloudTalk’s reliability, we could improve sales teams’ performance and close more deals than we could have ever imagined.”

Jamie Devlin
Head of Operations

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Increasing productivity for 200 customer support agents

“With CloudTalk’s Analytics I now get to see every step of the way. We can find discrepancies and gain a much better understanding of our teams.”

Nelly Donnelly
Service Delivery Manager

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Delivering success for Glovo’s customer support team

“CloudTalk improved our team’s cost and efficiency. The script feature allows us to lead the calls in a much more systematic way.”

Yohann Bensadoun
Global Supply Growth

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Scaling outbound calls for MyHeritage 158 sales agents

“We have seen a significant increase in our outbound call volume. We can now reach out to more prospects and customers than ever before.”

Elay Sasson Call
Center Manager

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What is Topic Extraction?

Topic Extraction is an AI-driven feature that listens to conversations, analyzes speech, and instantly pinpoints the most important topics—without you lifting a finger. It scans through your calls, identifying key themes, trends, and insights.

By leveraging advanced AI speech analysis, Topic Extraction helps you cut through the noise and focus on the crucial factors that drive business results.

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How Does Topic Extraction Work?

Topic Extraction uses Natural Language Processing (NLP) and machine learning to analyze customer interactions. It collects data from calls, converts speech to text, and then identifies key topics by grouping similar words.

This technology detects patterns and categorizes information, giving you a clear summary of what was discussed—without needing to comb through transcripts. Whether it’s customer feedback, business meetings, or call center recordings, Topic Extraction transforms speech into actionable data.

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Benefits of Topic Extraction

Maximize Results with the Right Focus

Save Time, Money and Effort

Skip the tedious task of reviewing hours of conversations. AI-powered Topic Extraction scans speech data in seconds, so you can focus on decision-making instead of manual analysis. This saves you from time-consuming tasks while cutting costs.

Uncover Hidden Trends

AI doesn’t just capture what’s said—it detects patterns and emerging trends across multiple conversations. Stay ahead of market shifts, customer concerns, and business opportunities without digging through endless transcripts.

Detect Issues in Real-Time

With fast insights from Speech Analytics, you can quickly detect and respond to emerging customer concerns or operational risks. Whether it’s misaligned messaging, service gaps, or compliance red flags, Topic Extraction helps you take action before issues escalate.

Boost Efficiency and Accuracy

AI eliminates human error and bias in data analysis. By automatically categorizing speech into key topics and themes, it ensures consistency and precision, helping teams streamline workflows and take action with confidence.

Actionable Insights

Focus on the Data That Drives Action

See how to leverage AI Topic Extraction to turn speech into real-time, data-backed decisions.

Solve Real-World Business Challenges

AI-powered Topic Extraction helps businesses across industries unlock valuable insights from conversations, improving efficiency, customer experience, and compliance.

Financial Services & Banking: Ensure regulatory adherence by monitoring customer calls for compliance risks, fraud detection, and service quality.
Contact Centers & Customer Support: Analyze customer interactions to detect common complaints, improve agent performance, and provide faster resolutions.
Healthcare & Insurance: Extract key themes from patient calls to identify service gaps and ensure compliance with healthcare regulations and industry standards.
E-Commerce & Retail: Analyze customer feedback and support interactions to uncover trends in product issues, buying behavior, and service expectations.

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How to Implement Topics Extraction in CloudTalk?

On the dashboard of your CloudTalk account,
navigate to Account > Settings.
Go into the AI Conversation Intelligence tab and make sure it is On.
Under Features, turn on Topics Extraction and save the changes.
Once this setting is updated, changes are reflected for all users.

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Features

Other features you might like

Call Summary & Tags

Eliminate repetition and boost efficiency with AI-powered post-call Summaries & Tags.

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Flagship Feature

Sentiment Analysis

Get immediate feedback on your caller’s mood by following their sentiment shifts.

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Call Transcription

Analyze and understand your calls by automatically transcribing them with AI.

Learn more

Talk/Listen Ratio

Track the Talk/Listen Ratio to provide data-backed feedback and enhance CX.

Learn more

Frequently asked questions

Everything you need to know about the product and billing.

What is Speech Analytics used for?

Speech analytics is used to analyze recorded customer conversations to extract valuable insights, such as identifying key topics, trends, and common themes.

Why is Speech Analytics important?

Speech analytics is important because it allows businesses to transform unstructured voice data from calls into actionable insights. It helps businesses understand customer needs, improve service quality, monitor agent performance, and ensure compliance with industry regulations.

What are the benefits of Speech Analytics for call centers?

The benefits of speech analytics for call centers include improved agent performance through targeted coaching, enhanced customer satisfaction by identifying and resolving issues faster, and greater operational efficiency through automated analysis of large volumes of calls.

What is Speech Analytics software?

Speech analytics software is a tool that uses AI and machine learning to analyze spoken language in customer conversations. It transcribes calls, detects keywords, evaluates tone, and identifies sentiment, helping businesses gain insights into customer interactions. This software is typically used in call centers to monitor performance, improve customer service, and extract key business intelligence.

What is the difference between Speech Analytics and Voice Analytics?

The key difference between speech analytics and voice analytics is that speech analytics focuses on the content of the conversation, analyzing the words spoken, detecting keywords, and identifying sentiment. Voice analytics, on the other hand, examines vocal characteristics such as tone, pitch, and emotion, regardless of the content. Both work together to provide a comprehensive analysis of customer interactions.

Which businesses can benefit from using Speech Analytics?

Businesses that handle a high volume of customer interactions, such as call centers, customer service departments, sales teams, and financial services, can benefit from using speech analytics. Any organization that relies on understanding customer needs, improving service quality, and optimizing agent performance can leverage speech analytics to enhance customer satisfaction and operational efficiency.

How to improve service quality with Speech Analytics?

Speech analytics enhances service quality by identifying patterns and trends in customer interactions, allowing for the detection of recurring issues. It facilitates agent training by focusing on key areas to improve their performance. Additionally, it helps adjust customer service strategies and ensures compliance with quality standards.