What is speech analytics and how are contact centres benefiting from it

Have you heard of speech analytics? You know it’s powerful, but you’re not quite sure what it is or how it could benefit you?

No worries! In this post, we’ll help you understand what speech analytics is, how it works, and how it’s being used in customer service—so you can decide whether it’s worth adding to your contact centre software.

1. WHAT IS SPEECH ANALYTICS?

In a contact centre, speech analytics is AI-powered technology that analyses all conversations to automatically extract valuable insights that improve customer service and save time.

Thanks to speech analytics, call centres can access key information from every conversation, such as the reason for the call, its category, the customer’s level of satisfaction, the quality of the agent’s support, and even a summary of each conversation.

2. SPEECH ANALYTICS VS VOICE ANALYTICS

Although often used interchangeably, they are actually two very different technologies:

• Speech analytics focuses on what’s being said—the verbal content (words, phrases, intentions, etc.)

For example: “This customer is unhappy.”

• Voice analytics, on the other hand, focuses on how it’s being said—the acoustic qualities of the voice (tone, pace, pauses, volume, etc.)

For example: “The customer’s voice is low and slow.”

3. WHAT TECHNOLOGIES POWER SPEECH ANALYTICS?

For a machine to understand what is said in a conversation and to extract information from it, all these technologies are needed:

3.1 ARTIFICIAL INTELLIGENCE

A set of technologies that enable machines to simulate certain human abilities, such as understanding, analysing, or making decisions. The use of AI in contact centres is already widespread—not just for interacting with customers, but also for generating insights.

3.2 MACHINE LEARNING

A branch of AI that enables the system to learn from the data it extracts. The more calls it analyses, the better it becomes at spotting issues, key terms or emotional cues. This is what allows models to evolve and improve over time.

3.3 AUTOMATIC SPEECH RECOGNITION (ASR)

ASR is the technology that converts spoken audio into text. It allows a call to be “written down” so it can be analysed.

3.4 NATURAL LANGUAGE PROCESSING (NLP)

NLP enables systems to comprehend human language beyond individual words. It allows machines to understand the meaning of a phrase, identify conversation topics, or detect customer intent.

3.5 SENTIMENT ANALYSIS

Sentiment analysis is an NLP function that detects the emotional tone in speech or text. It helps determine whether a customer is upset, thankful, frustrated, or neutral—even if they don’t say it outright.

For example:

• Negative sentiment: “I’ve been waiting 20 minutes and no one’s helping me.”
• Positive sentiment: “Thanks for sorting that out so quickly.”

4. HOW DOES SPEECH ANALYTICS WORK?

Now that we know the technologies involved, here’s how the process works—from the moment a voice is recorded to when key insights are extracted:

4.1 RECORDING THE CONVERSATION

The first step is to record the call. Every speech analytics tool needs an audio recording (for voice channels) as this is the raw material for analysis.

💡 While machines can analyse voice directly, converting it to text makes the process easier—like giving the system a “pre-chewed” version of the conversation.

4.2 TRANSCRIBING THE CALL

Once recorded, the sound wave is turned into text using a speech recognition model (ASR). Transcribing calls is also handled by AI.

💡 The accuracy of the transcription depends on both the audio quality (noise, overlapping speech, mic quality) and the model used—e.g. whether it’s trained to understand different accents or slang.

4.3 ANALYSING THE CONTENT

With the transcript ready, natural language processing (NLP) models kick in. They can:

• Categorise the conversation by topic.
• Detect keywords or relevant phrases.
• Identify customer intent (e.g. complain, ask, cancel).
• Analyse emotional tone (if sentiment analysis is included).

4.4 INSIGHT GENERATION

Finally, all the generated data is displayed in a chosen format (e.g. a dashboard or report) for review and action.

5. WHAT ARE THE BENEFITS OF USING SPEECH ANALYTICS?

The contact centre industry is increasingly talking about this tech. Teams already using it report that:

• They can identify issues without manually listening to every call.
• They’re spotting improvements in agent performance (training, best practices, etc.).
• They reduce the risk of compliance breaches, like GDPR violations.
• They monitor customer satisfaction without relying on surveys.
• They enhance the customer experience by identifying responses, scripts, and behaviours that lead to satisfaction.
• They make data-driven decisions, not guesses.

6. HOW DOES SPEECH ANALYTICS ADD VALUE TO A CONTACT CENTRE?

Since the dawn of call centres and customer experience metrics, there’s always been a supervisor or QA team who listens to calls manually to assess service quality.

This has been the case for years. A slow, partial, fully manual process—until speech analytics came along.

This technology can analyse not just calls, but also chats, emails, and WhatsApp messages—and do it in real time.

We’re no longer just talking about saving hours of listening—we’re talking about automating service quality analysis in seconds.

Thanks to automatic transcription, speech analytics tools—like our Quality Monitoring—generate the following for every interaction:

• A headline summarising the reason for the call.
• A summary of how the conversation unfolded.
• A category that classifies the type of contact.
• An assessment of the customer’s emotional state (happy, neutral, unhappy).
• A quality score for the service provided (1 to 5 stars).

All of this without human input. And best of all: for every call, if you choose.

FIND OUT HOW TO ELIMINATE MANUAL TASKS FROM YOUR CONTACT CENTRE

If your agents and supervisors are overwhelmed, optimise their time by freeing them from tasks that don’t add value.

Artificial intelligence is already capable of extracting key data from every conversation and measuring your contact centre’s service level in real time.

Get in touch to find out how you can get started.