Speech Analytics

What is Speech Analytics?

The speech analytics platform enables you to create an application that is simple to use and gets you closer to your consumer intent through empathy-based sentiment analysis. Speech-to-text transcription enables rapid and accurate call analysis.

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Benefits of Speech Analytics Software

Multilingual transcription

Analyze and convert multiple languages to get a better insight

Accuracy

Use domain-specific targeted words and phrases, such as addresses, currencies, years, and abbreviations, to improve the understanding of your transcription.

Manage operations efficiency

Analyze your team’s performance and design staff training based on conversation analytics reports. The outcome will be seamless customer handling and improved CX.

Time-saving report extraction

Flexible pricing options provide more transparent cost management.

Reduced costs due to automation

Reduce manpower costs by automating phone calls or audio/video file conversation analysis.

Improve strategic business decisions

Improve strategic choices using customer sentiment and conversation information to optimize serviceability and product offerings.

 Features of a speech analytics platform

1
Wide coverage

Use the large user base to cover global languages with speech-to-text.

2
Content filtering

Redact anything in your transcription that may be inappropriate or include personal or confidential information.

3
Noise robustness

easily recognizes and converts noisy background audio without noise cancellation.

4
Speech adaptation

Add industry-specific or specific keywords or phrases for automatic word recognition to personalize your speech analytics application.

5
Real-time speech

Real-time extraction of speech recognition results

FAQ

Frequently Asked Questions

What is speech analytics?

Speech analytics transcribes voice calls to provide deep insights, metrics, and trends. It uses AI services like natural language processing, transcription, and speech technologies to understand and analyze voice conversations. The call center uses these insights on each voice interaction to assess customer experience, evaluate agent performance, and monitor the company’s strengths and weaknesses.

How does speech analytics work?

Analysis

Speech analytics categorizes keyword spots, redacts (for compliance), and reports call analysis.

Insights

The speech analytics platform reports sentiment, agent performance, call quality, and compliance monitoring.

Processing of data

It examines audio recording and calls metadata using various AI services, such as transcription, tonality-based sentiment analysis, and automated speech recognition.

What advantages do speech analytics offer?

Keep track of important KPIs

Speech analytics can help customer support teams to build up analysis on any number of customer interaction moments. It can be anything from customer happiness and average handling time to compliance breaches and supervisor escalations.

 

Speech analytics near-real-time feedback

Supervisors may provide agents customized feedback almost instantly due to quick analysis and complete call coverage.

 

Uncover any hidden inefficiency

Leadership can understand what’s impacting contact center KPIs and find inefficiencies by keeping an eye on them.

 

Personalized training

Supervisors and learning and development teams may create a personalized training session for agents using call data.  

        

Enhance user experiences

Teams may look at the factors driving outstanding customer experiences and signs of negative ones using sentiment analysis, which can help them lower customer churn.

 

Boosts call coverage significantly

Historically, call center QA teams check 2-4 calls per agent each month. Organizations may analyze all voice calls using speech analytics.

Is speech recognition and voice recognition same?

Speech recognition recognizes said words, while voice recognition recognizes the speaker’s voice. They both have distinct roles in technology. Therefore, this is important.

What is sentiment analysis?

Sentiment analysis, often known as opinion mining, is a technique used in natural language processing (NLP) to determine the emotional tone of a text. Businesses commonly use it to identify and categorize ideas regarding a particular product, service, or idea.

What do call center speech analytics entail?

Call centers use speech analytics to listen to voice recordings or real-time customer calls to understand the demands and behaviors of the customer.

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