Speech technology is an innovative solution for call centers to improve both customer satisfaction and internal operations, the most impactful of which are speech analytics and speech recognition.
While sometimes used interchangeably, both tools serve different purposes, working together as a powerful duo. Let’s have a look at what makes them unique, but also how they compliment each other to enhance call center productivity.
What’s the difference between speech analytics and speech recognition?
Speech recognition
Speech recognition transcribes spoken words into written text. It’s useful for call centers in capturing live conversations and turning them into transcripts in real time, acting as a powerful virtual assistant to agents. It’s the technology behind speech-to-text tools and Interactive Voice Response (IVR) systems that empower call centers to automate the repetitive, every day tasks that take up valuable time and resources.
Speech analytics
Speech analytics goes even deeper than speech recognition. It analyzes conversations and identifies speech patterns, sentiment, tone of voice, and even emerging trends. It takes into account keywords and emotions to assess criteria like agent performance and compliance, and can even gauge how satisfied customers are based on their language patterns. Unlike speech recognition, speech analytics is all about understanding the context and intent of interactions. It then generates actionable insights after each call to guide agents and managers towards strategy improvements.
Similarities and differences
Key differences
The main distinction between speech recognition and speech analytics is their purpose: the former simply converts spoken words into text, while the latter interprets the deeper meaning of those words. Think of speech analytics like an add-on to speech recognition – it enhances its abilities by turning the data it generates into actionable insights.
Plus, recognition is more technically focussed than analytics. Its main goal is transcription accuracy – getting each and every word correct to provide authentic results. Analytics, on the other hand, is a more strategic tool. Its aim is to produce data, insights, and analysis for call centers to use to their advantage.
Finally, both tools have separate applications in the call center: speech recognition powers tools like auto-transcription and IVR, while analytics handles compliance, sentiment analysis, and trend identification.
Overlap
While both technologies are clearly different in their purposes, they mostly work hand-in-hand. Speech analytics simply wouldn’t function without speech recognition: the latter feeds the raw data it collects into speech analytics. Together, they transform customer interactions into powerhouses of information and insights. Their synergy only amplifies their individual abilities, creating an all-round solution for call center enhancement.
How they work together to improve call centers
Individually, both tools can ease the manual burden of quality assurance and call auditing. But together, they create a seamless flow of information and insights. Here’s how:
- Better agent performance: Speech recognition transcriptions can be used to train agents in optimal interactions, while analytics can automatically identify areas for improvement, such as objection handling or slow issue resolution.
- Enhanced customer experience: Real-time transcription guarantees accurate documentation and makes interactions clearer during calls, while analytics identify dissatisfaction, allowing managers to step whenever necessary.
- Full compliance visibility: Speech recognition generates the transcriptions – speech analytics scans them for regulatory compliance to reduce risks.
Benefits of speech technology in call centers
- Time-saving: Thanks to speech recognition automating note-taking, transcription and compliance checks, agents have more time to spend on meaningful customer interactions.
- Better insights: Analytics generates a deeper understanding of customer needs and agent performance than humans are able to extract from manual quality assurance.
- Cost-effectiveness: With less human error and labor, automation reduces operational costs.
- Improved customer satisfaction: Real-time sentiment analysis helps resolves issues proactively, before they have time to take root.
How Voiso implement speech analytics and recognition
With Voiso, speech recognition and analytics is part of the package. Our powerful call center software offers comprehensive speech technology with numerous features:
Real-time transcription
Voiso’s speech recognition ensures accurate documentation during live calls, acting as a virtual assistant for agents.
Sentiment analysis
Our speech analytics tool can identify customer emotions and generate call scores to point towards negative or positive outcomes, enabling managers to address dissatisfaction immediately.
Compliance tools
Voiso’s speech analytics automatically spots and flags regulatory violations or language that fall outside the compliance guidelines, preventing issues before they evolve.
Performance monitoring
With Voiso, speech analytics evaluate agent performance and even suggest actionable improvements to boost the team’s efficiency.
Conclusion
Powerful on their own but better together, speech recognition and analytics are the ideal solution for call centers looking to become more customer-centric, efficient and compliant.
With Voiso’s AI-driven speech analytics, you get the best of both worlds – every conversation has the potential to result in actionable insights.
