AI-powered speech analytics reveals hidden insights in the calls your contact center receives. These insights help you create a better experience for your customer and a more efficient system.
Table of contents
- What is call center speech analytics?
- Why AI-powered speech analytics?
- Industry Use Cases for AI Voice Analytics
- Benefits of AI voice analytics across industries
Speech analytics is not just a conversation transcription tool. You can program it to identify and analyze words, phrases, categories, and themes within a conversation. It can uncover patterns and pain points that might otherwise go unnoticed.
Speech analytics lets you hear the voice of your customer like it has never been heard before.
What is call center speech analytics?
Call center speech analytics is the process of using AI voice analytics to analyze call center recordings for customer sentiment, intent, and emotions. This can be used to improve customer service, identify call center agent issues, and track call center performance.
Speech analytics can help call center managers in a number of ways, including:
- Monitoring call center agent performance
- Identifying call center customer sentiment
- Tracking call center KPIs
- Improving call center quality assurance
Call center speech analytics can be used to improve customer service by identifying customer sentiment and emotions. This can help call center agents address issues more effectively and provide a better customer experience.
Why AI-powered speech analytics?
Much of your call center’s responsibility is keeping your customers satisfied. 33% of customers say they will walk away after one bad experience.
Great customer service looks like this:
- Meeting your customer’s needs
- Serving your customers quickly and efficiently
- Empathy towards your customers’ issues
Here are five reasons your customers will thank you for adopting AI-powered speech analytics.
You’ll grow customer insight
Data helps you improve every aspect of your call center. It helps you focus your strategy on continuing the things that you are doing right and correcting those you aren’t.
More data means more accurate analytics. As your sample size of data increases, you can predict outcomes with more accuracy.
If you are an average contact center, each of your agents receives, on average, 50 calls per day. That’s a lot of data to pass up without leveraging speech analytics.
Speech-to-text analytics uses machine learning and natural language processing to transcribe and classify conversations. You can categorize and score calls to find out:
- Customer intent
- Cause for dissatisfaction
- Reasons for call ends
The more you know about each conversation, the more you can fine-tune your approach. Using this data you can create an actionable plan to make adjustments to meet your customers’ needs.
You’ll have a “fly on the wall” in every call
Two problems that plague customers and call centers alike are:
- Low first call resolution rates – having to call back multiple times for the same reason is a major source of customer frustration
- Average handle time – being transferred agent to agent because no one has the answer takes up valuable time in your customer’s day
With speech analytics, you can listen in on conversations and find areas of knowledge that agents lack. Speech analytics provide objective and targeted information to your agents about what they are doing right and how they might improve.
When your agents are more knowledgeable your customers reap the benefits. Each time they interact with your call center, the agents they are connected with are more likely to have all of the information necessary to resolve their query.
As your agents are trained to be more efficient, your average handle time also improves. This means your customers are on hold and on the line for less time.
You’ll teach agents EQ
Sometimes the conversations that happen in the call center are loaded with emotions like frustration and dissatisfaction. Having an empathetic ear on the other end of the conversation lets your customers know you hear them and are doing everything in your power to assist.
Studies have found that the best way to develop emotional intelligence is through practice. Agents can practice soft skills like empathy, active listening, and de-escalation by leveraging real-time speech analytics. They can coach your agents during customer calls and provide recommendations.
Empathetic agents take ownership of the problem and strive to see it through. Your customers feel valued, heard, and taken care of.
You’ll root out problems & provide root cause solutions
Customer intent gives you insight into the reasons your customers are calling and can help you identify problems in your products and services. Speech analytics can identify patterns in customer intent that can be used to solve issues before they become problems for your customers.
For example, if a high number of customers are calling to troubleshoot why they can’t log in to their accounts, there may be a problem with your website. You can reduce the number of customers this problem affects simply by being aware of its existence.
The fewer problems your customers encounter, the better. Your customers will thank you for being proactive in your customer service strategy.
You’ll exceed expectations
Speech analytics identifies what your customers want and what they expect out of their experience. You can make sure the service you are providing is in line with both of these with the use of scorecards.
You can create scorecards for each call that have core customer service values baked into them. As you hone in on what your customers need, want, and expect you can adjust scorecards to reflect those findings.
Speech analytics lets you automatically score these conversations and provide instant feedback to your agents creating an environment for continuous improvement that makes a happy customer.
Industry Use Cases for AI Voice Analytics
AI voice analytics can be used in a number of industries to improve customer service and support, including:
Analyze call center recordings to improve customer service, identify call center agent issues, and track call center performance.
Call center AI voice analytics can be used to detect fraud, compliance issues, and customer sentiment. This can help banks and financial institutions improve customer service and prevent losses.
Analyze contact center recordings to improve patient care and identify potential issues. Track patient call data, identify call center quality issues, and monitor staff performance to improve call center operations for patients.
Analyze call recordings of sales interactions to improve conversion rates. You can monitor call center agent performance, identify customer sentiment, and track call center KPIs to boost retail customer service and support.
Benefits of AI voice analytics across industries
- Improve call center agent performance
- Improve customer satisfaction
- Reduce call center costs
- Monitor call center compliance
- Detect call center fraud