Speech Analytics Call Center: Use Cases, features & More

How Speech Analytics is Shaping Call Centers

When people speak, their tone changes based on their mood and emotions. While a call center agent might miss these subtle shifts at the end of a long shift, you can use software trained to recognize them.

This is where call center speech analytics helps ensure that you don’t overlook any important signals reflecting customer satisfaction. 

In this blog post, we’ll see how speech analytics in call centers can ensure quality assurance and optimize customer interactions.

What is Speech Analytics in Call Centers?

Call center speech analytics is a technology that processes customer conversations using AI and converts unstructured voice data into actionable insights.

It can identify phrases, vocal attributes, tone, and sentiment, which can help analyze the nature of the call and its quality.

It’s different from call transcription, as speech analytics dig deeper into identifying patterns in customer attitude and guide customer service agents. 

How Does Call Center Speech Analytics Work?

Speech analytics utilizes deep technologies like machine learning (ML), natural language processing (NLP), and sophisticated algorithms. It’s trained on a large volume of conversations to interpret human language and identify the participant’s emotions and context. 

The speech analytics insights help agents personalize the conversation and react accordingly. The call center analytics tool can be used to evaluate call quality on both call recordings and live calls. 

→ Post-Call Analytics: Analyzes recorded calls to evaluate agent performance and quality assurance and identify areas of improving the customer service experience.

→ Real-time Analytics: Offers agents the right information during the call on customer’s mood, allowing them to be empathetic and agile in real-time.

Importance of Call Center Speech Analytics

In contact centers, empathetic conversations can help convert a detracting customer into an advocate. Speech analytics adds science to human interaction and can help you:

1. Improve Customer Satisfaction

An inbound customer call already indicates friction in the customer journey, and that’s where speech analytics can help identify the reason for repeated calls from customers.

For example, speech analytics can identify customer’s dissatisfaction with the IVR. This insight allows you to improve your IVR capability and offer other self-service options like chatbots. As a result, you increase customer satisfaction and prevent any escalations. 

2. Identify Areas of Weakness in Call Center Operations

You can use speech analytics to identify the factors impacting customer satisfaction and call center inefficiencies, such as operational and performance issues, including call volumes, call quality, and agent performance. 

For example, managers can personalize training for the agent by using speech analytics data, such as the agent’s overall performance metrics, such as call handling and customer satisfaction. 

3. Enhance Agent Performance

The agents and supervisors can use the data from speech analytics to identify areas of improvement and make informed decisions to improve performance. 

Moreover, real-time speech analytics insights can keep agents aware of customers’ emotional states so that they’re handled accordingly. This can help agents reduce stress and allow them to deliver consistent call center service during peak call times.

4. Offer Predictive Service

Using call center speech analytics tools, businesses can constantly monitor and track any factors causing spikes in call center activity. They can use the patterns and trends to resolve potential issues before they impact customer experience proactively. 

5. Ensure Regulatory Compliance

With more agents working remotely, call centers have put stringent regulatory requirements in place to ensure agents adhere to the scripts and do not breach customer privacy. 

Speech analytics provide real-time insights to ensure agents stay on track and flag anything that goes against regulatory compliance. The tool alerts agents on the use of certain words and prevents any unnecessary demands of information for legal compliance.

Use Cases of Speech Analytics in Call Centers

Let’s look at some ways call centers can use speech analytics to their full potential. 

1. Evaluate Customer Satisfaction

Surveys can help you gauge how well the call center is operating. For instance, a CES survey can reveal terms like “easy” or “frustrating” that customers may use to describe their experience.

You can also run NPS and CSAT surveys to identify trends and patterns in customers’ words and sentiments to prioritize actions.  

2. Monitor Agent Performance

Supervisors and managers can actively monitor a call center agent’s performance using speech analytics insights. It can automatically analyze conversations and create a standard evaluation process, highlighting the agent’s performance. 

3. Generate Quality Leads

For both outbound and inbound call centers, speech analytics can increase the chances of leveraging upsell and cross-sell opportunities. It can uncover patterns in customer behavior and preferences, enabling sales and marketing teams to design relevant strategies.

Call center agents can focus on what resonates with the potential customers to transform generic calls into personalized interactions that boost lead quality. 

Features to Look for in a Speech Analytics Software

If you’re considering a call center speech analytics platform, here are some key features to look for:  

Multilingual Conversation Analysis

The tool should work with multilingual conversations to explore diverse markets, ensuring personalized customer support and effective communication overcoming language barriers. 

Advanced Analytics 

Speech analytics tools should support advanced analytics, such as AI-driven tools, to process a large volume of data seamlessly. It should help analyze tone, sentiment, and patterns in customer conversations. 

Advanced analytics can help understand customer emotions and identify potential issues before they escalate so businesses can refine their customer service strategies. 

Additionally, a custom dashboard can offer a unified view of key metrics indicating customer sentiment and agent performance, allowing quick insights and early issue detection for better decision-making.

Regulatory Compliance

Regulatory compliance is a key feature you should double-check when considering speech analytics. The software should ensure that your contact center adheres to industry data privacy and regulation laws by monitoring and flagging conversations that may breach regulatory requirements. 

For industries like finance, healthcare, and telecommunications, where strict regulations are in place, this feature helps businesses avoid costly fines and legal ramifications.

Integration with Existing Stack

The speech analytics solution should work perfectly with your existing systems, including CRM, workforce management and other applications. 

The integration streamlines data flow, reduces manual data entry, improves accuracy in customer insights, and reduces disconnected customer conversations. 

Automated Quality Management

The tool should offer an automated quality management capability that reviews customer-agent conversations based on predefined criteria such as compliance, customer satisfaction, etc., thus enhancing productivity. It should also ensure that the workflow automatically adapts to any changes in procedures, syncing everything without manual effort. 

The feature helps maintain a consistent call quality across all customer interactions and drives continuous improvements in call center operations.

Exotel is an AI transformation platform that improves customer communication and engagement. It offers a complete cloud contact center solution that optimizes operations with automatic dialers, detailed call analytics, routing, and more. To learn more, book a demo today with our expert team.

How to Implement Speech Analytics in a Call Center? 

Once you’re ready to implement speech analytics in your call center, here are the further steps: 

⇒ Step 1: Identify Your Call Center Operation Goals

Before finalizing the speech analytics tool, it is important to define your goals and objectives. This will help you determine the areas that need focus and find a solution that offers suitable features. 

⇒ Step 2: Find the Right Solution

This is the most important step — evaluate vendors that offer solutions suitable for your business. Here, you can consider factors like scalability, ease of user, regulatory compliance, and compatibility with your existing stack.  

One good way is to create a checklist of features you need and shortlist the vendors. You can take a live demonstration from the vendors to assess the platforms.

Unlock the full potential of your customer interactions with Exotel. Leverage AI-powered scoring and analysis, multilingual conversation analysis, real-time monitoring, and advanced analytics to make informed decisions and enhance customer experience. Request a demo today and see Exotel in action.

⇒ Step 3: Define KPIs

Based on your business goals, identify the call center speech analytics metrics to monitor and analyze to evaluate agents’ performance. It may include average handle time, first call resolution, agent performance, call quality, or customer sentiment.

⇒ Step 4: Onboard Agents

For effective speech analytics, it’s important to train the agents to utilize its benefits. 

Provide comprehensive training that demonstrates the benefits of speech analytics in improving agent productivity and performance. Show them how it can empower them with meaningful insights and enhance their interactions in real time. 

⇒ Step 5: Refine Your Scripts

The best part about speech analytics is that it helps you identify where your call scripts need improvements and refine them to maintain and enhance call quality. 

For example, take out any phrases that contain sensitive words or questions that can negatively impact customer experience. 

⇒ Step 6: Extract Insights on Call Center Performance

Once you have implemented speech analytics, use the data to identify the improvements it has led to. Extract meaningful insights to uncover the strengths and weaknesses of call center operations. 

This will help you understand where your customers commonly face some frustration or if your agents need more training. The insights will allow you to refine your processes and improve call center performance. 

Key Takeaways: Speech Analytics in Call Center 

Speech analytics in call center operations revolutionizes customer service, making it more agile, data-driven, proactive, and personalized. With real-time assessment of customer interactions, agents can deliver value-adding experience on the go. 

The platform helps streamline operations, improve agent performance, increase customer satisfaction, and enhance customer service efficiency. 

Exotel offers a cloud-first infrastructure ensuring flexibility and scalability that helps businesses of all sizes achieve superior customer engagement. Book a demo to explore the extensive set of features Exotel offers. 

FAQs 

1. What is the Difference Between Speech Analytics and Text Analytics?

The main difference between speech analytics and text analytics lies in the type of data they process audio vs. text. 

Speech analytics processes spoken language by extracting insights from voice interactions like customer service calls. Text analytics converts written content such as emails, chat transcripts, or survey data into quantifiable insights. 

2. What are the Limitations of Call Center Speech Analytics?

The limitations of call center speech analytics may include inaccurate transcriptions and analysis due to regional accents and poor audio quality.