What is Speech Analytics: Types, Uses and Benefits

Speech analytics is a relatively new technology that has become popular due to the enhanced usage of artificial intelligence. It significantly improves the productivity of call centers, provides company management with important insights for making management decisions, and minimizes the risks related to any violation of applicable regulations and laws. We will explain how it works in practice, what benefits you will get, and which brands successfully use this technology in their marketing strategy. 

What Is Speech Analytics

Speech analytics is the process of transcribing a person's voice, i.e., converting audio signals into text. It also involves highlighting important information such as keywords, emotionally colored statements, mentioning certain products or problems related to their use, etc. In some cases, speech analytics works in conjunction with voice analytics. The latter focuses on the tone of a sound to determine a person's mood and satisfaction with a service to predict the next steps. 

To understand what speech analytics is, you should also know that specialized software doesn't just fill databases. It also studies the information received, searches for hidden patterns and identifies trends. This makes it possible to generate valuable insights at different levels, including for line employees of call centers, team leaders and even top management. 

Types of Speech Analytics

Speech analytics systems fall into two categories:

• Information post-processing systems work with audio files stored in computer memory. These can be recordings of calls and conferences, voice messages in messengers, and answering machines. Such software is slower but gives more accurate results and analyzes information in more detail. For example, it can break a call into separate segments and compare it to the ideal conversation structure to point out mistakes to an employee and give recommendations on how to handle the next call. 
• Real-time services provide assistance to call center employees when they are on the line with a customer. They usually have limited functionality but allow you to avoid problems instead of dealing with consequences. Most often, AI-based speech analytics systems operate in real-time. They allow you to adjust the structure and tone of a conversation, warn managers about rule violations, automatically search for information in the database, and generate personalized commercial offers. 

How Does Speech Analytics Work

According to Grand View Research, AI-powered speech analytics is the trend of the current decade. Although it is still inferior to traditional algorithm-based software in terms of market share, the value of this segment is growing much faster. Experts of the consulting company predict that AI systems will take the lead in 2027-2028. Therefore, we will consider the principles of their operation:

1. Audio signal processing. Artificial intelligence uses natural language processing (NLP) to convert words into text. Machine learning technology allows you to identify patterns, search for connections, and fill in the blanks. It significantly improves the quality of transcription while processing voices with an accent or speech defects, as well as when there is extraneous noise and interference on the line. 

2. Filling the database. AI speech analytics identifies keywords in transcribed texts. This allows it to categorize materials by mentions of certain brand products, the area of responsibility of certain departments, the emotional nature of an appeal, and the quality of assistance provided. 

3. Analysis itself. At this stage, another AI-based solution, Big Data, comes into play. The software performs millions of calculations per second, searching for relationships between certain elements of the database. It checks all hypotheses — even the most impossible ones that an analyst would never consider. This makes it possible to identify hidden patterns, such as the dependence of speech tone on the first word in a dialog or the reliance of customer satisfaction on the number of words per minute of conversation. 

4. Generating insights. The main task of AI speech analytics is to provide management with information for making management decisions. The software can evaluate the KPIs of each individual call, workplace, department or product. It can also be configured to compare these indicators with industry standards or the performance of the closest competitors. 

Why Should You Use Speech Analytics

The main benefit of speech analytics is significant time savings. The human brain perceives text two times faster than sound. Even if each call is analyzed completely, this significantly reduces the workload of call center employees, analysts and managers. This technology has other benefits, which we will discuss in more detail. 

1. Increase customer satisfaction 

By highlighting keywords, you can instantly find the materials you need in the customer support knowledge base or even generate personalized offers right during a call. During post-analysis, this will allow you to achieve a higher level of customization to customer needs. The Connected Customer report shows that 79% of people want to be connected immediately to the most skilled expert on the subject, and 82% believe that they should have all the necessary materials at their fingertips. This is exactly what a speech analytics system can help you do. 

2. Increase call center productivity

In the case of WestJet, a voice bot trained on speech analytics materials solved 87% of customer problems, reducing the workload on employees by almost ten times. SQM Group's statistics also show that using such software reduces the number of repeat calls by 15%. This not only optimizes financial performance but also increases employee loyalty. According to the Orange Group, 69% of call center employees feel more attached to the company thanks to the benefits of speech analytics. 

3. Discover new marketing opportunities

By extracting keywords from a conversation and finding hidden interrelations, you can learn more about your customers' needs, preferences and desires. This allows you to launch a hyper-personalized campaign with individualized offers for each person. Opus Research studies show that the use of speech analytics features in marketing yields an average return on investment of 81%. 

Beyond hyper-personalization, speech analytics can help you revise and strengthen your overall marketing strategy. For example, an analysis of several dozen calls revealed that your customers respond most positively to specific characteristics of your product or company, completely different from those in your ad messages. In other words, customers appreciate the service's ease of use and round-the-clock support, and you emphasize discounts.

Thus, speech analytics have shown that you aren’t talking about what your audience really needs and, therefore, lose new customers and money. But implement changes gradually to test the waters. Get started using Claspo widgets on your website to deliver your updated marketing message.

In addition to describing your offer (key differentiators, etc.), they can encourage site visitors to take a targeted action (buy, learn more, subscribe, and so on). Our built-in analytics system will show you the number of clicks and the conversion rate of the widget, helping you understand whether your current message is resonating with your audience.

Try this template

After, run A/B testing of the widget and compare whether the hypothetical message "Achieve your goal in 1 day with our product" performs better than "Free support from our team until you get results." Once you identify the winning message that converts best, you can scale changes to your website, landing pages, and other communication channels.

4. Compliance with regulations and laws

Real-time analysis of dialogs prevents violations while minimizing risks: if an employee approaches a critical point, they will get a corresponding warning. Post-processing of conversations will help obtain materials for additional specialist training. According to Fortune Business Insights, 67% of companies that use speech analytics systems use the risk minimization function and see a significant workload reduction in their legal departments. 

Speech Analytics Use Cases

Speech analytics software is most often used in the following industries:

• IT - helps identify modules and individual product features that require the most attention. It helps to develop a customer-centered product policy, increasing user satisfaction.
• Fintech - research in the field of speech analytics shows that it can be used to improve both service and security. If dialog patterns of different calls differ drastically, it may be a sign of fraud.
• Retail - statistics show that 61% of consumers still prefer voice calls. On the business side, it's worth noting that voice leads have a 28% higher retention rate and significantly higher value for a company. This makes speech analytics systems very useful for retailers.
• Healthcare - the smallest mistakes in this area can lead to multimillion-dollar lawsuits. Businesses should know how to use speech analytics as an early warning system for possible violations. In this case, investments in artificial intelligence and new technologies can yield huge profits.
• SaaS - in the service and web services industry, prompt and efficient customer support is vital. Speech analytics allows you to solve problems faster and issue bonuses to compensate for inconveniences. 

Claspo widgets are a perfect intermediary between voice leads and your prompt and efficient support team. Use our call back templates that collect the phone numbers of site visitors (hello, lead generation) and transfer them to your CRM and CDP for further customer contact.

With our flexible display rules, you can set widgets to appear in the right place and time. For example, visitors who take too long to explore your pricing page probably need help. But why guess? Use speech analytics to identify the most common times customers express specific needs or frustrations.

Suppose customers often ask about your return policy. In that case, you can show a pop-up window with information about the return process when users have visited several website pages or spent a lot of time on the checkout or specialized information pages. Perhaps they may be unable to find the information they need to decide or complete a transaction.

Examples of Speech Analytics

According to Global Market Insights, in 2023, companies spent almost $2.5 billion on speech analytics systems. This figure has grown by 17% annually in the past and may accelerate to 20-25% in the future. So, here are the companies that managed to get the most out of AI-based speech analytics technology. 

Revenue Enterprises

This debt collection and loan restructuring company had problems with its call center performance. Due to high workloads and technology limitations, managers could analyze only a small share of calls — about 1/10. This reduced productivity, limited training opportunities and created a large number of legal risks. 

By implementing speech analytics best practices, managers were able to handle 100% of calls. In addition, time spent was cut in half compared to manual processing of 1/10 of calls. The company also created a full-fledged training department within the call center. In addition, it significantly reduced the number of complaints and lawsuits. 

Cdiscount

A French retailer serves millions of customers every day. The capacity of its call centers was barely enough to accept requests, let alone analyze them in any form. This created difficulties in developing effective marketing campaigns. 

The use of speech analytics made it possible to receive, analyze, and categorize 2 million calls and 200 thousand call hours per month. The company was able to launch about 75 thousand personalized offers. Overall, this increased customer satisfaction by 15%.

RoadVantage

This insurance company was experiencing excessive duration of calls, which reduced the overall productivity of the call center. Employees spent too much time identifying customer needs. In addition, they could not ensure consistent service quality and total compliance with legal regulations. 

In this example of using speech analytics, the average time spent communicating with customers was reduced by 14% while increasing customer satisfaction. In addition, the transition to a high-tech solution enabled management to make data-driven decisions, which improved the efficiency of using available resources in the long term. 

You can also reduce the workload on your customer service department by using chatbots. We discussed them in detail in a separate article. For example, you can trust a chatbot to communicate with customers in your messengers. And here, Claspo would also be appropriate. Our site widgets can show visitors all available channels through which they can contact you. Some will choose a call with your support team, while others will prefer to receive answers to their questions in text form. This variety will improve the customer experience and positively affect your results!

Conclusion

Speech analytics technology is the future of call centers and customer service in general. It significantly improves productivity, reduces time spent and increases customer satisfaction. Even more importantly, high-quality analytics allows you to monitor the quality of each call and ensure compliance with policies. Natural speech recognition systems can also provide company management with statistics and insights to help them make the right management decisions. And Claspo widgets will make it easy and quick for site visitors to reach your support team exactly when needed. After all, the more people interact with your support team, the more data you provide for speech analytics to get valuable insights, right?