SPEECH ANALYTICS: What Is It and How Does It Work?

Table of Contents Hide

What Is Speech Analytics?
1. Types of Speech Analytics
How Does Speech Analytics Work?
Which Businesses Can Benefit from Using Speech Analytics?
Speech Analytics Software
Speech Analytics and Its Difficulties
Why Is Speech Analytics Important?
What Is Speech Analytics Used For?
What Are the Features of Speech Analytics?
What Skills Do You Need for Speech Analytics?
What Is the Difference between Voice and Speech Analytics?
How Do You Collect Speech Data?
How Do I Do Speech Analytics?
Final Thoughts
Related Articles
References

The term “Speech Analytics” refers to the practice of gleaning useful information from recordings of spoken words and phrases. The software used for speech analytics may transcribe data from conversations held in a wide variety of languages and dialects. Nexidia and Verint are examples of the speech analytics you can go for. Read on to learn more about Speech Analytics and how it works.

Let’s dig in!

What Is Speech Analytics?

Speech analytics is a method for deciphering and gleaning information from audio recordings or real-time talks. Several methods exist for this, such as keyword analysis, sentiment analysis, and conversation analysis. Speech analytics is commonly used in call centers and other customer service environments to better understand customer needs, deliver more personalized service, pinpoint problem areas, and boost CSAT and NPS ratings. It is also widely employed in the financial, healthcare, and retail sectors.

With a combination of natural language processing (NLP) and machine learning techniques, speech analytics software delves deep into recordings of human conversations. The software has also been taught to spot certain words, phrases, patterns, and conversations based on tone and mood.

Types of Speech Analytics

Speech analytics can be divided into two categories: real-time and historical.

#1. Real-Time Speech Analytics

Customer calls are examined for speech patterns in real time using speech analytics software. This provides agents with real-time access to insights, trends, and analytics that may be used to enhance the quality of their current conversations with customers. While a call is being taken, real-time analytics can disclose insights on client sentiment, tone, and trends, and even provide operators with suggestions for improving the customer experience.

#2. Post-call Speech Analytics

The information gained via post-call speech analytics pertains to a call after it has concluded. Discovering conversational keywords and developing individualized text categorization models are only two examples of how this information might inform the development of future approaches to customer service.

How Does Speech Analytics Work?

When it comes to analyzing human speech, nothing beats the combination of cutting-edge AI, NLP, ML, and algorithms that make up speech analytics. This type of speech recognition is able to catch up on consumer mood by assigning an emotional tone to customer comments and spotting patterns in calls.

With the use of speech analytics tools, you can also hear the customer’s actual words, allowing you to better comprehend their wants and needs. Knowing how customers feel allows you to make decisions based on actual data as opposed to assumptions about how they feel. Improve customer connections and agent efficiency with data-driven insights from an examination of what real consumers are saying about your business.

Which Businesses Can Benefit from Using Speech Analytics?

Speech analytics is especially useful in highly regulated sectors like healthcare and finance, where storing and searching client data must adhere to strict regulations. They also have an urgent need for early warning signs of compliance issues, and calls from concerned customers can serve as an indicator.

Speech Analytics Software

The following are some of the types of Speech Analytics you can opt for:

#1. Callminer

Callminer was an early industry player. They’ve also been providing their services to a wide variety of sectors, including healthcare, insurance, business process outsourcing (BPO), technology, and more. To help extract meaning from speech data, they offer sentiment analysis and agent-based scorecards. Callminer is good for business customers and has great customer service.

#2. Voicebase

Voicebase markets itself as an all-channel voice analytics platform. Also, it may connect to any data source about your customers and pull out useful information. It also provides integration with a wide range of business intelligence and data warehousing solutions.

#3. Observe.AI

Observe is useful for call centers since it allows them to extract useful information from call logs. The software also records every call and provides insights into customer satisfaction, areas for improvement in coaching, and regulatory requirements. You may emulate the finest practices of the most effective managers and educators by coaching teams through focused coaching and training programs that promote lasting change.

#4. Tethr

Tethr uses machine learning to transcribe spoken words into text, which is subsequently subjected to in-depth analysis tailored to the specific task at hand. The software also evaluates your sales and support conversations to give you information about your prospects, customers’ attitudes and problems. It has improved efficiency, lowered churn rates, and enhanced customer service.

#5. NICE Nexidia Speech Analytics

The sophisticated speech analytics included in NICE Nexidia help businesses learn invaluable lessons from their customers’ interactions. Algorithms powered by artificial intelligence also allows it to sift through mountains of audio data and draw useful conclusions for organizations.

#6. Verint Speech Analytics

The speech analytics platform from Verint makes it easier to examine client interactions in search of patterns and new ways to enhance the customer service provided. The superior analytics features of the platform also reveal interesting facts about consumers’ habits and preferences.

#7. Genesys

Genesys’ suite of customer experience solutions includes contact center-specific speech analytics technologies. The software analyzes both speech and text interactions to better help marketers understand customer preferences and opinions.

#8. Avaya

Call center agents can use Avaya’s conversational intelligence platform to listen in on and analyze client conversations for patterns and trends. It records and translates talks, highlighting the feelings of both customers and service reps.

#9. Talkdesk

Talkdesk Interaction Analytics is a speech and text analytics platform driven by artificial intelligence that helps call center workers learn more about their customers by identifying key dialog moments, subjects, intents, and feelings.

#10. Convin

Convin is an omnichannel contact center conversation intelligence platform powered by artificial intelligence.

#11. Five9

Using Five9’s contact center analytics software, businesses may examine their customers’ voices and digital interactions to learn more about their customers’ experiences and how their agents are doing.

#12. Gong

When it comes to revenue analysis and sales education, Gong is the undisputed leader in the speech analytics field. Small and large teams have both benefited from Gong’s real-time insights about customer sentiment, lead health, and potential pitching opportunities to boost conversions. Gong is more expensive than competing products, but it’s worth it for business users.

#13. Wingman

The Wingman mobile app is what truly sets it apart from the aforementioned alternatives. For the purpose of increasing sales, Wingman gives real-time battle cards, cues, and nudges. Wingman is pleased to offer comprehensive speech transcription that includes additional details about the health of your company’s sales.

Read Also: TOP 11 BEST DATA ANALYTICS COMPANIES 2023 ( Reviewed)

How to Find the Right Voice Analytics Software for Your Needs

When selecting the appropriate tool, the following considerations should be made after the use case and area of emphasis have been established:

High-quality speech recognition
Adaptations to preexisting programs
Initiation and maintenance of service
Access to a Full Set of Features
Access to reduced or free test flights
Explicit and implicit pricing structures
Legally binding agreements

Speech Analytics Software: What to Look Out For

The speech analytics software you use must be able to rapidly identify complicated concepts from massive data sets. If you want to get the most out of your speech analytics, you should also use speech analysis software with the right set of capabilities.

#1. Evaluation of call centers as the norm

Supervisors should also be able to analyze and keep tabs on each agent’s performance with the use of your speech analytics software. The accuracy, bias, and compliance can all be improved by analyzing all of the data from the agents’ calls instead of just a random sample.

#2. The field of analytics includes speech analytics as one component

Advanced analytics technology will be able to analyze both text and speech. By consolidating all of your customer service data onto a single platform, you can see how your brand is being seen and how your customers are feeling about their interactions with you.

#3. Transforming complex information into enhanced user experiences

Providing experiences for customers that not only meet but also surpass their expectations is the backbone of any successful business strategy. You may enhance the interactions and experiences your consumers have with your brand by using a platform that gives you insight into the customer experience and what your customers are saying in phone calls.

Furthermore, the information provided by your tool on the state of your data is insufficient. You need actionable insights from your speech analysis to boost operational efficiency, decrease customer attrition, and lessen the frequency with which your firm is contacted about the same issues.

Scenarios When Speech Analytics Software Would Be Useful

The following are instances where it can be useful:

#1. Customer Service

Examine call logs to see if there are any repeating themes in customers’ comments, concerns, or inquiries. With the use of Speech Analytics, businesses may enhance their products and services and provide a better overall consumer experience.

#2. Market Analysis

Customers’ preferences and sentiments can be gleaned from interviews and focus group conversations by employing speech analytics.

#3. Spotting Fraud

Voice analytics mostly uses speech recognition and voice pattern analysis to investigate potential instances of fraud.

#4. Sentiment Analysis

To ascertain the speaker’s mood or attitude, speech analytics examines their words. Knowing how customers feel about a business or its offerings can be aided by this information.

#5. Interlingual Communication

With the help of speech analytics, spoken words can be converted into written text and subsequently translated into other languages.

Speech Analytics and Its Difficulties

Although advancements in AI have greatly improved speech analytics platforms’ capacity to comprehend spoken language, significant obstacles persist. Accents, dialects, background noise, speech impairments, and varied speech rates are only some of the obstacles that make it hard to accurately transform spoken words into writing. Incorrect analytical findings may stem from misunderstandings. Unfortunately, not all speech analytics algorithms can comprehend linguistic nuance. Furthermore, characteristics such as sarcasm, irony, metaphorical idioms, and cultural nuances can make it very difficult to comprehend spoken language.

Another difficulty is figuring out how to incorporate speech analytics platforms into preexisting call center infrastructure without disrupting data flow or requiring costly upgrades. Many companies may not be able to afford the necessary technology, software, and training to do this.

Why Is Speech Analytics Important?

Communication is a cornerstone of modern business. Conversations over the phone express more than simply the words being said; they also provide information about the speakers’ intentions, feelings, and tone of voice. The following are some examples of how speech analytics might benefit a company:

#1. Respond to Consumer Inquiries

By analyzing conversations as a whole, speech analytics can reveal crucial insights and spot trends that might otherwise remain hidden in isolated phone calls. With the correct speech analytics technology, organizations may learn how they can better serve their employees and customers.

#2. Boost the Efficiency of Your Call Center

Although you may have some control over your contact center personnel, it is impractical to listen to every call recording in order to ensure high quality. Reviewing only a small percentage of calls can obscure deeper trends in the contact center that have an effect on efficiency and customer satisfaction.

With the use of speech analytics software, which automatically scores all calls for compliance, KPIs, and performance, it is much simpler to evaluate the efficiency of each agent. Speech analytics software can automatically grade agents and consumers by transcribing their conversations using automated speech recognition (ASR) technology. You can use the results of this research to enhance your call quality, and your agents will receive a more objective evaluation of their work.

#3. Competition Analysis

Using speech analytics, you can learn details about the competition that your agents may not always volunteer.

#4. Salesmanship Development and Instruction

Speech analytics may tell you what’s working and what’s not by monitoring your sales calls. You may use this information to hone your sales pitch and boost your revenue as a result.

#5. Enhancements to the Process

Improving your procedures, knowledge bases, and other data stores is crucial. Once a procedure has been established, it is rarely revised. But by using speech analytics, you can acquire the prompts for adjusting your current procedure, which will boost your business’s productivity and results.

#6. Better Analytics and Reports

Sentiment, tone, and recurring themes in client encounters can all be gleaned via speech analysis. It’s utilized to compile data for analytics and reporting on rep efficiency.

#7. Better Productivity

Using speech analytics, businesses can better understand client contact patterns and adapt their operations accordingly. If many consumers are coming in with the same inquiry, for instance, that data could be used by the contact center to streamline how they handle that inquiry.

#8. Better Service to Customers

Speech analytics can be used to enhance the customer service experience by evaluating client conversations. One way to do this is to find solutions to the most frequently asked questions or problems experienced by customers.

#9. Agent Instruction and Guidance

You can learn a lot about pitching problems with different agencies by using speech analytics. You can also use it to find the best agents and the ones who need the most help rising to the top. Quality teams may organize the training, which can be further tailored to each agent based on insights into what an agent is saying or missing.

#10. Issues of Regulation and Law

When it comes to protecting client data and adhering to regulations, industries like banking, healthcare, and finance are quite strict. Also, using speech analytics to detect inappropriate behavior in this area helps save costly compliance lawsuits down the road. The call center can analyze recordings of interactions to find cases where agents deviate from policies and train them accordingly.

#11. The Thoughts and Opinions of Customers

Emails and chats provide you with insight into what customers are saying, but they don’t reveal how they feel. With speech analytics, you may get a deeper understanding of your clients’ discussions by learning not just what they said but also how they felt throughout those talks.

What Is Speech Analytics Used For?

Interaction analytics, or speech analytics, is a technology that uses AI to decode, process, and analyze human conversation. Speech analytics are also used by contact centers to evaluate digital channel (chat, text, etc.) call records and transcripts.

What Are the Features of Speech Analytics?

In order to process and analyze human voice, speech analytics employs a wide range of cutting-edge AI technologies, such as automatic speech recognition (ASR), natural language processing (NLP), machine learning (ML), transcription (transcription), tonality-based sentiment analysis (TBSA), and algorithms.

What Skills Do You Need for Speech Analytics?

If you want to make a profession out of speech analytics, you’ll need to be able to think critically and communicate well. You need to have solid data analysis and pattern recognition skills. You also need to be able to explain your findings to others.

What Is the Difference between Voice and Speech Analytics?

Voice analytics looks at how something was said, while speech analytics looks at what was said. Tone, pitch, stress, speed, and rhythm are just a few of the aspects of sound that voice analytics software examines.

How Do You Collect Speech Data?

It is common practice for speech therapists to keep score using tick marks. A plus or minus sign indicates if the youngster accomplished the desired goal after being given verbal, visual, or tactile prompts.

How Do I Do Speech Analytics?

Collecting and storing spoken language data
Transcribing the spoken language data
Analysing the transcribed data
Extracting insights and actionable information
Implementing changes and monitoring results

Final Thoughts

Businesses can gain a deeper understanding of their customers’ interactions, sentiments, and emotions with the use of speech analytics software. These platforms use artificial intelligence and natural language processing to equip service workers with the knowledge they need to more effectively interact with consumers, swiftly address their concerns, and leave them feeling emotionally fulfilled. We do hope this article was helpful.