10 Best Speech Analytics Software for 2023

Often, it is said that data is the new oil.

But data without any analysis is just like crude oil. It has a lot of potential but only if someone refines it through the process called data analytics. 

In the past two decades, the field of data analytics has hugely evolved but one important channel of data was always left aside i.e. Speech.

Speech analytics software has just come to the forefront in the past 5 years.

Simply put, it is a process of driving insights from the speech data generated by a business. 

A well-established organization would generate terabytes of data in the form of speech regularly. This data would be generated for:

1. Demand generation
2. Sales
3. Customer support
4. Recruitment
5. Internal team calls
6. Customer success
7. Market research and so on.

Speech data is super-rich when compared to text data. It not only provides you with customer insights but also helps you understand your internal processes.

Speech analytics is the process of converting your data into meaningful insights by first converting it into text and then driving insights on this content.

A. What is speech analytics?

Speech Analytics is the technique of analyzing recorded calls or live conversations in order to extract useful insights and information. 

This can be done through a variety of techniques, including keyword spotting, sentiment analysis, and conversation analysis. 

Speech Analytics is usually used in customer support or contact centres to enhance the customer experience, provide quality service, identify areas of improvement and improve CSAT and NPS score.

It is also used in a variety of other industries, such as finance, banking, healthcare, and retail.

Speech analytics software uses natural language processing (NLP) and machine learning algorithms to analyze spoken language data.

The software is trained to recognize specific keywords, patterns, and conversations based on tone and sentiment.

B. Why is speech analytics important?

Speech is one of the most important pillars of today’s business.

Voice conversations not just convey the content but also give insights about the context of conversations like emotions, sentiments, tonality, etc.  A business can use speech analytics for the following use cases:

1. Training and coaching of agents

Speech analytics can provide you with insights about pitching issues with various agents.

It can help you identify the top agents as well as bottom rung who would need hand-holding to become a top rung agent.

By giving you insights on what an agent is speaking or missing, quality teams can plan the training which can further be customized for each agent

2. Compliance and legal matters

Industries like finance, banking, healthcare, etc are very stringent about personal information and legal compliances.

Speech analytics can help you identify any untoward incidents in this domain thereby saving huge compliance litigations at a later point in time.

By analyzing recorded interactions, the call center can identify instances where agents may be deviating from established guidelines and take corrective action.

3. Customer insights and sentiments

While chats and emails provide you a sneak peek into customers’ conversations, they don’t tell you anything about customer sentiment.

Speech analytics not only tell you about customers’ conversations but also tells you about the sentiments of the customer thereby making your analysis richer

4. Competition analysis

Speech analytics can help you identify information about your competitor that your agent might not report every time they get on a call.

5. Sales training and improvements

By analyzing your sales calls, speech analytics can help you identify what is working and what doesn’t work. This can help you fine-tune your sales pitch thereby increasing your topline.

6. Process improvements

It is very important to keep on improving your processes, knowledge repositories, and other databases. Once a process is set, companies don’t go back to their drawing boards to reset it.

But with speech analytics, you can get the nudges for modification of your existing process thereby helping you improve your company’s efficiency and outcomes.

7. Enhanced reporting and analytics

Speech analytic provides detailed insights into customer interactions, including sentiment, tone, and common themes.

This is used to generate reports and analytics that helps in tracking agent’s performance.

8.Increased efficiency

Speech analytics can help identify trends and patterns in customer interactions, which can be used to streamline processes and improve efficiency. 

For example, if a large number of customers are calling with the same question, the contact center can use this information to develop a more efficient process for addressing that issue.

9. Improved customer service

By analyzing customer interactions, speech analytics can help identify areas for improvement in the customer experience.

This can include identifying common customer questions or issues, and providing solutions to improve the overall quality of service.

C. 5 use cases for speech analytics software

1. Customer service

 Analyze customer calls to identify trends and patterns in customer feedback, complaints, and questions.

Speech Analytics help organizations improve the customer experience and identify areas for improvement in their products or services.

2. Market research

Speech analytics can be used to analyze focus group discussions or customer interviews in order to extract insights and understand customer preferences and attitudes.

3. Fraud detection

Voice patterns and speech recognition are the two main elements of voice analytics in order to examine the fraudulent activities.

4. Sentiment analysis

Speech analytics analyses spoken language in order to determine the sentiment or emotional state of the speaker. This can be useful for understanding customer sentiment towards a company or product.

5. Language translation

Speech analytics  automatically transcribe spoken language into written text, which can then be translated into other languages.

B. 10 best speech analytics solutions to consider for your business

There are many speech analytics vendors available in the market. We are listing the top 10 players as per our analysis.

1. Enthu.AI

Enthu.AI is one of the top speech analytics tools available in the market.

Enthu.AI captures 100% of your voice calls, transcribes them and brings out meaningful analysis from those transcriptions. 

It is specially designed for contact centers and provides insights on important call moments, agent performance, coaching opportunities, and customer insights.

With a free pilot available and no binding annual agreements, it is one of the most flexible options available in the market.

2. Verint

Verint is an enterprise software providing business intelligence tools to its customers.

It happens to also do speech analytics apart from workforce management, fraud and security compliances, interaction insights, etc.

Verint’s speech analytics helps in call transcription but doesn’t support coaching and training use cases explicitly.

3. Callminer

Callminer is one of the earliest players in the market. They have been serving industries like healthcare, insurance, BPO, technology, etc. They provide sentiment analysis and agent-based scorecards to provide meaningful insights from speech data.

Callminer is suitable for enterprise clients and has a great customer support.

4.  Voicebase

Voicebase positions itself as a multichannel voice analytics tool. With the capability of connecting any source of customer data to extract insights, voicebase helps you uncover hidden data.

Voicebase also enables you to connect to various BI tools, data warehousing tools. Priced at $250 per month, this is on the costlier side and is more suitable for enterprise customers.

5. Observe.AI

Observe helps contact centres get meaningful insights from their calling data.

The software captures 100% of the calls and drives insights on customer response, coaching opportunities, and compliance needs.

You can coach teams with targeted coaching and know what training programs drive change and replicate what top supervisors and trainers do best.

6. Tethr

Tethr uses machine learning to convert voice into text and then run deep analysis on it based on the use case.

The software provides you analysis on sales and customer support calls providing your insights about the health of your leads, customer sentiments, and customer pain points. 

It has helped businesses decrease their churn rates, increase efficiency and build better customer experiences.

7. Gong

Gong is the pioneer in the speech analytics space when it comes to revenue intelligence and sales training. 

Gong has helped large and small teams drive real time insights on customer sentiments, lead health and possible pitching opportunities to increase the conversion. 

Gong is priced higher than other tools and is beneficial for enterprise customers.

8. Chorus

Chorus is another player in the segment of voice analytics software. It is owned by Zoominfo and focuses on sales intelligence use cases.

It has powerful AI algos which convert voice to text and then analyse them for better sales outcomes. It provides analysis on deal opportunities, performance of sales agents and possible coaching opportunities. 

It integrated with VOIPs and VC tools to capture your calls and input them into various CRM solutions.

9. Salesken

Salesken converts your sales calls into real time text, provides you sales cues and helps you navigate through the entire sales pitch to make every pitch a winning one.

10.Wingman

Wingman has just come up with a mobile app which makes it different from other tools mentioned above. With the use case of revenue intelligence, wingman provides real time battle cards, cues and nudges to better the sales calls.

Wingman prides itself in providing in depth speech transcription with deeper insights on sales status of your business.

C. How to find the right voice analytics software for your needs

We have previously written about how to evaluate speech analytics software.

Once you are clear about the use case and focus area, you should keep the following points in mind while choosing the right tool for you:

• Speech to text accuracy
• Integrations with existing software
• Onboarding and ongoing support
• Availability of feature set
• Options for free/discounted pilots
• One time and recurring pricing
• Contractual commitments

 Conclusion 

With technology in the space of speech analytics evolving each passing day, the industry is growing at a whopping 20.5% CAGR. It is estimated to grow to a $4.5B market by 2026.

Speech analytics will become table stakes for businesses engaged in customer engagement, sales, and the contact center industry.

As the technology evolves, we would see a huge surge in speech analytics software,speech-to-text transcription, expansion to various languages, and insights in qualitative aspects of the calls like the tone of the customer, emotions, etc.

Companies would further build predictive analytics stacks on top of available data, thus bringing insights and predictability to the businesses.

We are looking for exciting times for the industry and strive to be a pioneer player in shaping up this space.

FAQs

1. What are the benefits of speech analytics?

Speech analytics is the process of analysing spoken language in order to extract and understand useful information.

Top benefits are: Improved customer service, enhanced insights, improved compliance and increased efficiency and productivity.

2. What is speech analytics software?

Speech analytics software  uses NLP and ML algorithms to analyse and interpret spoken language in order to extract and understand useful information.

This software is typically used in customer service, sales, and marketing, and can help organisations improve customer service.

3. How to do speech analytics?

1. Collecting and storing spoken language data
2. Transcribing the spoken language data
3. Analysing the transcribed data
4. Extracting insights and actionable information
5. Implementing changes and monitoring results

Tushar jain

Tushar Jain is the CEO and Founder of Enthu.ai. In this free time he loves to read books.