AI for Business: Using Voice Data for Better Team Performance

By Krish Ramineni

More and more businesses are shifting to a voice-first strategy as a response to the change in consumer behavior, among other things. There has been a significant uptick in the use of voice assistants in the last couple of years. Around 70% of consumers say they prefer to use voice assistants when making payments and interacting with customer service. 

Another reason for the shift is the wealth of rich information buried inside voice data—information that will improve your team’s performance and help strengthen your business’s bottom line.  

Artificial Intelligence (AI) does the time-consuming work of surfacing all that information. It provides business leaders and team members insights that will improve their capabilities, course correct actions, and enhance their decision-making processes. 

Voice Data Fluency Using AI 

Businesses that have digitized all their internal and external communications have a massive repository of knowledge waiting to be utilized. This could be financial meetings, customer service calls, and sales calls.  

It would take someone days to sort, clean, and make sense of a huge amount of unstructured and structured voice data. AI can analyze all those for far less time. It can search for patterns humans can overlook or have difficulty identifying, regardless of expertise. The result is valuable data without silos.  

With AI, being fluent in voice data has become much easier. Managers don’t need to be statistical analysis experts to glean insights from data. For instance, they can see how their teams are performing just by looking at a conversation intelligence’s dashboard, which can include AI voice notes that highlight key points and trends. They can see what’s working and what’s not.

Conversation Intelligence is a suite of AI-powered features. It assesses the sentiments of call participants, which members have the most conversations, who are talking the most, and how frequently competitors are mentioned in a call, among other things. 

Enhancing Intra-Organizational Team Efficiency 

The wisdom of the crowds tells us that many are better than one, that there is strength in numbers. This is possible if every person in a team is a superstar performer. And that is much harder than it appears to be, regardless of how big and successful the company is. In fact, according to a study, 82% of Fortune 500 executives are having difficulties recruiting such talents. 

Let’s look at this in a different way. What if you have a few superstar performers but dozens of high-potential employees? You already have a pool of up-and-coming top talents; they just need the proper guidance to reach that level. 

Voice Data using AI recruiting technology will provide that guidance. AI is a tool that augments human capabilities. It can turn mediocre to good and good to great. 

Here are a few applications for AI-enabled voice data: 

• In marketing, it can help teams better understand the voice of their customers, repurpose transcripts into rich SEO content, and generate quality leads with sentiment analysis.  This even applies to bigger projects like books with which an AI novel generator can help you out.  
• In sales, it can help managers coach their reps, log notes into CRMs, create action items, and streamline onboarding.  
• In recruiting, it can fill out application systems, train recruiters faster, and boost cross-team collaboration.  

Using Voice Data for Better Decision Making 

Most customer-centric companies will agree that listening to clients and understanding their needs and expectations are critical to improving and growing business. Conversation intelligence is a big part of the puzzle to turn this into a reality.  

Conversation intelligence ensures that every interaction with clients or potential clients is captured and analyzed to improve customer experience and, eventually, the bottom line. Without it, companies have to randomly analyze calls, leaving much room for speculation and guesswork.  

It provides personalized metrics and gives you the flexibility to benchmark, analyze, and explore improvement opportunities within a department. It x-rays all your conversations and makes them more actionable by identifying:  

• What works well and what doesn’t during critical interactions. 
• How much do your team members talk vs. listen during meetings? 
• How frequently does your prospect/client mention competitors? 
• The overall sentiment during conversations. 
• If your conversations tend to go off-topic.  

Conversation intelligence gives an instant overview of your team’s interactions to boost performance and accelerate coaching. 

Voicing Concerns and the Future 

Unlike traditional programming, AI and its subsets (e.g., Machine Learning and Natural Language Processing) is an advanced technology that improves as it is fed with more datasets. The models can predict better values through constant training. 

Handling data, regardless of volume, is a big responsibility. Privacy and security should be a key priority when it comes to this. Specific measures ensure end users’ protection, such as data encryption, GDPR certification, and SOC II Type 1 and Type 2 compliance. 

But beyond that, the company must genuinely be customer-centric. That means that every person in the company should empathize with the customers and be their advocate. Protecting customers is more of a human issue than a technology issue.  

AI can be beneficial to teams in more ways than one. Analyzing voice data is just one of them. This opportunity is vast and prevails across industries, from one-person start-ups to large enterprises. It is up to organizations to decide how they want to approach this technology and the opportunity it brings.

About the Author  

Krish Ramineni, CEO and co-founder of Fireflies.ai, an AI meeting assistant that helps transcribe, take notes, and complete actions during meetings.