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Conversational Analytics: What is it? by Behavioral Signals

Conversational Analytics: What Is it?

By 2022, Gartner predicts that most companies will be valued on their information portfolios instead of their physical assets and earnings. Data is the new oil, and companies that can leverage that information and utilize it for actionable insights are significantly more successful. Nowhere is that more indicative than in conversational analytics – the process of capturing and analyzing voice data from routine conversations users have dozens of times per day.

Conversations happen everywhere. The phone calls we make to discuss bills or obtain support. The online meeting conference software we use to coordinate with clients. The apps like WhatsApp and Snapchat that we use with friends and family. While there are a huge number of text conversations via SMS, chat, and email every day – there are even more voice conversations. And increasingly, technology is able to capture and analyze the data from those conversations.

Voice Data is Plentiful – Companies Can Leverage This

In 2016, US and UK employees spent 163 billion minutes in conference calls, and on average 92% of all customer interactions happen over the phone. Combine that with astounding statistics like WhatsApp’s announcement of 100 million voice calls per day, and there is a treasure trove of voice data being created and passed around the globe every day.

While many of these conversations are private and many more happen in public, where recording might not be feasible due to technology or privacy restrictions, a significant number happen in situations that can be analyzed. This is already done using software that records our calls, for quality assurance purposes or for file keeping, and where data analysis doesn’t always mean actually ‘listening’ to what is being said. Emotion recognition, for example, captures the vocal cues of the conversation and disregards any of the actual ‘content’ of the conversation.

The benefit of this approach is it’s language agnostic and can be helpful where privacy is an issue, like in financial calls. Some of the insights that can be extracted are:

Emotional Charge. Metadata can be provided by analyzing the positive or negative emotional charge of a call.
Behavioral Prediction. Voice data can be used to predict user behaviour based on their intentions and actions within a call.
Post-Call Analysis. A summary of a customer service representative or salesperson’s performance after a call can provide objective feedback for future improvement.
Live Suggestions. A method used to help the rep, in real-time, during a call by offering coaching recommendations, but also providing her on-screen performance indicators, like talking speed, overlap or customer emotions like agitation. ‘Whisper agents’ are already being used by companies like Allstate to provide real-time suggestions.

When implemented safely and securely, conversational analytics allows customers to leverage the hugely valuable data already at their fingertips in millions of annual calls and conversations to better understand employees, customers, and potential target audiences. It can lead to better customer service, higher sales numbers, and key insights that drive the future of the company.

Additional Benefits of Conversational Analytics

Voice is more pervasive than ever before. We utilize dozens of apps every day to communicate with each other for work and personal reasons. More than 110 million people in the US alone use a voice user interface every month on their phone, tablet, computer, or through a dedicated voice assistant. Millions more will buy devices or appliances with integrated voice assistants in the next five years. On top of this, the technology to detect and analyze human voice is growing increasingly sophisticated. Not only are these systems able to capture and measure basic vocal attributes, the use of AI can help aggregate this information into specific KPIs that lead to behavioural prediction.

The result will be a change in how we live our lives. Whether it’s an always-listening mobile device, voice assistant or wearable, it’s possible to monitor conversations around the clock and use that data for a number of benefits. Humans don’t control their voices to the same extent as they do their words or their facial expressions. The result is that we are both less self-aware of our voices and how our speech can impact those around us, and there is more subtext to be drawn from voices in a conversation. It’s more sincere and in many cases a far better indicator of emotions and behavioural intent.

This can be beneficial in several ways including:

Professional Improvement. Those who want to do better at work can receive emotion and behaviour reports on their call performance and see where and why their mood may have shifted. They can, for example, become better salesmen by understanding their customers but also how they responded when ‘price’ was brought up.
Stress Management. An app can provide tips to help manage stress and fatigue when your voice indicates a spike in either.
Health Monitoring. Combined with other biometric data collected from wearables, conversational analytics can identify perceived stress, anxiety, or exhaustion in your voice and notify you if there is a concern.
Relationship and Empathy Support. You can gain a greater sense of self-awareness in how you speak to your significant other, or in the way you treat those around you.

Imagine an app that signals you when your emotional charge shifts to negative, even if you didn’t realize it. Imagine getting updates when your stress levels start to subtly increase, even before you feel it otherwise. This is the potential of conversational analytics. And these benefits are equally viable in business.

Pushback Against Call Recording and Analysis

People have been forthcoming in sharing their data. More than 80 million smartwatches are expected to ship by 2021 and Juniper Research estimates 8 billion voice assistant-enabled devices will be on the market by 2023. Location sharing, heart rate monitoring, and always-on listening devices have become the norm for many consumers, but there is still significant pushback on the idea of a specific entity listening to or analyzing our conversations.

Companies will need to be responsible and protect user data, anonymize it, and keep it safe, if they want to keep on having customers. Regulations will need to catch up and protect the user. Voice is another piece of data as is our location, our biometric data like our heartbeat, or our emails. Users need to know their rights and obligations while companies must follow regulations and security protocols, and above all respect what the user is entrusting them with.

Implemented correctly, conversational analytics will allow companies a greater sense of what works and what doesn’t in customer service and sales. It will help individuals live better lives and become more self-aware of their interactions with those around them. It can leverage data in a safe and secure way while opening up a treasure trove of data insights.