Call center voice analytics in context 

I used to see these on the t-shirts of some computer science graduates I knew in the 1990s. 

It read:

“I’d rather write programs to write programs than to write programs.” 

I used to wonder if this would ever become a possibility. That’s what intelligence has brought in. There is so much available data, and with the right tools, you can do wonders with that data. Now, the intelligence engines let me answer customer queries, send reminder messages, and make decisions automatically. 

When we talk about a call center, the available data is in the form of speech. Every call center generates gigabytes of data every day. 

What do we do with them? 

Managers and supervisors of a call center listen to only 2% of the recorded calls unless something unfavorable happens. Often, the unfavorable happenings are never reported. 

What happens to the remaining 98% of the recordings? 

They just sit on the storage servers and get listened to only when there are complaints. Then you identify what went wrong, but then the damage is already done. 

Call centers are leaving a lot of money on the table without an enterprise-grade voice analytics solution.

Assume that you have a voice analytics solution in place, then the scenario is completely different. 

You can rapidly analyze call recordings to identify compliance issues, misselling, and privacy issues – either warn the agent or escalate to a manager to take corrective action. 

This would ensure that your call center complies with regulations and helps you understand grey areas to improve your call center function’s overall productivity and happiness. 

Well, this sounds interesting. But how does a voice analytics solution work? 

How does a Voice Analytics solution work? 

Voice analytics solution uses audio from recorded calls and converts them into structured data for searching and analyzing. The tools also utilize other associated data, such as customer profile information or when the customer interaction occurred. A text transcript is also extracted from the call. 

Its features include advanced search and filtering, enterprise-grade speech recognition and transcription, contextual call playback data, tagging and commenting, transcript visualization, and full PCI redaction. 

The search works in a custom fashion. It includes a highly flexible search engine for quickly and easily finding and retrieving calls through a free-form combination of keywords, phrases, acoustic measures, filler words, and call metadata. 

How does voice analytics provide you with the insights that drive decision-making? 

Every customer call matters in a call center. It is very easy to miss half the conversation without a face-to-face interaction. 

Voice analytics, along with intelligence, not only monitors ‘what is said’ but also ‘how it is said.’ It takes into account both the language and behaviours of the callers. It can figure out the mood of the caller when they called in and if it changed during the call. 

Let us assume that you are generating Gigabytes of data every day. How do you figure out which calls to listen to? 

It is like finding a needle in a haystack. 

Voice analytics helps you pull out the right calls to monitor based on keywords, phrases, moods, sentiments, awkward pauses, foul language use, irritable tone, etc. Now, you would have those calls with these defined parameters, and you get to listen to them. This can help you predict outcomes and provide you with insights on how to better your customer experience.

Let me give you an example I experienced first-hand a few months ago. 

A few months ago, in the US, I subscribed to a new phone connection, and the telco’s call center agent told me that the phone would be automatically unlocked in two months. I specifically asked this question as to when it would be unlocked, as I keep traveling to India very often. I believed I could use the same phone if the provider unlocked it. 

But, after two months, I realized that it was not unlocked. So, when I inquired with the call center again, I was told that it would be unlocked only when all the dues were cleared. This was a surprise for me. So, I told them about my conversation with the agent before subscribing to their plan. 

They had no provision to unlock before all their dues were collected. It was a mistake committed by an agent, and now this has become a customer service/experience issue. 

What is the pressing need for voice analytics in the call center here? 

A call center solution having a voice analytics feature enables the agent to use the right data and monitor calls to pick anything out of the ordinary. A good voice analytics platform that searches the call metadata would have raised a red flag on this automatic unlocking conversation. After that, they could have called me and clarified it. They could have taken this up as a training need and ensured that the agent was empowered to handle such issues in the future.

Voice analytics – customer feedback use case

I have covered most use cases as a part of this article. The biggest use case would be the customer satisfaction surveys that you conduct. 

How do you receive customer feedback?

You receive customer feedback through emails, SMS, IVR key presses, and the like. Imagine doing that using a voice feedback system. 

With a voice feedback system, you can even ask for qualitative feedback, such as “What did you like about our service? Or What did you not like about our service?” The customers are likely to give their feedback in natural speech. 

The voice analytics system can run through this feedback and provide you with insights that would never have been possible otherwise. 

In summary, voice analytics will provide you with the insights that will allow you to provide the best possible customer experience.

People speak on an average of about 100 words per minute, and imagine the number of hours the agents are on call. You generate tons of data and can learn a great deal from them. 

Voice analytics makes it easy for you to derive insights from these conversations based on pre-defined keywords and phrases, besides flagging conversations that border on insufficient information and misselling.