How to Extract Value from your Call Recordings

Unlike text-based communications, contact centers cannot analyze the content of voice calls quite so easily. The widely used practice of randomly selecting calls for review can be time-consuming and increasingly inadequate. To gain visibility over all communication channel recordings equally, it is crucial to level the playing field.

Speech-to-text transcription is the first step to unlocking the full potential of your call recordings. Converting audio to text allows contact centers to analyze voice calls with the same scrutiny as text. As part of speech-to-text transcription, Natural Language Processing (NLP) is applied to the audio. This enables technology to understand human language, isolate words and phrases, and distinguish meaning.

Transcription starts automatically on call completion, allowing contact centers to begin gaining insights quickly. This removes the need for random sampling, allowing you to utilize expensive human resources more effectively. As the technology develops, NLP could be applied throughout a call, for real-time analysis.

So your call recordings are transcribed. What now?

Some compliance regulations might affect just a small percentage of your overall call traffic. This creates a needle-in-a-haystack situation when trying to find specific interactions. You need a way to narrow down and categorize these transcripts into meaningful sub-sets.

Thanks to NLP, your contact center has the ability to break down human speech, and to group call recordings based on the words and phrases used in each call. Entire sentences, even topics and trends, can be targeted. This lets you group interactions, link them to specific campaigns or products, and detect the presence of required statements and scripts. With the right solution, you can view the degree to which agents adhered to scripts as a percentage, and produce a definitive list of calls for further investigation with a single click.

Automating this laborious identification and selection work allows compliance teams to locate the calls they need quickly and accurately. Furthermore, with the use of Intelligent Automation, instances of non-compliance are much less likely to go undetected, as 100% of interactions are analyzed.

Now you can filter calls into meaningful groups. Let’s go a step further.

Did you know that customers prefer to engage with an organization using the voice channel when it’s a high-importance issue? The emotions expressed in these calls by customers, and the way your agents deal with them, are an invaluable source of information. However, feelings are abstract concepts and highly subjective. How can your contact center uniformly identify and categorize emotion without doing so manually?

Sentiment analysis automatically identifies interactions that contain negative or positive key words and tones of voice, which indicate possible training requirements or need for further scrutiny. This allows you to better understand your customers, and eliminate the pain points in their experience.