The Voice of the Customer (VOC) is one of the most obvious, yet underutilized tools organizations have at their disposal to create outstanding customer experiences, increase customer loyalty and retention, and boost profits.
As an element of customer experience, the Voice of the Customer focuses on what customers want, need, expect, and prefer. It represents:
What a customer is saying (direct input collected through customer surveys, polls, monitoring of social media channels, product reviews, customer feedback, and most importantly the voice data generated in your contact center), and
How they feel/behave (indirect input collected through heatmaps on websites and other diagnostic tools to identify friction and acceleration points, e.g., rage clicking, monetary transactions, product usage, market research, and more).
VOC Is Crucial In Creating Great Customer Experiences Across The Entire Customer Lifecycle
Most companies already gather direct and indirect customer input data, but for the most part, this happens sporadically as a point solution. For example, the online marketing team analyzes website traffic and visitor behavior while the direct marketing team might aggregate survey data, but the two rarely meet and almost never get triangulated with contact center data.
The problem with this is that your customers view any interaction with your company as a single interaction, whether they are abandoning a cart on your website, calling the contact center to get answers to concerns or issues they might have, opening a product shipment they just received, or turning to the chat to request a refund.
The Voice of the Customer is that red string that connects them all, and organizations who utilize as many data points to create actionable customer insights will have an enormous competitive advantage.
Humanizing The Voice Of The Customer In Your Contact Center's Voice Data
Your contact center probably has hundreds, if not thousands, of conversations with your customers every day. They are telling you not only what they want, need, and expect from you, but also how they feel about their experience of interacting or doing business with your organization.
However, until now, that data was inaccessible. Sure, you could provide customer satisfaction surveys at the end of each call or survey your call center agents, but it has been incredibly difficult to get a complete picture of what is going on.
Thanks to Voice Recognition and Voice-to-Text Transcription we can now transcribe all recorded calls and then let Artificial Intelligence and Machine Learning extract important keywords and phrases.
Now, all of a sudden, we can quantify, measure, and analyze what is being said. Not only can we now see how many calls are about a broken product or requesting a refund, but we can also understand the behavior and emotions around these interactions. We can categorize calls into topics and dive deeper into what drives or what stalls success.
Analyze Customer's Emotions Over Rational Thoughts
Until now, companies had to rely on analyzing the "What" using big data analysis rather than the "Why" of traditionally unquantifiable emotions. But with customer sentiment analysis achieved through Artificial Intelligence-based text analytics, we can now overlay crucial insights as to what drives a certain behavior rather than just the outcome.