Why Voice of the Customer?
Voice of the Customer (VoC) is the biggest buzzword in retail today. Everyone is laser-focused on understanding customer needs, expectations, and feedback on their products and services.
Fortune 500 companies have crumbled because they don't have a grasp on their VoC. On the flip side, the world's fastest-growing startups have IPOed at insane valuations by understanding VoC. Take Microsoft for example, who has invested heavily in their product suites (Dynamics, AI) to help their retail customers better understand VoC. It's come down to a simple decision - understand VoC or fade into the archives of history.
However, can we truly understand the Voice of the Customer without understanding the Voice of the Customer? Sounds redundant, but hear me out.
The volume of customer calls that retail experiences, vast with a richness of information, have in the past been a black hole for deriving insights. Marketing teams invest heavily in understanding the social sentiment of their brand. Yet, the one source that has the most possibility of customer insight with voice conversation, has remained untapped. The insights in voice conversations are a goldmine of powerful information that can change a company overnight.
Companies have tried and failed for decades to transcribe voice conversations into text to derive those insights. By losing sentiment and tonality, you lose out on the emotions of the customer. And how can you understand the Voice of the Customer without the emotion?
Case #1 "Yeah, your product works well" .
However, add some sarcasm...it is the complete opposite effect.
Case #2 "Damn, that's bad".
However, with some positive energy, it actually means a completely different effect.
Voice of the Customer with Observe.AI
At Observe.AI, we bring the Voice of the Customer to the Voice of the Customer. Our industry first contact center AI platform changes the game by analyzing combined audio and text to detect patterns in the tone of speakers.
We provide insights into the customer's words, sentiments, emotion, and silences to find out truly what the customer is thinking about you. With this information, you can build empower your contact center to better address your customers needs, coach your agents to improve customer experience, and project patterns for inventory control (and much more).
Let's dig into one specific feature around contact center insights. Here’s how it works:
Word Cloud and Hypothesis Building
Observe.AI empowers you to create word clouds based on themes that you want to explore. With these word clouds, you can create a hypothesis that can then be further tested on your Observe.AI dashboard.
Weekly and monthly trends in these word clouds can tell you how customer “talk” has changed over time.
Complex Query Building
You can also build queries to specifically look for a specific subset of all your calls.
For example, if you want to know “what are my customers from UK saying about product returns from 1st Feb to 15th Feb, when they have a negative sentiment during the call?”.=
Primary and Secondary Call Drivers
Observe.AI helps you identify the root cause for why customers are calling in. You can determine the primary reason for calls and then drill into the secondary reasons for such call.
Once you know the breakdown of call reasons, you can create more efficient processes to reduce such root causes.
About the Author: Pete Lee heads the partnerships and strategic alliances vertical at Observe.AI. He is a business graduate from Chicago Booth School of Business and has served in the US Navy. He has previously worked with several High-Tech companies in the Enterprise space.