Why Voice of Customer?
Voice of the customer or VoC is the biggest buzz word in retail. 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 of their VoC. On the flip side, fastest startups have IPOed at insane valuations by understanding VoC. The worlds largest company, Microsoft is investing heavily in their product sets(Dynamics, AI) to help their retail customers better understand VoC. 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 customers calls that retail experiences with its richness of information have been a black hole for insight. CMO spend a large amount of investments understanding the social sentiment. Yet, the one source that has the most possibility of customer insight with voice conversation is untapped. The insights into voice conversations produce a goldmine of powerful information that can change a company overnight.
Companies have tried for years with little success to transcribe voice into the text to get insight. However, by losing sentiment, tonality you lose out on the emotions of the customer. And how can you have 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 Customer with Observe.AI
At Observe.AI we bring the Voice of the Customer to the Voice of the Customer. Our industry first SpeechNLP AI Platform changes the game 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, you can project patterns for inventory control, and much more.
Observe.AI’s Analyze feature enables you to get insights from the huge number of customer interactions happening in your call center. Here’s how:
Word Cloud and Hypothesis building
Analyze helps you 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, monthly trends in these word clouds tell you how customer “talk” has changed over time.
Complex Query building
With Analyze, you can 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.