According to Statista, 37% of customers prefer to interact with brands over the phone, followed by 19% of customers preferring chat and 15% wanting to email.
The phone is still the primary point of interaction for many customers and proves to be a valuable channel for gathering customer data.
By collecting this type of data, organizations can analyze and transform them into actionable insights with many use cases.
The most common technology used in customer phone calls is speech recognition and speech analysis. What can be done to take customer engagement to a higher level, leveraging every ounce of the interaction?
Symbl.ai CEO and Co-Founder Surbhi Rathore explains how conversation intelligence adds a new valuable layer to customer data and helps deliver meaningful experiences.
Maximize the Potential of Conversation Data
The phone is the tried-and-tested communication channel which works when nothing else does. Yet, interactions over digital channels are becoming more popular with younger, more tech-savvy age groups.
A Twilio report revealed that 96% of organizations believe not digitizing customer engagement would have negatively impacted their business. With the pace of digital transformation of many companies skyrocketing in the last few years, taking customer engagement seriously has become imperative for a great customer experience.
Rathore thinks there are a lot of opportunities for maximizing digital content and increasing customer retention. She says:
“Maximizing the potential of conversation data is the ability to convert that data to analytics, actions and knowledge, in real-time.
“This maximization of data is not just about speech recognition. Still, it is a critical part of the equation, and we do need it. However, if you’re not using it correctly and not deriving actions, coaching, and compliance from it, you’re really missing out on revenue growth.”
Conversation intelligence is the secret weapon that takes speech recognition to the next level, and much more. The use cases for conversation intelligence are multi-fold, from customer service and education, to telehealth, gaming, and meetings.
“In most of these use cases, customer engagement plays a big part in customer experience therefore maximizing that touch point data becomes a very critical factor”, adds Rathore.
Finding Value
Before employing any conversation intelligence, organizations must first ensure that they have access to conversation data, whether audio, video or text conversations. Rathore explains this further:
“If your product is making users go to Zoom or Google Meet, or any other similar meeting platform to do meetings, and then they come back to execute the rest of the workflows, can you actually have access to those recorded files?
“It’s important to have the data continuity across all customer touchpoints and that it does not get interrupted.”
Having the complete life cycle of interaction and data enables agents to seamlessly switch between platforms without losing any valuable information from the customer.
Conversation intelligence connects the dots between post-interaction data, data that is being stored in real-time, and predictive data. Starting from the most basic post-interaction data such as transcription and live-captioning, Rathore says:
“The most-low hanging fruit that you can embed in your platform is creating an accessible user experience for your customers, using live captioning or real-time transcription.
That enables you to both start capturing the data from the conversation itself and help people catch up to the conversation and build an inclusive experience. For example, this is essential for webinar platforms, considering that we are always multitasking.”
The next step would be the option to search, index and filter content for better distribution and knowledge creation. This allows for easier topic search, along with recommendations based on search history.
Rathore also mentions content moderation as one of the essential components of conversation intelligence:
“It is also important to allow customers to moderate, redact, comply and detect profanity in content. Its hugely helpful in order to ensure we remove the biases or we remove the bad information from passing through.”
Finally, workflow automation helps users predict future engagement and improve the outcome of interactions, fueling customer satisfaction and growth.
Symbl.ai transforms customer experiences with conversation analytics and intelligence at scale. Find out how you can leverage their solutions to boost customer satisfaction: https://symbl.ai/
