Leverage NLP-based UniMRCP Integration To Power Modern Customer Experience

Clients can now implement state of the art speech recognition into their IVR solutions using Deepgram’s UniMRCP 

IVR technology is witnessing a tectonic shift toward becoming a full-blown virtually managed deep science technique for contact centers and customer support management platforms. And, it’s the customer preference that’s pushing IVR platforms to leverage more of AI ML and marketer’s behavioral marketing intelligence capabilities to solve Customer experience issues commonly linked to IVRs.

Business analysts around the world are riddled by these two questions:

1. How can their organizations increase marketing and sales efficiency using AI and Automation tools?
2. How quickly can their Customer Support teams and Contact Center Agents improve complaint resolution and continue to provide a high standard of support under challenging circumstances?

In a latest NLP related Martech product announcement, Deepgram has announced UniMRCP integration that will allow our customers to connect state of the art speech recognition with their existing Interactive Voice Response (IVR) solutions such as Genesys, Cisco, Avaya, and Nuance. The next-gen NLP platform would play an important role in further improving the customer experience management strategies across industries and departments.

Natural language processing or NLP, together with other AI-based machine learning and data science application, provide highly promising foundation for contact center agents and remote workforce operators who are inundated with a flurry of calls and inquiries that need immediate resolution.

NLP is clearly proving to be a game clincher for sales and customer service teams involved in one-on-one conversations. In the last six months, we have witnessed an avalanche of innovations and upgrades in Martech and sales technology platforms offering NLP and speech recognition capabilities with their standalone products and solutions.

Even before the pandemic, speech recognition capabilities were projected as the most readily acceptable technologies to improve Marketing performance via enhanced personalization and customer experience management.

Where is IVR Heading in Contact Centers?

COVID-19 has ushered a new era in automated self-service management of contact centers. Contact center agents, business analysts and users — everyone is reaping benefits of NLP-based IVR techniques that modernize the entire customer experience journeys and modernize the contact centers without jeopardizing marketing goals.

The shift toward self-service IVR models is not a seasonal change– rather, it’s brought about by the rampant growth in e-commerce businesses and B2B software industries taking a cue out of B2C contact center models.

In a highly commoditized economy, a thorough-bred NLP-based IVR can truly differentiate your product experience and customer service quality from the rest of the competition.

Don’t believe us?

Here’s what top Market Research firms state about IVRs.

A majority of customers drop out of shopping journeys or abandon interactions with contact centers due to poor IVR technology. According to Vonage, companies using IVR can lose up to $262 per customer every year due to faulty IVR interactions, prompting wrong options to customers and other pertinent ambiguities that call centers are incapable of handling on their own using an IVR.

Conversational IVRs are therefore very important in not just delivering contextual customer experiences over call or chat, but also in ensuring customers stick to your business.

According to Deepgram, the benefit of IVR is that “customers are able to use their voice to navigate the menu versus using a touch-tone, which requires customers to listen to an automated menu and press multiple numbers before being routed to the correct customer service agent.”

However, we need NLP and Speech recognition to work in tandem to solve the glaring holes in practical applications. IVR functions might sound great in theory, but not always in reality, because not all customer inquiries fit into a multiple-choice menu.

In most cases, especially in actions related to banking and credit card facilities, IVR experience

can easily turn from helpful to frustrating when the system struggles to accurately capture the reason customers are calling or the customer has to listen closely for the correct menu prompts instead of being able to simply state the reason for their call. A wrong press of the button on screen can put you back in the IVR loop, wasting time or resulting in a call-drop.

Deepgram NLP makes it simple.

In a world where customer experience can make or break your business, it’s critical that the call center experience is quick and intuitive.

Deepgram’s state-of-the-art speech recognition technology seamlessly fits into existing IVR solutions. This synergy helps Martech customers access the information they need faster and minimize frustration for first-time callers by ensuring that they are heard correctly the first time. Deepgram’s solution provides its customers with unparalleled accuracy (over 90%), taking into account keywords that are important to your customers and automatically adjusting to noise pollution, meaning that the customer is heard the first time, regardless of background noise.

What is Deepgram UniMRCP?

Media Resource Control Protocol or MRCP is an industry-standard data and communication protocol. It is commonly used for IVRs. UniMRCP is the open source cross-platform implementation of the MRCP client and server. Deepgram has built a futuristic UniMRCP offering which allows enterprises to accurately capture the reason customers are calling by automatically adjusting to your customer’s unique audio profile and by distinguishing between speakers and filtering out background noise.

This enables enterprises to address customer pain points from the start, providing customers with a more positive customer experience overall.

AI ML training models improve NLP and speech recognition models used in MRCP. Deepgram’s AI ML solution helps the IVRs to identify with unparalleled accuracy the keywords that are specific to your brand, and that matter most to your customers.

This further streamlines the customer call center experience, routing customer calls to the correct support person based on their needs. UniMRCP makes it possible for companies to build a custom IVR dialogue workflow, as you have reliable transcriptions to build NLU models and automation off of.

What’s next for IVR Ecosystem?

Deepgram powers the next generation of Conversational AI Marketing for effective customer experience management. These can be used in improving IVR and AI voice products, virtual customer assistants, Chatbots and agent productivity solutions.

It can also be used in improving remote workforce collaboration and sales intelligence reporting, particularly in B2B commerce.

Deepgram currently serves innovative contact center solutions such as Agara, Active.ai, Observe.ai, Tethr, and Sharpen, providing them accurate transcription and customer experience foundation.

“There could be hundreds of issues a customer is calling in about. Add to this complexity there is a distribution of words, specific to each of our customer’s brands,” said Arjun Maheswaran, CTO at Agara. “We couldn’t get these words right using Google, Amazon or Speechmatics, and are thrilled to finally reach our accuracy goal with Deepgram.”

To share your insights on Conversational AI and Martech for Contact Centers, please write to us at sghosh@martechseries.com