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Role of voice technology in reducing consumer stress
Role of voice technology in reducing consumer stress

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One question posed by the pandemic is how businesses can efficiently and effectively deliver outstanding customer service at scale. 

The does not mean removing humans from the equation but harnessing the power of voice technology to augment the services that people provide for greater customer service efficiency. It means using voice technology to properly understand the customer service issues your business is addressing and then leveraging the technology to drive efficiency through an organization for the benefit of its end users.

SOLVING OLD PROBLEMS NEW WAYS

The pain points we hear about now when it comes to customer service are not new pain points. But when you ask companies what their solution is, many have been looking at only slightly savvier variants of what they have already had in place. But Voice AI is a totally different solution. It draws on cloud processing power and advances in machine learning, with the ability to leverage data to identify and understand the top use cases that can are so these can be addressed. 

Leveraging modern technological advances to solve these old problems makes a lot of sense, but the difference is the new capability to do so in a very user centric way. We are thinking about the user experience, the end user. People respond really well to hearing support, and especially the empathy we build in to the voice narrative.

It’s important to recognise that there are pain points on both sides of the conversation. There are the pain points of the end user – “I need service now”, and “I need my issue resolved”. Accessibility can be an issue here because end users don’t necessarily know where to go to get support; they have to wait on hold for a while or experience incomplete support that may be unable to resolve their issue.

Scale can also be an issue. Imagine you’re at an airport, you can visualise the people waiting in line. If you’re at the customer service desk, you will know what type of questions are going to be asked again and again. But imagine it’s 10,000 people a month in that line. How do you identify and filter all the information that’s coming in? You don’t see the people angry on the phone, or at the chatbot. How do you tag that data? How do you determine the patterns in these conversations? What are the indicators for an escalation and how can this create give a great user experience? 

We are already seeing the rise of self-service activities – tag your own baggage, for example – so you can automate a line of 50 people waiting to get their bags checked. We need to be optimising these systems and creating better efficiencies.

There are already numerous examples of self-service activities that are being effectively delivered through voice AI technology using Smart IVR and multi-modal formats from I’m trying to replace my card to I’m trying to book a room or I’m having trouble accessing my account.

The technology isn’t going to solve all of the world’s problems. But that doesn’t mean that technology doesn’t have amazing potential and high prospective value. 

Source: MARTECHSERIES


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