Conversational AI Is the Future of Customer Experience

Sebastian Glock at Cognigy explains that with customer behaviour going through a whirlwind of changes, conversational AI is likely to become the new kingmaker in CX leadership.

From HAL 9000 in 2001: A Space Odyssey to the love interest in Her, pop culture set our expectations for conversational AI extremely high.

No wonder that the first generation of chatbots and ‘virtual assistants’ released a decade ago disappointed swaths of customers eager to experience what was once the realm of science fiction.

From repeating over and over that we are choosing ‘option three’ over the phone while a dehumanised voice responds ‘sorry, I did not quite get that’ to desperately needing some human empathy, our love affair with conversational AI seemed hopeless.

But, there is light at the end of the tunnel, and customers are about to be blown away!

Did We Get Off the Wrong Foot With Chatbots?

Businesses quickly fell in love with chatbots, implementing them in their customer-facing interfaces. However, this love affair was not necessarily always shared by their customers. The sharing of cringy chatbot replies has become a mainstay of Twitter for most of the past decade.

If chatbots were useful in orienting customers towards the right sources of information, they failed to provide the support and comfort that is often needed most when someone is seeking assistance.

The gap between the objectively useful purpose of chatbots – filtering through customer enquiries to ease pressure on customer support staff – and the desire for an understanding ear from customers created a lot of frustration.

The limited capabilities of the first generation of chatbots often harmed companies’ reputation and the very concept of chatbots. These early tools were perceived as blatant attempts at reducing interactions with customers, providing very little help and instead redirecting people towards generic help pages – an often-frustrating experience for customers.

There is an argument that businesses were too quick to adopt chatbots in their customer-facing interfaces. Now that chatbots and the field of conversational AI have made enormous strides, the challenge is to shift customers’ perception of these services crippled by the memory of struggles past.

Customer-Focused Conversational AI

The reality is that conversational AI has significantly improved thanks to machine learning (ML), artificial intelligence, and complex algorithms.

At a time where global productivity is lagging, due to the pandemic and pressures put on individuals, businesses need to consider advances made in AI to generate growth. Rather than easing the pressures on customer support teams and alleviating basic processes, conversational AI and customer support teams have continued to work side by side.

This is not necessary and an expense an organisation can do without. Thanks to the improvements in AI, repetitive calls can now be filtered and answered and the quality of interactions between customers and support staff can be enhanced – ultimately improving employee satisfaction, which is particularly vital in a sector that has a traditionally high labour turnover.

We need to reconsider our relationship with conversational AI because, considering the rapid progress made over the past decade, there is no future where shopping and conversational AI are not part of the same experience.

The past 18 months showed that online shopping is widely adopted. While this meant some businesses could keep operating during the pandemic, it increased demands for 24/7 customer support.

How Can a Chatbot Know How to Help

Sebastian Glock

Conversational AI refers to the technology behind chatbots and voice assistants. It uses ML, natural language processing (NLP), advanced dialogue management, and data to mimic human interactions.

As crazy as it sounds, when you are yelling at a voice assistant when trying to reschedule your flight, the technology is learning from your short temper! AI puts the customer at the centre of its attention, not only to learn but also to provide answers and help.

The technology first understands what you are saying thanks to NLP, automatic speech recognition, and text-to-speech algorithms. It then processes your words and creates a formal response – in a matter of a couple of seconds!

Machine learning helps software applications learn from historical data, spot patterns, make decisions and adapt without the need for constant monitoring and intervention from a human.

Automatic speech recognition is an exciting field of computer science that reinvents the way digital tools recognise and translate spoken language into text.

Changing the Game With Low-Code

Low-code conversational AI is making this technology more democratic and inclusive than ever before. Low-code means that it is within everyone’s reach – not requiring a dedicated team of coding experts to be able to make sense of its capabilities.

Hence, conversational AI platforms like Cognigy can be adopted by both large multinational conglomerates and your local bakery sending cakes online since the pandemic.

Conversational designers can create interfaces that allow for specificity in conversational AI without writing a line of code. Coding has always been an obstacle to widespread technology adoption. Call centre managers know the advantage of having staff able to speak many languages, but the coding language is rarely one of them.

The struggle to understand highly technical tools such as conversational AI solutions has often been a reason behind frustrating chatbot interactions since the technology is not set up to answer specific customer needs.

Now that this tool is within everyone’s reach, this stage of the customer journey can be seamlessly incorporated into the brand experience without having to train an already busy staff.

Conversational AI makes the customer experience better for everyone – regardless of whether or not each customer actually interacts with the technology.

For example, if you have 100 people in a waiting line and help 50 of those automatically, the other 50 only have to wait half the time to speak to a human that can help with their more complex issue. Bots not only help those they are directly dealing with but everyone seeking to interact with that business or service.

Data analytics can make conversational AI work even harder, tracking customer interactions and satisfaction to understand what is working and what needs more attention.

The reality is that chatbots got bad press. Yet, thanks to artificial intelligence and significant advancements, chatbots are now at the heart of customer experience. It is time to align our perception of conversational AI with the benefits they provide after years of rapid progress.

But there’s one way to do it properly: by putting the customer at the centre of conversational AI so that businesses can take part in the future of CX.

Author: Guest Author