Automation got a bad reputation pretty quickly in the customer service world. Since the 1980s, calling customer support has meant being put on hold by automated phone systems repeating the unconvincing assurance: "Your call is very important to us".
Automated phone systems turned into chatbots. This technology could be just as frustrating with bots conducting clumsy conversations that failed to provide real help. In a 2019 survey, 86% of customers said they’d rather interact with a live agent if given a choice.
But in 2020, COVID-19 led to a spike in call volumes for both pharmacies and airlines. At the same time, sickness and social distancing reduced call centre capacity. Many companies turned to chatbots and virtual assistants to pick up the slack.
Suddenly, customers were forced to engage more with conversational AI – and often found they didn’t mind the change. By December 2020, only 18% of customers had a negative view of chatbots and a majority actually preferred bots with AI technologies for simple tasks like changing an address..
Have customers universally embraced conversational AI? Not necessarily. But they’re more comfortable with it, largely because the technology is more sophisticated than ever before,, meaning bots now speak using more natural, human language, greatly improving customers’ conversational experiences with bots.
To truly put customers at ease, it’s important to understand what they do and don’t like about conversational AI, and how automation can best be used to enhance CX.
What is conversational AI?
Conversational AI definition: artificial intelligence technologies that use data, machine learning and natural language processing (NLP) to recognise text and speech inputs and respond to users in their chosen language.
“Conversational AI is basically a machine talking with a human,” says Giovanna Chethuan Esguerra, a customer success consultant at Zendesk. “It can be through chatbot in a chat or messaging channel or through a voice assistant on the phone.”
One of the big advantages of conversational AI is that it’s cheaper than hiring more staff for your marketing, sales or support departments. However, Giovanna stresses that conversational AI chatbots should not be seen as an alternative to a human workforce. Instead, bots should be used to handle the most operational, repetitive and time-consuming tasks so humans are free to take on more challenging issues.
“AI has been introduced into consumers’ lives for some time now, through products like Siri and Alexa,” says Sam Chandler, a scaled success team manager at Zendesk. “But interestingly enough, only 20% of organisations that are aware of AI are actually using it. Many companies I’ve worked with are interested in machine learning tools like conversational AI but don’t feel savvy enough to leverage them effectively.”
Ideally, AI will complement a company’s broader life cycle and channel strategy. Conversational AI chatbots, for example, can work in tandem with self-service strategies such as help centres and FAQs. When a customer asks a chatbot for help returning an item, the bot can direct them toward a piece of content that explains the company’s return policy.
“Regardless of which form of AI you choose to explore, these investments are just like any other expenditure: they should fit into your CX strategy instead of becoming your CX strategy,” Sam stresses. “Make sure your AI investments reference your originally stated goals and include measurable KPIs to track viability.”
How do different customer demographics feel about conversational AI?
As one might expect, there’s a generational divide when it comes to consumer sentiment towards conversational AI.
“In our Zendesk CX Trends Report 2020, we found that many people are willing to interact with AI,” Giovanna says. “But mostly the younger generations (Gen Z and millennials) are more open to using it, if it works correctly, because they’ve grown up using more sophisticated technologies.”
Older customers sometimes aren’t aware that they’re interacting with a bot and can feel tricked once they realise they’re not talking to a human agent. Younger generations tend to be more AI-savvy. These digital natives have more experience with bots and are more enthusiastic about using them – if it means getting a faster or more accurate response.
Still, it’s also important to keep in mind that ‘younger generations’ is a relative term.
“A common misconception is that the ‘generational divide’ starts much earlier than it actually does,” Sam says. “Whilst it’s true that older generations tend to favour live channels, like voice, this curve begins much later than most companies believe – approximately between 70 and 80 years old.”
And this phenomenon is bound to change as generations who grew up with conversational AI get older themselves. There are even some contexts in which the ‘age gap’ is already pretty insignificant.
“When we look at the results of the study, we see that only a small minority of each age group disagrees with the statement ‘AI is useful to solve easy problems’," Giovanna points out.
In other words, people of all ages tend to think AI is fine for answering easy questions. However, customers are more resistant to bots if they have a more complex issue – especially if they’re an older baby boomer or part of the Silent Generation.
“But the real point is that if you’ve done your job right, none of that should really matter,” Sam says. “Chatbots are a way to bridge the gap between self-service and live agents. So, regardless of age or other demographics, your customers should be comfortable with those elements of your CX strategy or you’re going to run into adoption issues.”
Also, Sam warns against blaming your customer demographics for your own CX inadequacies. It’s possible that the way you’re implementing your conversational AI platform is more problematic than the technology itself.
“If you’re having an adoption issue, it could be because your customers don’t embrace that kind of channel,” she explains. “Or it could be that you’re attempting to force certain issue types into channels that aren’t ideal for the topic or for that point in your customer’s journey.”
How ‘human’ does an AI conversation need to seem?
A chatbot isn’t meant to fool someone into thinking that they’re talking to a real person. However, conversational AI should use language that customers are comfortable with.
“Even if a person knows they are talking to a bot, we should still make it the most natural and friendly experience possible,” Giovanna says. “For example, the AI should be configured to speak in the same terminology as our customers. And you should leverage all the customer data you possess to make the experience feel more personalised for the user.”
If your conversational AI platform is empowered with the right customer data, a chatbot can:
- Address a customer by name
- Refer to the customer’s status
- Know what products and services the customer has purchased
- See the path of the customer’s journey
With insight into a customer’s previous interactions, chatbots can provide less redundant and more helpful support.
“If a customer just read an article from our help centre, the bot should take that into account and suggest different content to resolve their issue,” Giovanna says. “A good way to achieve success with AI is to work on its development and use cases with designers, engineers and business stakeholders to ensure all parties bring their consumer and business knowledge to the table.”
Respect your customer enough to let them make their own decision on whether to engage with your chatbot. Let them choose if and when they want to flip over to a real agent.