AI chatbots are a good start, but now’s the time to stand out from the crowd

“Am I talking to a real person?”

Before the internet, this would have seemed an absurd thought when talking to someone. Horror classics like The Thing, Invasion of the Body Snatchers and They Live have always played on our niggling fears that the people around us aren’t real people.

But that’s just the silver screen, right? In the real world, we could be confident back then that our daily interactions were human to human (or maybe human to pet!).

Today, you may frequently be asking yourself whether a live chat online is with someone, well… alive. Last year, 23% of customer service businesses were using AI chatbots, and 15% of us had talked to a corporate chatbot within the last 12 months. Servion Global Solutions predicts a hefty 75% of all customer service interactions will be through AI chatbot platforms within the next five years.

The upshot is that AI chatbots are here to stay, so let’s put aside the stats for now; it’s time to get back to basics.

You may be wondering what AI chatbots actually are, how chatbots work and what challenges and opportunities stand in their path. Or, you may already be a master of the chatbot platform. In which case, not only will we try to answer these earlier questions, we’re also going to explore how AI chatbot platforms can disrupt themselves before becoming disrupted by others – by building a deeper, more emotionally connected brand and customer experience (CX).

What are AI chatbots?

If you’re technically savvy enough to be online and reading this article, you’ve almost certainly encountered chatbots before. They’re computer programs that are designed to imitate human conversation through text.

Your bank might use simple chatbots to guide you toward FAQs and areas of the website where your questions can be answered without speaking to a real-life adviser. Yet there’s a big difference between a bare bones chatbot and more advanced conversational AI chatbots.

The most basic versions rely largely on programmed menus and decision trees, showing limited conversational skills. In other words, you’ll know you’re talking to a bot. Keyword recognition features can offer more appropriate and realistic responses, but they’re still unlikely to pass the Turing Test.

AI chatbots instead use artificial intelligence (admittedly, the name is a bit of a giveaway) to provide a more well-rounded and immersive experience. They can remember past interactions and, in some instances, contextualize conversations, allowing them to learn and improve their responses. To achieve this, more complex technologies and principles are at play, such as natural-language processing/understanding (NLP/NLU), machine learning (ML) and deep learning.

What can an AI chatbot do?

To answer this question, let’s first ask another. What do you want an AI chatbot to do? Chatbots are bound by the limitations of the underlying NLP and ML technologies, but they’re still being used in fascinating and creative ways across many industries.

Chatbots have been developed that can analyze medical information and help doctors diagnose illnesses based on patient histories and symptoms. The Insomnobot-3000 offers friendly night-time chit-chat for people who struggle to get to sleep. Others have been designed to offer conversational therapy and mental health support.

In education, AI chatbots can help new college students get through their first days on campus by offering housing application guidance and class registration services. Meanwhile, essay and assignment grading platforms are becoming more and more accurate with every passing day.

Legal chatbots can generate, review and analyze documents; perform due diligence; answer client queries; and develop leads. Financial services firms use chatbots to offer advice to customers, complete transactions, fine-tune insurance products and more. These examples are just the tip of the iceberg.  

And let’s not forget chatbots are also akin to virtual assistants such as Siri, Cortana and Alexa. That means you’re using these technologies every time you ask your Echo Dot to answer a frivolous vital question, order your favorite pizza, or annoy the neighbors with your ‘top’ playlists.

But while it’s now established what chatbots do well, it’s also time to start thinking about what chatbots can’t do alone, and the value of filling those gaps to make a better chatbot experience.

The pros and cons of chatbots

We’ve covered what AI chatbots are and some of the things they can do. Now, here are a few benefits and drawbacks to keep in mind:

Pros

• Fast, automated customer service 24 hours a day, seven days a week
• Serve an unlimited number of customers at the same time
• Help customers solve simple queries and tasks efficiently
• The best AI platforms remember and learn, essentially training themselves
• Free up staff by taking monotonous, time-consuming tasks off their hands
• Customer trust in AI chatbots is growing.

Cons

• 42% of brands say their number-one priority is creating a more human experience for their chatbot
• Many people (71% of Americans) still prefer the human touch
• Chatbots are easily replicated between competitors. No longer are they a competitive differentiator or brand experience
• In many cases, customers interact as they would with advanced search, not in a conversational way, to get what they need and go
• Chatbots aren’t perfect; customers expect online search tools to be accurate, and often have an expectation that chatbots will perform in a similar manner
• Some services are too complex for AI chatbots to handle
• They can only advance as fast as NLP and ML evolution
• They lack the tone of voice and body language capabilities needed to make a strong connection with people.

What’s next for chatbots in 2020? Brand differentiation!

The appetite for chatbot technology is growing; but the disruptors are fast becoming the disrupted. Between 2017 and 2018, the number of Facebook Messenger chatbots leaped from 100,000 to 300,000 – and the number of chatbots providers besides Facebook is growing by the day.

Now is the time for differentiation.

Chatbots have set a foundation for knowledge given in conversational form. However, for companies to build differentiated brand experiences, they will need to evolve from text to omnichannel engagement, with brand ambassadors becoming the customers’ champion.

Even their very being needs to evolve to make people more engaged with them.

One survey found that less than a third of people across all generations said chatbots are friendly and approachable – only slightly more said chatbots offer a “good” experience. These figures should hardly be surprising; when was the last time a corporate chatbot (intentionally) made you laugh or smile?  

Virtual assistants like Siri and Alexa are often better. They can be funny, playful or sassy, and they have tons of hidden Easter eggs in their programming to keep users coming back. They’re still a one-dimensional sensory experience though – you speak, they speak. It’s the same with messaging chatbots, you write, they write back.

If you’re more of a visual person, most voice assistants on the market won’t be able to work in the way you operate best. Same if you’re a verbal learner using a chatbot.

As competition in the chatbot industry heats up, all of these obstacles become ways to differentiate and stand out from the crowd.

Making a better chatbot: The digital human difference

Chatbots undoubtably have their place in the digital workforce. But there’s a huge gap between the value chatbots offer to customers and what real people offer. This is where digital humans can bridge an important gap in the customer experience.

Like AI chatbots, digital humans are available 24/7 and have access to massive amounts of data. Unlike AI chatbots, they have a face and a voice and use written words.

It makes for a more natural interface, which can be used to make the chatbot’s functionality more friendly and approachable – adding a welcoming smile, an affirmative nod and non-verbal cues we’ve spent millennia mastering as humans.

Digital humans also communicate in more than one way. They’re visual, they speak, they can use text and they rely on user actions in the form of speech. In this way, their communication covers all four bases of the VARK learning methodology, making the job of communicating information more effective, regardless who’s using it.

The results? A more inclusive, friendly and “human” way to interact with customers, even as the human touch becomes a rarer thing in business.

But that’s not all that should get brands excited. Digital humans are much better representative of a company’s brand than a chatbot could ever hope to be – they embody the uniqueness of the brands they work for, and they can’t be copied.

If customers wanted support from an insurance chatbot, they have tens of thousands of options. If, say, the Geico Gecko was giving that support, there’s only one brand in the world who could provide that experience.

The chatbot evolution has already begun

Chatbots have evolved a lot in the past few years, and no one can deny that AI-driven platforms are revolutionizing customer experiences.

But in a multidimensional world, one-dimensional solutions are just the first step on the CX journey – one that has already had the human experience hollowed out of it and replaced with technology that’s more functional than engaging.

The good news is that chatbots can become something more – and it doesn’t require a huge technical step to get there. The underlying conversational AI that makes the best chatbots work can be used to power the conversational abilities of a digital human. But that digital human can then speak, see, smile, laugh and converse in a more engaging way; a more human way.

AI chatbots are the much-needed knowledge foundation, but it’ll be digital humans that bring the experience to life, in a way no competitor could.

It’s this convergence of information, experience and brand that in 2020 will see the beginning of the chatbot evolution – the year when more chatbots find their voice, their face, and their personality.