Not so long ago, keyword queries in search engines were the norm.

You don’t know it, but Google and its simple-looking search box played an amazing trick on you. I’m not even sure they knew they were doing it in the early days, but they managed to convince us that if the string of words or phrases we entered generated the wrong results, it must be our fault. 

As users, we didn’t wonder why the search engine hadn’t understood what we wanted, we simply told ourselves we’d not been precise enough to get the results we were after.

Over 20 years, we’ve become used to thinking like machines when we interact with technology. What a brilliant bit of cognitive conditioning by the tech giants!

This ‘think-like-a-machine’ mindset has underpinned the customer experience since the dawn of computers and coding but proliferated with the explosion of the World Wide Web at the turn of the century.

Many of us, for example, will be familiar with the feeling of frustration after selecting the wrong delivery address, or accidentally putting an item in our basket multiple times when shopping online.

Surely in 2020, the technology we use should understand human behaviour, our imperfect nature and our natural ways of communicating? Getting answers from technology, and completing the tasks associated with them, should ultimately be as easy as asking a question of another human being.

Thanks to artificial intelligence and machine learning, we now have the ability to recognise and process natural language in online search. Something which has fundamentally changed the user experience and the way we interact with technology in our daily lives.

According to Google, conversational search has led to an increase in personalised queries related to the needs of the individual. For instance, mobile searches beginning with “do I need” and “should I” have grown by more than 65 percent in recent years, while 70 percent of requests to Google Assistant are expressed in natural language.

From self-serve portals, to chatbots and virtual assistants, automated customer service is now a staple of the way we engage with brands and content online. But there remains an expectation-reality gap in this process.

If the questions we ask are hard to understand, then we’re asked to clarify with a return question, often sparking an entirely ancillary conversation to pin-point exactly what it is the customer wants.

This problem with current automated customer service tools stems from the fact that many providers use off-the-shelf chatbots or generalist natural language processing (NLP) engines from providers like Amazon and Google.

The results are effectively glorified FAQ systems that lack the depth of understanding to handle complex, specific customer queries in relation to business-critical services.

Automating broad, wide-ranging conversations between humans and an AI interface to a high degree of accuracy is still tricky. But we can narrow the fields in which NLP platforms, and the machine learning capabilities associated with them, are deployed.

By focusing on specific areas of knowledge or industries, it’s now possible to harness the power of proprietary NLP platforms that better fulfil user requests within these verticals, for example by using conversational AI. And, since NLP is context-driven, customers can get the answers they’re looking for, even if their question isn’t spelled or worded correctly.

Fundamentally, it’s this capability to emulate truly human-like conversation that will take the customer experience to the next level. But there’s another opportunity here for brands to think carefully not just about how their customers communicate, but the channels they use, an area in which AI is opening up new possibilities.

With rising app fatigue in an attention economy, forward-thinking businesses are looking to some of the most widely used apps on the planet, such as WhatsApp and Facebook Messenger, as the next frontier for customer engagement.

Combining NLP with the most popular messaging apps and companies’ existing IT infrastructure – including order management and customer communication systems – has the ability to transform the entire customer experience.

Lightning quick time to respond. Fully personalised and contextualised replies to queries. Intelligent suggestions that reflect what the customer actually wants – not what you assume they want. It’s an exciting new world, and we have the tools to make it a reality right now.

From hyper-personification, to simpler ordering, to enhanced customer service, AI has the ability to bring brands and their customers closer together on the channels they use and love the most.

These are the kinds of user-focused experiences we must deliver in the era of AI. An era in which technology adapts to us, not the other way round, and finally puts an end to the frustrations caused by supposed ‘customer error’.

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