Assistant bots vs. traditional interfaces

If you go to a big retail store like Walmart to buy something, your natural instinct would be to ask one of the human assistants about what you are looking for and where in the store you can find it. In some cases you may even tap into the expertise of those assistants to get reviews about a particular product or brand, whether that has worked good for other customers etc. Those assistants can tell you a lot more than what is available for everyone to see in the store. In other stores these assistants can be more proactive, they try to get into a conversation with you to understand your needs, your preferences and then advise you to your satisfaction.

In the digital world, the assistant bots do the similar thing. They can be on public websites, inside a customer portal, on mobile apps and have access to vast information via back office integrations. Businesses use them to guide and educate the potential and existing customers through their moments of need. These assistants provide that personalized engagement that the other traditional customer touch points have never been able to do.
However, these assistant bots or more popularly called chatbots can be very bad customer experience if they are poorly implemented. They can frustrate, confuse and ultimately bore the customers. In fact they can hurt the businesses by turning away those customers. 

AI to the rescue ?

With chatbots gaining popularity, it only makes sense that developers are attempting to make them better too. Enter artificial intelligence (AI) – the tech trend which is undoubtedly making chatbots smarter while simultaneously detracting from the user experience.  AI has progressed exponentially in recent years to become one of the most exciting tech possibilities in contemporary development. With great power comes great hype – and outfits in countless industries are attempting to leverage the technology even when it is unnecessary. A lot of developers make claims about their machine learning capabilities but seldom provide any evidence.

Want vs need

Common sense will say that smarter is always better – but this is not the case when it comes to the chatbot. The fact of the matter is that customers do not care how powerful the chatbot is. They care about how helpful and useful it is – and that is not synonymous with AI. Ultimately it all comes down to design and purpose. Some use cases demand a simple chatbot that has a predefined conversational flow and focuses on a limited set of functionality. Some other use cases demand a chatbot that supports more free flowing conversation which is more customer driven. In those cases it is critical to understand the intent of the customer and provide a relevant and personalized response. That’s where those chatbot implementation rely on powerful AI technologies like Natural Language Process(NLP) and intent mapping, and complex backend integrations.

Chatbots cannot be bought off the shelf to make them work for businesses. They need to be designed, educated and trained like a new employee fresh out of college.