A while ago lots of people were saying chatbots were going to revolutionise the online world, but most of them turned out to be irritating and not all that useful. It seemed like the fabled chatbot era was over before it began. Since those ‘dark’ times, a lot has changed and the technology has finally started to catch up with the hype, with chatbots (or conversational AI) now able to be used across webchat, messenger services and using voice through voice assistants and traditional phone call IVRs.
So What Are Chatbots?Chatbots are essentially a service that users interact with via an interface, often appearing as a pop up on the side or bottom of a website, in a messenger or other mobile app. The good ones are focussed on helping people with questions about products or services or to complete tasks or transactions. All of this is done with the aim of taking the more mundane, repetitive processes off the customer service teams so they can be better utilised to deal with more complex issues that machines can’t manage.
Driven by Artificial Intelligence (AI), they seek to mimic human interactions without trying to pretend to be one. They provide real-time interaction with your business any time of the day or night , enabling businesses to service more people more efficiently and, if done right, improve customer satisfaction at the same time.
Brief History of ChatbotsSince the 1960s people have attempted to create an intelligent human/computer interaction based on a natural language model - a model based on interpreting and understanding language as humans use it, based on typing or speaking in plain English. The idea has permeated pop culture for a generation or more from Hal in ‘Space Odyssey’ through to more recent times like the character in ‘Her’ that Joaquin Phoenix falls in love with.
One of the original (and probably the most famous) bots was ELIZA - a chatbot therapist who offered some basic advice to her “patients”.
How Do They Work
More advanced chatbots use Natural Language Processing (NLP) or Natural Language Understanding to help computers comprehend requests and allow them to respond within the context. Chatbots using NLP understand the context and meaning behind a query, even when it doesn’t use a specified set of keywords. These chatbots also use Machine Learning (ML) to train their knowledge base to better understand topics and areas of expertise, allowing them to become more helpful to users as time goes on.
A virtual assistant like Siri will use a more complex conversational AI model. The assistant should be able to understand and respond to basic conversations and understand the nuances of the conversation. The first complex interaction is the language model and understanding the request, and the second part is to identify the action that needs to be taken to fulfill the request.
What Can Chatbots Do?
Depending on the implementation chatbots can also hand off conversations that they cannot assist with by seamlessly transferring the information you’ve already provided to a support agent that can continue the conversation. This still saves support staff time and if handled well does not cause any friction with the customer or prospect.
The power of a chatbot depends on two key criteria – the systems it is connected to and can interact with and the extent of the tasks it has been trained to handle. That said, one of the best features of a chatbot is that it can grow its capability over time, you can complete an initial roll out with a limited scope of tasks and integrations for a low price point then expand the use cases once the advantages of the platform become clearer to the business.
The Omni Channel Experience
A number of chatbot platforms can offer a true omni channel experience utilising a single core chatbot that can interact via website chat, Facebook Messenger, Virtual Assistants (like Google or Alexa) and also over telephone using text to voice and voice to text technologies (using a service like Twilio Voice API).
This approach provides efficiency in development of the core conversation flows (create it once and use it across multiple channels) whilst also allowing for branching with different variations of language or response across each channel.
It is also best practice to not attempt to hide the fact that people are interacting with a bot. There are a group of users that will prefer to interact with a human and refuse to chat with a computer – and it is far better if you don’t try to trick this cohort. You can always set up the chatbot to hand off to the correct human assistant for the group of people that prefer this interaction. If users aren’t forced into only using a chatbot then this is a fairly simple challenge to overcome.
Chatbots are evolving rapidly and becoming more powerful, with use cases extending far beyond the initial applications that had been imagined 50+ years ago. Organisations can leverage them as a business tool alongside traditional front-line staff to provide customer support and sales assistance. In an age when visitors are trying to connect with brands when it suits them, having an effective AI chatbot to guide and support these interactions means brands can connect with more users in helpful ways no matter the time of day.