They will soon become a cornerstone of our daily lives but what exactly is the difference between a chatbot and a virtual assistant?
- Are chatbots and virtual assistants the same?
- Myth 1: A chatbot is not intelligent enough 🧠
- Myth 2: A virtual assistant can carry out a wider range of functions
- Myth 3: A virtual assistant is better at remembering the context 💬
- Myth 4: Chatbots can’t remember previous interactions of information
- Myth 5: Chatbots can’t identify sentiment. 😢
- Myth 6: Keeping consistency across channels is harder with a chatbot
- A final note
The history of technological development is littered with examples of various formats fighting it out for market dominance. The VHS and the Betamax, the Blu-ray and HD DVD, or more recently the current virtual headset battle between HTC Vive and Oculus Rift. At times, these format wars will dictate what we refer to the new invention as. When purchasing a high-density optical disc we tend to ask for a Blu-ray for example.
Are chatbots and virtual assistants the same?
It depends on who you speak to. A school of thought exists which believes there is no difference and that either one could be an umbrella term for the conversational agent.
If this is the case then it seems redundant to have two names for the same function. Chatbot is by far the more popular term according to Google Trends.
In general, if its primary mode of interaction is through messaging (Slack, Facebook etc.) then you are communicating with a chatbot. There is an argument that the likes of Siri cannot be a chatbot because it exists outside of these channels. But this does not feel like enough of a differentiator.
In fact, of more importance is the function of the chatbot (or virtual assistant) that you employ. In this regard, there are some myths surrounding their capabilities that should be debunked.
Myth 1: A chatbot is not intelligent enough
Some of the most powerful chatbots are equipped with robust natural language processing in order to understand the meaning of an inquiry rather than simply the keywords.
Previous bots might have only been able to carry out a limited number of conversations through either hard-coding, wildcard matching of words and phrases or time-consuming keyword training. However, bots powered with NLP are now far more flexible. Unfortunately, many chatbots do not leverage true NLP and are giving chatbots a bad name.
Thanks to machine learning, chatbots will continue to improve and will produce higher self-service rates than ever before.
Myth 2: A virtual assistant can carry out a wider range of functions
While there might be some truth to this now, the gap between what the two hope to achieve is constantly narrowing.
In the past, the chatbot could only perform specific tasks, such as a password change or information about the weather. Whereas, the virtual assistant was more wide-ranging in what it offered.
Thanks to advancements in NLP and machine learning, however, this is changing. Chatbots are now far more diverse and can carry out more functions through their ability to understand natural language. The use of decision trees, for example, makes it far easier to discover the exact intent behind user inquiries, broadening its functionality even further.
Myth 3: A virtual assistant is better at remembering the context
Even now, virtual assistants still struggle to remember key information during conversations but chatbots are already proving they can store what you tell them.
For example, Inbenta’s chatbot Veronica is able to remember your email address if you provide it to her.
If you tell her “My email address is….” then she will retain that information for future use. Therefore, if you were to ask for a demo she would not require you to resubmit it.
Rather than debate what we should name them, it is important to recognize how the chatbot (or virtual assistant) will provide the most human-like experience possible by understanding our natural language to the best capabilities.
Myth 4: Chatbots can’t remember previous interactions with users
One of the most spread myths about chatbots is that they aren’t able to recall previous interactions with a user. A few years ago, that was true. However, nowadays, with the use of AI, chatbots collect information from the user, and not only can they refer to previous conversations, but they can also act accordingly.
Let’s say a user has made a purchase on an e-commerce site that uses an AI chatbot. That information is stored on the user’s profile and is accessible by the bot. This allows the chatbot to easily recommend similar or related products in a proactive way, or respond to requests of information regarding orders and track their delivery for the customers.
Myth 5: Chatbots can’t identify sentiment
Before, businesses would turn to virtual assistants for those applications where more human or emotional intelligence was needed. However, this is largely obsolete. Modern-day chatbots not only detect sentiment, but also learn with new interactions with visitors and customers, broadening the empathetic responses they can provide to reassure visitors whenever they have doubts or get angry due to transaction issues.
Myth 6: Keeping consistency across channels is hard with a chatbot
The implementation of chatbot instances use to be confusing, as support requests weren’t centralized and every channel instance of a chatbot require its own platform and responses. This created the idea that chatbots couldn’t keep consistency. Another issue is the common use of machine learning techniques, where chatbots learn by themselves without human supervision. The lack of human control over them can create patterns the lead bots to deliver different responses to the same questions depending on the user, the time of the date or hundreds of other variables.
All these scenarios together have damaged the image of chatbots in terms of consistency.
However, the use of Symbolic AI and NLP techniques, together with new platforms providing cross and omnichannel support have eliminated this issue and improved the way large organizations empower their customer service teams with chatbot solutions.
A Final Note on virtual assistant and chatbot
As both chatbot and virtual assistant technology improves, the lines between both of them become blurry and more difficult to define. It is likely that, in the years to come, both technologies will be assimilated into one and the names will be interchangeable.
Inbenta is a leader in natural language processing and artificial intelligence for customer support, e-commerce, and conversational chatbots providing an easy-to-deploy solution that improves customer satisfaction, reduces support costs, and increases revenue.
Interested in finding out more? Our team of experts is available to show you how Inbenta can benefit your company.
Check out our similar articles
- Proactive vs. Reactive Chatbots - Pros and Cons
- What is Digital Self-Service?
- Increase Productivity and Improve Employee Retention with HR Service Automation