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Conversational Commerce is still the future of e-commerce

Marketing Specialist

This blog deals with the importance of incorporating self-learning algorithms in virtual assistants. How self learning works and why is it so crucial in order to deploy a truly intelligent virtual assistant?
With self-learning, businesses can not only save time from constantly training the virtual assistant, but also resources from trying to always keep up with customers’ ever-changing needs.

With self-learning, businesses are entering a new era of automation and are able to see the true potential of conversational AI.

The superiority of virtual assistants over chatbots is undeniable. The main difference between these two solutions is the technology used; the first use
AI and statistical methods, while the latter are keyword-based.

Chatbots are rule-based, which means they “scan” messages for specific keywords, in order to provide an answer. If they fail, they fallback and
enter an infinite loop of rephrasing requests or transfer the user to a
customer support representative.

Virtual assistants on the other hand, use machine learning and supervised learning to understand the meaning of a sentence. They can be quickly trained to comprehend what the user desires, using a few examples the business provides. Hence, they can accurately understand sentences with unknown words and typos, providing an elevated experience for the end users.

For example, the business trains the virtual assistant with a few
example-questions regarding the business hours.
e.g. When are you open? What time can I come?
If a user asks “What time should I drop by?”, a chatbot will fallback while a virtual assistant will understand the meaning and provide the appropriate response.

Just like humans would work, but faster.

However, not all virtual assistants are equally smart and capable of improvement. Many use supervised learning, but very few use unsupervised learning, aka self-learning. And here lies the future of conversational AI.

Self-learning AI comprises of deep learning algorithms capable of
self-improving a virtual assistant, by analyzing large amounts of data and detecting patterns. Virtual assistants equipped with this capability can be a lot more than a customer support assistant.

One of the greatest business challenges is to understand what your market needs and expects. A lack of that knowledge can create a gap and subsequently, bad customer service and experience.

With self-learning, you can bridge the gap between customer needs and business offerings.

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