If you are considering adding a chatbot to your website in order to handle customer support for you or to improve your visitors’ experience in some other way, you might already be familiar with the fact that not all bots are created the same.
Likewise, they don’t all function the same. The main distinction is the one between the rule-based bots and their AI-based brethren. As you’ll see, AI bots win no matter the criteria for comparison you choose.
The global chatbot market is expected to hit the billion-dollar mark before 2025, so you should hop on board this growing trend and get a chatbot that suits your needs as soon as possible.
Get to know the basics
Rule-based chatbots depend on keywords in the questions they receive to understand the queries. Then, the chatbot will research predefined answers to provide a relevant response.
On the other hand, AI software-powered chatbots use machine learning and NLP to provide a more conversational experience. AI-powered chatbots also learn with more interactions using a process based on human reasoning.
How do rule-based chatbots work?
Rule-based bots have a limited range of purposes that they can be used for. This stems from the fact that they can only answer questions based on a predefined set of rules that are embedded into them. This feature makes it easier to train and get them started. Thus, it might seem that they have an upper edge over the competitors, as they are a bit easier to train and can be cheaper.
However, this advantage is also their main flaw, as these bots cannot learn on their own and will only provide the answers that the companies want them to provide. Once the customer asks something absent from the database, they have to pass the conversation to a human agent.
Rule-based chatbots also need instructions for performing every small to complex task. If anything that is out of the database comes their way, then the rule-based bots are stuck.
Another flaw of these bots is their inability to have a personalized communication. We all speak in different patterns, and one person could express the same idea or need using other words than somebody else. These bots are unable to recognize this unless they are trained for many nuances of human language.
Because of this, although rule-based bots can be quickly implemented, they are hard to maintain after a certain length of time.
Overall, rule-based chatbots’ main disadvantage is their inability to understand the context and learn independently. Therefore, there is often a disconnect between the end-user and the bot, leading to frustration and delays. Because of these shortcomings, rule-based bots cannot operate entirely autonomously. They must rely on human intervention whenever anything outside of their database arises.
What to know about AI-powered chatbots
AI bots are self-learning bots that are programmed with Natural Language Processing (NLP). Thanks to this, they can save you a lot of time and money in the long run.
They are an exceptionally efficient aid to companies with a lot of data as they can self-learn from the data. Because of this ability, unlike rule-based bots, they do not need to be updated after a specific interval of time.
Another advantage of AI-powered chatbots lies in the fact that they can be programmed to understand different languages and can even learn to read a customer’s emotions. This gives a more advanced, personalized overall experience.
With constant learning ability, AI bots can help provide personalized customer service to enhance customer engagement. Since AI bots can handle customer queries from end-to-end without human interaction required, they can be deployed for round-the-clock customer service.
Overall, you could call AI bots the more advanced type of chatbots, as, besides the matter mentioned above, they can also understand patterns of behavior. This gives them the ability to continuously improve as more data comes in, which provides them with a broader range of decision-making skills and much greater independence.
They are also more resource-efficient since they can handle highly complex support needs without requiring any human input. This enables organizations to optimize their staff numbers, either trimming down or reallocating human resources to more meaningful, revenue-generating projects. Meanwhile, end-users receive the on-demand support they need, maximizing satisfaction levels.
Conclusion
As you see, AI-bots offer the most bang for your buck because they can do everything a rule-based bot can do, along with much more complex and useful functionality. They can also add a much appreciated human touch to the conversation, which makes them more pleasant to interact with.