A chatbot is an artificial intelligence software that’s designed to stimulate conversation with human users through messaging applications, websites or mobile apps. They’ve been created to help companies provide greater customer satisfaction, cut down on human errors and also save time.
In addition to this, they can make it easier for companies to approach global markets and are also very cost-effective if managed properly. But how do they work exactly?
How exactly do chatbots work?
Chatbots use pattern matching to classify text and ensure that a suitable response is built for the customer. Although it’s very technical, this is the most effective and commonly used concept in chatbots.
To put it simply, pattern matching is the process where the text input from the customer is compared with all of the text stored within a particular database. Once the chatbot finds a match between the two, it responds to the user - all in just a few seconds.
A standard structure for these patterns is AIML, which stands for artificial intelligence markup language. For this structure to work properly, it’s crucial that your chatbot can be fed as much data as possible.
Here’s a straightforward example of artificial intelligence markup language in action:
Another fundamental piece of machinery inside a chatbot is the text classifier. This is a type of algorithm where the chatbot will aim to classify particular snippets of text to generate a response to the customer.
Whoever is set the task of creating these text classifications will need to assign a set of predefined categories to free text. For example, classification categories could include words such as great work, unhappy or adequate.
So, for example…
Someone lands on your website and wants to make a complaint about one of your products. They may type in something like:
“Hi there. I ordered some curtains last week and for some strange reason, some pink floral ones have arrived. I’m all down for bright colours but unfortunately, I don’t think they’re really going to fit the vibe I’m going for in my brand new man cave.”
The word ‘unfortunately’ should then be detected by the bot and fall into a particular classification category. This should then allow the bot to generate a response to the user.
The response could be something along the lines of: “Hi there. Thanks for your message. Please could you let me know your name and the date you made the purchase so that I can look into this further?”
This approach is called sentiment analysis, where the chatbot will process particular words and determine whether they’re positive, negative or neutral. The most powerful chatbots are those which can understand these words the quickest and react to create the most precise response.
Artificial neural network
Artificial neural networks are one of the main tools used in machine learning. They play a huge role in the world of artificial intelligence and chatbots alike. Artificial neural networks are organised into three layers. These include:
- Input layers
- Hidden layers
- Output layers
Although very effective, artificial neural networks can be difficult to manage. This is because they require a considerable amount of computer power. However, their ability to outperform nearly any other machine learning algorithm makes it an extremely popular choice in the chatbot industry.
Now that you know the ins and outs of how a chatbot works, it’s the perfect time to learn even more about conversational marketing.
Learn more about the world of conversational marketing today
Artificial neural networks and text classifications are just a couple of concepts which you’ll need to get to grips with when you’re building your chatbot. To help you get your head around the ins and outs of conversational marketing, we’ve put together a guide which covers everything you need to know.