Artificial Intelligence basically means a computer program that mimics the intelligence of a human being. This program can make decisions like a human being and can take actions according to the data provided.
Remember the last time you tried to get in touch with a company through its Facebook page?
Remember when you sent them a message on Facebook – you received an instant reply saying,
“Hey, thank you for getting in touch with us, here are some interesting articles to help you out, we will get back to you as soon as possible”.
Every website you go to that has a chat icon that is powered by an artificial intelligence program. These chatbots are fed with tons of data so that when an inquiry comes in, it quickly scans through all the data in its memory and answers questions accordingly.
How is AI revolutionizing the chatbot experience?
The goal that artificial intelligence is moving towards is “Understanding human needs before they anticipate them”.
We aren’t here obviously, but there has been great progress been made in this field.
A great example is e-commerce chat systems.
The e-commerce chatbots need to segregate regular queries which can be answered with pre-written templates versus queries that need to be forwarded to a support agent through a CRM.
For example, if the website sells Mangos, and a specific batch of mangos have received a large number of refund queries. When a new support ticket is generated requesting for a refund – the AI must now determine whether to forward it to higher management of process the refund by itself.
Here is where smart AI chatbots kick in. They first check the SKU of the mangos that have received a large number of refund queries. The AI then matches the SKU of the current support ticket to the ones that received refund queries earlier. If it is a match it processes a refund or a discount coupon.
An important feature to note here is the chatbots ability to sense language patterns.
A great example of this is GMAIL. Nowadays when you receive an email – Google has trained it’s AI to sense certain language patterns in the content of the emails. Based on these language patterns it gives you generic reply options like, “Sounds good”, “Will Check It Out”, etc.
This is how AI runs through chat content as well. It first senses if there are any matches to the language patterns that it has been fed and then it takes actions accordingly. This is just one way that the AI makes decisions.
How does the chatbot become AI Smart?
A chatbot that can truly impress is one that can learn and learn fast. Using Machine Learning Algorithms the AI is trained. Just like a child is taught manners using negative reinforcement. The Machine Learning Algorithms uses something known as Reinforcement learning.
Here whenever the AI makes a decision it is rewarded or punished based on the judgment of its decision. In this way – the AI slowly collects data over time. So if a child spills a bottle of jam and gets a good beating he knows that this action is a failure. When he shows his parents a drawing he made and gets a positive response – he knows that this is a good action and receives good feedback.
Just like training a child – the machine learning algorithms rewards or punishes the Artificial Intelligence on their decisions helping them slowly become a self-sufficient adult program over time. This helps the AI create a reserve of data on which to draw from while taking decisions on their own making it a truly smart AI.
So each time the chatbot responds to a message with the right call – it gets rewarded and when it makes the wrong call it gets punished. This gives the chatbot an idea on how to respond to the most common questions and in some rare cases – how to respond to unusual queries as well.
What are the features of A Smart AI enabled Chatbot?
1 – It is able to understand the context of a question in multiple languages.
When a chat query comes in, it could be anything from a general inquiry to an aggrieved customer. The AI should be well trained in understanding Natural Language Patterns (NLP). Once it gets a hang of certain language patterns it will be able to effectively take better decisions regarding the best response to the chat query.
2 – It should understand the intent of a question.
Let’s assume a customer sends in a price query via the chatbot on a website. The AI should be able to understand if this is a potential lead or not. If a price query has come in – it should be able to respond to the query with relevant pricing information because the intent of this questions is a prospect making a purchasing decision. Optionally it should have enough data to know whether or not to direct this query to a salesperson.
3 – It should be trained enough to provide an accurate first response
Using Machine Learning algorithms, the chatbot should be able to accurately read the query and instantly provide an accurate first response. For this to be effective the machine learning process is quite essential to helping the AI either respond with ppre-writtentemplates or understand if a human touch is needed to sort this problem or not.
While making a chatbot intelligent – it is essential that one clearly defines what the endgame goal of this training should be. Are you trying to help the chatbot give customer’s information? Or are you trying to get the chat to ask the user for information.
?The chatbots that ask the users for information are known as collectors and those that give information to the user are known as a helper.
If you are looking to create a great customer experience that yields long-term relationships that turn into sales, then it will better for you to train your chatbot as a helper.
The key to an effective helper chatbot is its ability to understand the context of a query and this is effectively achieved using Natural Language Processing.
Once you have effectively trained it and given it enough data to act as an employee taking decisions – you can automate much of your support and sales operations with a simple chat bot.