AI enabled chatbots to create stellar automated customer support experiences

Chatbots are on the rise and here to help make lives of people and businesses easier. Especially in customer support, chatbots are often used to help answer customer inquiries. However, chatbots are not always as good as we hope them to be. Frustrating and rigid question/answer flows ruin the customer experience and are hurting your brand reputation. Setting up a chatbot can also become very expensive and time consuming.

This article helps you to understand the different chatbot degrees for customer support and what pitfalls to be aware of when implementing a chatbot in your customer support.

What chatbot degrees are there for customer support?

When looking at chatbot and customer support automation, there are two axes you have to look at.

The first axis is the degree of humanity in the conversation. On the far left you have chatbots that are very much decision tree driven with simple questions and answers. On the far right you have chatbots that understand human language by using Artificial Intelligence (Conversational AI) and Natural Language Processing (NLP) technology. These chatbots are intent driven.

The second axis to look at is the degree of which personalization takes place. On the far left you have very general, FAQ based questions. On the far right you have personalized experiences like changing an order and cancelling a subscription.

What pitfalls are there when implementing a chatbot in your customer support?

Implementing a chatbot can be tricky, depending on the degree of personalization and the degree of humanity you want in your customer conversations. Here are the 3 biggest pitfalls when implementing automation in your customer support.

Using a DIY chatbot builder

The first pitfall is to use a DIY chatbot builder. Yes, it’s easy and quick, but you’re only building a simple chatbot that is not smart and not personalized . This ruins your customer support experiences and hurts your brand name.

Building a chatbot from scratch

Beginning from scratch for a chatbot can create good, human-like and personalized customer support experiences, but is also very expensive. Unless you are a big company that can spend 100K a year on chatbots, this is a no-go for small businesses.

Training the NLP engine yourself

To make human-like automation experiences with a chatbot, you have to train the NLP so it understands human language. This is a time consuming process where the NLP engine needs continuous corrections and learning. Here again the rule is that unless you’re a big company with dedicated Conversational AI experts, this is a no-go for small businesses.

NLP stands for Natural Language Processing. It’s a technology that is used for analyzing human language, either spoken or written. Every sentence is analyzed and scored using Artificial Intelligence and statistical models.

These models use previous sentences as a reference and look at the probability that a new sentence is pretty much the same. Let me give you an example. In the database we have the sentence: “I want to know the status of my order”.

The intent of this sentence is order_status and a chatbot can reply to this. If a new sentence comes in that we don’t have in our database, the model calculates the probability that the intent of that new sentence is the same. For example,“What’s the status of my order?”. Here the intent of this sentence is the same as the previous sentence. When a new sentence is correctly recognized, it is saved in the database and that’s how a chatbot gets smarter every day.

At Table Duck we create smart and personalized customer support experiences for small businesses without you having to train the NLP, build a chatbot from scratch or use a DIY chatbot builder that just isn’t creating that experience for you. We have predefined sets of intents with all the training data required to create a good experience. Our platform is an easy to use, non-time consuming way to automate your customer support.